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Williams CM, Henschke N, Maher CG, van Tulder MW, Koes BW, Macaskill P, Irwig L. Red flags to screen for vertebral fracture in patients presenting with low-back pain. Cochrane Database Syst Rev 2023; 11:CD008643. [PMID: 38014846 PMCID: PMC10683370 DOI: 10.1002/14651858.cd008643.pub3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/29/2023]
Abstract
EDITORIAL NOTE See https://www.cochranelibrary.com/cdsr/doi/10.1002/14651858.CD014461.pub2/full for a more recent review that covers this topic and has superseded this review. BACKGROUND Low-back pain (LBP) is a common condition seen in primary care. A principal aim during a clinical examination is to identify patients with a higher likelihood of underlying serious pathology, such as vertebral fracture, who may require additional investigation and specific treatment. All 'evidence-based' clinical practice guidelines recommend the use of red flags to screen for serious causes of back pain. However, it remains unclear if the diagnostic accuracy of red flags is sufficient to support this recommendation. OBJECTIVES To assess the diagnostic accuracy of red flags obtained in a clinical history or physical examination to screen for vertebral fracture in patients presenting with LBP. SEARCH METHODS Electronic databases were searched for primary studies between the earliest date and 7 March 2012. Forward and backward citation searching of eligible studies was also conducted. SELECTION CRITERIA Studies were considered if they compared the results of any aspect of the history or test conducted in the physical examination of patients presenting for LBP or examination of the lumbar spine, with a reference standard (diagnostic imaging). The selection criteria were independently applied by two review authors. DATA COLLECTION AND ANALYSIS Three review authors independently conducted 'Risk of bias' assessment and data extraction. Risk of bias was assessed using the 11-item QUADAS tool. Characteristics of studies, patients, index tests and reference standards were extracted. Where available, raw data were used to calculate sensitivity and specificity with 95% confidence intervals (CI). Due to the heterogeneity of studies and tests, statistical pooling was not appropriate and the analysis for the review was descriptive only. Likelihood ratios for each test were calculated and used as an indication of clinical usefulness. MAIN RESULTS Eight studies set in primary (four), secondary (one) and tertiary care (accident and emergency = three) were included in the review. Overall, the risk of bias of studies was moderate with high risk of selection and verification bias the predominant flaws. Reporting of index and reference tests was poor. The prevalence of vertebral fracture in accident and emergency settings ranged from 6.5% to 11% and in primary care from 0.7% to 4.5%. There were 29 groups of index tests investigated however, only two featured in more than two studies. Descriptive analyses revealed that three red flags in primary care were potentially useful with meaningful positive likelihood ratios (LR+) but mostly imprecise estimates (significant trauma, older age, corticosteroid use; LR+ point estimate ranging 3.42 to 12.85, 3.69 to 9.39, 3.97 to 48.50 respectively). One red flag in tertiary care appeared informative (contusion/abrasion; LR+ 31.09, 95% CI 18.25 to 52.96). The results of combined tests appeared more informative than individual red flags with LR+ estimates generally greater in magnitude and precision. AUTHORS' CONCLUSIONS The available evidence does not support the use of many red flags to specifically screen for vertebral fracture in patients presenting for LBP. Based on evidence from single studies, few individual red flags appear informative as most have poor diagnostic accuracy as indicated by imprecise estimates of likelihood ratios. When combinations of red flags were used the performance appeared to improve. From the limited evidence, the findings give rise to a weak recommendation that a combination of a small subset of red flags may be useful to screen for vertebral fracture. It should also be noted that many red flags have high false positive rates; and if acted upon uncritically there would be consequences for the cost of management and outcomes of patients with LBP. Further research should focus on appropriate sets of red flags and adequate reporting of both index and reference tests.
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Affiliation(s)
| | | | | | - Maurits W van Tulder
- MOVE Research Institute Amsterdam, Department of Human Movement Sciences, Faculty of Behavioural and Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Bart W Koes
- Center for Muscle and Health, University of Southern Denmark, Odense, Denmark
| | - Petra Macaskill
- Screening and Test Evaluation Program (STEP), School of Public Health, Sydney, Australia
| | - Les Irwig
- School of Public Health, University of Sydney, Sydney, Australia
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Ackermann DM, Dieng M, Medcalf E, Jenkins MC, van Kemenade CH, Janda M, Turner RM, Cust AE, Morton RL, Irwig L, Guitera P, Soyer HP, Mar V, Hersch JK, Low D, Low C, Saw RPM, Scolyer RA, Drabarek D, Espinoza D, Azzi A, Lilleyman AM, Smit AK, Murchie P, Thompson JF, Bell KJL. Assessing the Potential for Patient-led Surveillance After Treatment of Localized Melanoma (MEL-SELF): A Pilot Randomized Clinical Trial. JAMA Dermatol 2022; 158:33-42. [PMID: 34817543 PMCID: PMC8771298 DOI: 10.1001/jamadermatol.2021.4704] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2021] [Accepted: 09/28/2021] [Indexed: 12/20/2022]
Abstract
IMPORTANCE Patient-led surveillance is a promising new model of follow-up care following excision of localized melanoma. OBJECTIVE To determine whether patient-led surveillance in patients with prior localized primary cutaneous melanoma is as safe, feasible, and acceptable as clinician-led surveillance. DESIGN, SETTING, AND PARTICIPANTS This was a pilot for a randomized clinical trial at 2 specialist-led clinics in metropolitan Sydney, Australia, and a primary care skin cancer clinic managed by general practitioners in metropolitan Newcastle, Australia. The participants were 100 patients who had been treated for localized melanoma, owned a smartphone, had a partner to assist with skin self-examination (SSE), and had been routinely attending scheduled follow-up visits. The study was conducted from November 1, 2018, to January 17, 2020, with analysis performed from September 1, 2020, to November 15, 2020. INTERVENTION Participants were randomized (1:1) to 6 months of patient-led surveillance (the intervention comprised usual care plus reminders to perform SSE, patient-performed dermoscopy, teledermatologist assessment, and fast-tracked unscheduled clinic visits) or clinician-led surveillance (the control was usual care). MAIN OUTCOMES AND MEASURES The primary outcome was the proportion of eligible and contacted patients who were randomized. Secondary outcomes included patient-reported outcomes (eg, SSE knowledge, attitudes, and practices, psychological outcomes, other health care use) and clinical outcomes (eg, clinic visits, skin surgeries, subsequent new primary or recurrent melanoma). RESULTS Of 326 patients who were eligible and contacted, 100 (31%) patients (mean [SD] age, 58.7 [12.0] years; 53 [53%] men) were randomized to patient-led (n = 49) or clinician-led (n = 51) surveillance. Data were available on patient-reported outcomes for 66 participants and on clinical outcomes for 100 participants. Compared with clinician-led surveillance, patient-led surveillance was associated with increased SSE frequency (odds ratio [OR], 3.5; 95% CI, 0.9 to 14.0) and thoroughness (OR, 2.2; 95% CI, 0.8 to 5.7), had no detectable adverse effect on psychological outcomes (fear of cancer recurrence subscale score; mean difference, -1.3; 95% CI, -3.1 to 0.5), and increased clinic visits (risk ratio [RR], 1.5; 95% CI, 1.1 to 2.1), skin lesion excisions (RR, 1.1; 95% CI, 0.6 to 2.0), and subsequent melanoma diagnoses and subsequent melanoma diagnoses (risk difference, 10%; 95% CI, -2% to 23%). New primary melanomas and 1 local recurrence were diagnosed in 8 (16%) of the participants in the intervention group, including 5 (10%) ahead of routinely scheduled visits; and in 3 (6%) of the participants in the control group, with none (0%) ahead of routinely scheduled visits (risk difference, 10%; 95% CI, 2% to 19%). CONCLUSIONS AND RELEVANCE This pilot of a randomized clinical trial found that patient-led surveillance after treatment of localized melanoma appears to be safe, feasible, and acceptable. Experiences from this pilot study have prompted improvements to the trial processes for the larger trial of the same intervention. TRIAL REGISTRATION http://anzctr.org.au Identifier: ACTRN12616001716459.
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Affiliation(s)
- Deonna M. Ackermann
- School of Public Health, The University of Sydney, Sydney, New South Wales, Australia
| | - Mbathio Dieng
- National Health and Medical Research Council (NHMRC) Clinical Trials Centre, The University of Sydney, Sydney, New South Wales, Australia
| | - Ellie Medcalf
- School of Public Health, The University of Sydney, Sydney, New South Wales, Australia
| | - Marisa C. Jenkins
- School of Public Health, The University of Sydney, Sydney, New South Wales, Australia
| | | | - Monika Janda
- Centre for Health Services Research, The University of Queensland, Brisbane, Queensland, Australia
| | - Robin M. Turner
- Biostatistics Centre, University of Otago, Dunedin, Otago, New Zealand
| | - Anne E. Cust
- School of Public Health, The University of Sydney, Sydney, New South Wales, Australia
- Melanoma Institute Australia, The University of Sydney, Sydney, New South Wales, Australia
- The Daffodil Centre, The University of Sydney, Sydney, New South Wales, Australia
| | - Rachael L. Morton
- National Health and Medical Research Council (NHMRC) Clinical Trials Centre, The University of Sydney, Sydney, New South Wales, Australia
| | - Les Irwig
- School of Public Health, The University of Sydney, Sydney, New South Wales, Australia
| | - Pascale Guitera
- Melanoma Institute Australia, The University of Sydney, Sydney, New South Wales, Australia
- Royal Prince Alfred Hospital, Sydney, New South Wales, Australia
- Faculty of Medicine and Health, Sydney Medical School, The University of Sydney, Sydney, New South Wales, Australia
| | - H. Peter Soyer
- Dermatology Research Centre, The University of Queensland Diamantina Institute, The University of Queensland, Brisbane, Australia
| | - Victoria Mar
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
| | - Jolyn K. Hersch
- School of Public Health, The University of Sydney, Sydney, New South Wales, Australia
| | - Donald Low
- Cancer Voices New South Wales, Sydney, New South Wales, Australia
| | - Cynthia Low
- Cancer Voices New South Wales, Sydney, New South Wales, Australia
| | - Robyn P. M. Saw
- Melanoma Institute Australia, The University of Sydney, Sydney, New South Wales, Australia
- Faculty of Medicine and Health, Sydney Medical School, The University of Sydney, Sydney, New South Wales, Australia
| | - Richard A. Scolyer
- Melanoma Institute Australia, The University of Sydney, Sydney, New South Wales, Australia
- Royal Prince Alfred Hospital, Sydney, New South Wales, Australia
- Faculty of Medicine and Health, Sydney Medical School, The University of Sydney, Sydney, New South Wales, Australia
- New South Wales Health Pathology, Sydney, New South Wales, Australia
- Charles Perkins Centre, The University of Sydney, Sydney, New South Wales, Australia
| | - Dorothy Drabarek
- School of Public Health, The University of Sydney, Sydney, New South Wales, Australia
| | - David Espinoza
- National Health and Medical Research Council (NHMRC) Clinical Trials Centre, The University of Sydney, Sydney, New South Wales, Australia
| | - Anthony Azzi
- Newcastle Skin Check, Newcastle, New South Wales, Australia
| | | | - Amelia K. Smit
- School of Public Health, The University of Sydney, Sydney, New South Wales, Australia
- The Daffodil Centre, The University of Sydney, Sydney, New South Wales, Australia
| | - Peter Murchie
- Academic Primary Care Research Group, Division of Applied Health Sciences, University of Aberdeen, Aberdeen, Scotland, United Kingdom
| | - John F. Thompson
- Melanoma Institute Australia, The University of Sydney, Sydney, New South Wales, Australia
- Royal Prince Alfred Hospital, Sydney, New South Wales, Australia
| | - Katy J. L. Bell
- School of Public Health, The University of Sydney, Sydney, New South Wales, Australia
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Katz I, Irwig L, McGeehan K, Bell K. I need an exact margin measurement for this basal cell carcinoma! J Clin Pathol 2021; 75:857-860. [PMID: 34969782 DOI: 10.1136/jclinpath-2021-208030] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2021] [Accepted: 12/14/2021] [Indexed: 11/04/2022]
Abstract
BACKGROUND/OBJECTIVES Pathology laboratories are required to determine or estimate the measurement uncertainty for all quantitative results, but there is no literature on the uncertainty in margin measurements for skin cancer excisions. METHODS Six pathologists measured 4-14 histological margins in each of 10 basal cell carcinoma. RESULTS The mean of measurements from all the margins from all the cases was 1.8 mm (range 0 and 6 mm). Regarding the overall variance in margin measurements across the ten cases, 25% was from variation within cases (differences in margin measurement for a given case, because of different margins and different pathologists measuring each margin, SD 0.7 mm). For a given case, we estimate that 95% of margin measurements would fall approximately within±1.4 mm of the mean measurement for that case. When only pathologists' closest margin for each case were included (for the six cases with uninvolved margins), 6% of the overall variance was from differences within cases (because of different pathologists' measurements of the closest margin, SD 0.2 mm). For a given case without an involved margin, 95% of closest margin measurements would fall approximately within±0.5 mm of the mean closest measurement for that case. CONCLUSIONS Clinicians should be aware there is uncertainty in reported histological margins.
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Affiliation(s)
- Ian Katz
- Southern Sun Pathology, Thornleigh, New South Wales, Australia
| | - Les Irwig
- Faculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia
| | - Kevin McGeehan
- Faculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia
| | - Katy Bell
- Faculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia
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4
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Ackermann DM, Smit AK, Janda M, van Kemenade CH, Dieng M, Morton RL, Turner RM, Cust AE, Irwig L, Hersch JK, Guitera P, Soyer HP, Mar V, Saw RPM, Low D, Low C, Drabarek D, Espinoza D, Emery J, Murchie P, Thompson JF, Scolyer RA, Azzi A, Lilleyman A, Bell KJL. Can patient-led surveillance detect subsequent new primary or recurrent melanomas and reduce the need for routinely scheduled follow-up? A protocol for the MEL-SELF randomised controlled trial. Trials 2021; 22:324. [PMID: 33947444 PMCID: PMC8096155 DOI: 10.1186/s13063-021-05231-7] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2021] [Accepted: 03/27/2021] [Indexed: 02/03/2023] Open
Abstract
BACKGROUND Most subsequent new primary or recurrent melanomas might be self-detected if patients are trained to systematically self-examine their skin and have access to timely medical review (patient-led surveillance). Routinely scheduled clinic visits (clinician-led surveillance) is resource-intensive and has not been shown to improve health outcomes; fewer visits may be possible if patient-led surveillance is shown to be safe and effective. The MEL-SELF trial is a randomised controlled trial comparing patient-led surveillance with clinician-led surveillance in people who have been previously treated for localised melanoma. METHODS Stage 0/I/II melanoma patients (n = 600) from dermatology, surgical, or general practice clinics in NSW Australia, will be randomised (1:1) to the intervention (patient-led surveillance, n = 300) or control (usual care, n = 300). Patients in the intervention will undergo a second randomisation 1:1 to polarised (n = 150) or non-polarised (n = 150) dermatoscope. Patient-led surveillance comprises an educational booklet, skin self-examination (SSE) instructional videos; 3-monthly email/SMS reminders to perform SSE; patient-performed dermoscopy with teledermatologist feedback; clinical review of positive teledermoscopy through fast-tracked unscheduled clinic visits; and routinely scheduled clinic visits following each clinician's usual practice. Clinician-led surveillance comprises an educational booklet and routinely scheduled clinic visits following each clinician's usual practice. The primary outcome, measured at 12 months, is the proportion of participants diagnosed with a subsequent new primary or recurrent melanoma at an unscheduled clinic visit. Secondary outcomes include time from randomisation to diagnosis (of a subsequent new primary or recurrent melanoma and of a new keratinocyte cancer), clinicopathological characteristics of subsequent new primary or recurrent melanomas (including AJCC stage), psychological outcomes, and healthcare use. A nested qualitative study will include interviews with patients and clinicians, and a costing study we will compare costs from a societal perspective. We will compare the technical performance of two different models of dermatoscope (polarised vs non-polarised). DISCUSSION The findings from this study may inform guidance on evidence-based follow-up care, that maximises early detection of subsequent new primary or recurrent melanoma and patient wellbeing, while minimising costs to patients, health systems, and society. TRIAL REGISTRATION Australian New Zealand Clinical Trials Registry (ANZCTR): ACTRN12621000176864 . Registered on 18 February 2021.
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Affiliation(s)
- Deonna M Ackermann
- Sydney School of Public Health, Faculty of Medicine and Health, The University of Sydney, Sydney, Australia
| | - Amelia K Smit
- Cancer Epidemiology and Prevention Research, Sydney School of Public Health, Faculty of Medicine and Health, The University of Sydney, Sydney, Australia.,Melanoma Institute Australia, The University of Sydney, Sydney, Australia
| | - Monika Janda
- Centre for Health Services Research, The University of Queensland, Brisbane, Australia
| | - Cathelijne H van Kemenade
- Sydney School of Public Health, Faculty of Medicine and Health, The University of Sydney, Sydney, Australia
| | - Mbathio Dieng
- NHMRC Clinical Trials Centre, The University of Sydney, Sydney, Australia
| | - Rachael L Morton
- Melanoma Institute Australia, The University of Sydney, Sydney, Australia.,NHMRC Clinical Trials Centre, The University of Sydney, Sydney, Australia
| | - Robin M Turner
- Biostatistics Centre, University of Otago, Dunedin, New Zealand
| | - Anne E Cust
- Cancer Epidemiology and Prevention Research, Sydney School of Public Health, Faculty of Medicine and Health, The University of Sydney, Sydney, Australia.,Melanoma Institute Australia, The University of Sydney, Sydney, Australia
| | - Les Irwig
- Sydney School of Public Health, Faculty of Medicine and Health, The University of Sydney, Sydney, Australia
| | - Jolyn K Hersch
- Sydney School of Public Health, Faculty of Medicine and Health, The University of Sydney, Sydney, Australia
| | - Pascale Guitera
- Melanoma Institute Australia, The University of Sydney, Sydney, Australia.,Faculty of Medicine and Health, The University of Sydney, Sydney, Australia.,Sydney Melanoma Diagnostic Centre, Royal Prince Alfred Hospital, Sydney, Australia
| | - H Peter Soyer
- Dermatology Research Centre, The University of Queensland Diamantina Institute, The University of Queensland, Brisbane, Australia.,Department of Dermatology, Princess Alexandra Hospital, Brisbane, Australia
| | - Victoria Mar
- Victorian Melanoma Service, Alfred Health, Melbourne, Australia.,School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Robyn P M Saw
- Melanoma Institute Australia, The University of Sydney, Sydney, Australia.,Faculty of Medicine and Health, The University of Sydney, Sydney, Australia.,Division of Surgery, Royal Prince Alfred Hospital, Sydney, Australia
| | | | | | - Dorothy Drabarek
- Sydney School of Public Health, Faculty of Medicine and Health, The University of Sydney, Sydney, Australia
| | - David Espinoza
- NHMRC Clinical Trials Centre, The University of Sydney, Sydney, Australia
| | - Jon Emery
- Centre for Cancer Research, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Melbourne, Australia
| | - Peter Murchie
- Institute of Applied Health Sciences, University of Aberdeen, Aberdeen, United Kingdom
| | - John F Thompson
- Melanoma Institute Australia, The University of Sydney, Sydney, Australia.,Faculty of Medicine and Health, The University of Sydney, Sydney, Australia.,Division of Surgery, Royal Prince Alfred Hospital, Sydney, Australia
| | - Richard A Scolyer
- Melanoma Institute Australia, The University of Sydney, Sydney, Australia.,Faculty of Medicine and Health, The University of Sydney, Sydney, Australia.,Tissue Pathology and Diagnostic Oncology, Royal Prince Alfred Hospital and NSW Health Pathology, Sydney, Australia
| | - Anthony Azzi
- Newcastle Skin Check, Newcastle, Australia.,Faculty of Medicine, University of Queensland, Brisbane, Australia
| | - Alister Lilleyman
- Newcastle Skin Check, Newcastle, Australia.,Faculty of Medicine, University of Queensland, Brisbane, Australia
| | - Katy J L Bell
- Sydney School of Public Health, Faculty of Medicine and Health, The University of Sydney, Sydney, Australia.
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Hersch J, Barratt A, McGeechan K, Jansen J, Houssami N, Dhillon H, Jacklyn G, Irwig L, McCaffery K. Informing Women About Overdetection in Breast Cancer Screening: Two-Year Outcomes From a Randomized Trial. J Natl Cancer Inst 2021; 113:1523-1530. [PMID: 33871631 PMCID: PMC8562961 DOI: 10.1093/jnci/djab083] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2021] [Revised: 04/06/2021] [Accepted: 04/15/2021] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND Supporting well-informed decisions about breast cancer screening requires communicating that inconsequential disease may be detected, leading to overdiagnosis and overtreatment. Having previously shown that telling women about overdetection improved informed choice, we investigated effects on screening knowledge and participation over 2 years. METHODS We conducted a community-based, parallel-group, randomized controlled trial in Australia. Participants were women aged 48-50 years, without personal or strong family history of breast cancer, who had not undergone mammography in the past 2 years. We randomly assigned 879 women to receive the intervention decision aid (evidence-based information on overdetection, breast cancer mortality reduction, and false-positives) or control decision aid (identical but without overdetection information). We interviewed 838 women postintervention and recontacted them for follow-up at 6 months and 1 and 2 years. Main outcomes for this report are screening knowledge and participation. RESULTS We interviewed 790, 746, and 712 participants at 6 months, 1, and 2 years, respectively. The intervention group demonstrated superior knowledge throughout follow-up. After 2 years, conceptual knowledge was adequate in 123 (34.4%) of 358 women in the intervention group compared with 71 (20.1%) of 354 control participants(odds ratio = 2.04, 95% confidence interval = 1.46 to 2.85). Groups were similar in total screening participation (200 [55.1%] vs 204 [56.0%]; = 0.97, 95% confidence interval = 0.73 to 1.29). CONCLUSIONS A brief decision aid produced lasting improvement in women's understanding of potential consequences of screening, including overdetection, without changing participation rates. These findings support the use of decision aids for breast cancer screening.
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Affiliation(s)
- Jolyn Hersch
- School of Public Health, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia,Wiser Healthcare: A Research Collaboration for Reducing Overdiagnosis and Overtreatment, The University of Sydney, Sydney, NSW, Australia,Centre for Medical Psychology and Evidence-based Decision-making, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia,Sydney Health Literacy Lab, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia,Correspondence to: Jolyn Hersch, PhD, School of Public Health, Edward Ford Building A27, The University of Sydney, NSW 2006, Australia (e-mail: )
| | - Alexandra Barratt
- School of Public Health, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia,Wiser Healthcare: A Research Collaboration for Reducing Overdiagnosis and Overtreatment, The University of Sydney, Sydney, NSW, Australia
| | - Kevin McGeechan
- School of Public Health, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia,Wiser Healthcare: A Research Collaboration for Reducing Overdiagnosis and Overtreatment, The University of Sydney, Sydney, NSW, Australia
| | - Jesse Jansen
- Wiser Healthcare: A Research Collaboration for Reducing Overdiagnosis and Overtreatment, The University of Sydney, Sydney, NSW, Australia,Centre for Medical Psychology and Evidence-based Decision-making, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia,Sydney Health Literacy Lab, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia,Department of General Practice, Care and Public Health Research Institute (CAPHRI) School for Public Health and Primary Care, Maastricht University, Maastricht, The Netherlands
| | - Nehmat Houssami
- School of Public Health, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia,Wiser Healthcare: A Research Collaboration for Reducing Overdiagnosis and Overtreatment, The University of Sydney, Sydney, NSW, Australia
| | - Haryana Dhillon
- Centre for Medical Psychology and Evidence-based Decision-making, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia,School of Psychology, Faculty of Science, The University of Sydney, Sydney, NSW, Australia
| | - Gemma Jacklyn
- Wiser Healthcare: A Research Collaboration for Reducing Overdiagnosis and Overtreatment, The University of Sydney, Sydney, NSW, Australia
| | - Les Irwig
- School of Public Health, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia,Wiser Healthcare: A Research Collaboration for Reducing Overdiagnosis and Overtreatment, The University of Sydney, Sydney, NSW, Australia
| | - Kirsten McCaffery
- School of Public Health, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia,Wiser Healthcare: A Research Collaboration for Reducing Overdiagnosis and Overtreatment, The University of Sydney, Sydney, NSW, Australia,Centre for Medical Psychology and Evidence-based Decision-making, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia,Sydney Health Literacy Lab, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia
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6
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Gibson M, Scolyer RA, Soyer HP, Ferguson P, McGeechan K, Irwig L, Bell KJL. Estimating the potential impact of interventions to reduce over-calling and under-calling of melanoma. J Eur Acad Dermatol Venereol 2021; 35:1519-1527. [PMID: 33630379 DOI: 10.1111/jdv.17189] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2020] [Revised: 12/19/2020] [Accepted: 02/03/2021] [Indexed: 11/29/2022]
Abstract
BACKGROUND Pathologists sometimes disagree over the histopathologic diagnosis of melanoma. 'Over-calling' and 'under-calling' of melanoma may harm individuals and healthcare systems. OBJECTIVES To estimate the extent of 'over-calling' and 'under-calling' of melanoma for a population undergoing one excision per person and to model the impact of potential solutions. METHODS In this epidemiological modelling study, we undertook simulations using published data on the prevalence and diagnostic accuracy of melanocytic histopathology in the U.S. POPULATION We simulated results for 10 000 patients each undergoing excision of one melanocytic lesion, interpreted by one community pathologist. We repeated the simulation using a hypothetical intervention that improves diagnostic agreement between community pathologist and a specialist dermatopathologist. We then evaluated four scenarios for how melanocytic lesions judged to be neither clearly benign (post-test probability of melanoma < 5%), nor clearly malignant (post-test probability of melanoma > 90%) might be handled, before sending for expert dermatopathologist review to decide the final diagnosis. These were (1) no intervention before expert review, (2) formal second community pathologist review, (3) intervention to increase diagnostic agreement and (4) both the intervention and formal second community pathologist review. The main outcomes were the probability of 'over-calling' and 'under-calling' melanoma, and number of lesions requiring expert referral for each scenario. RESULTS For 10 000 individuals undergoing excision of one melanocytic lesion, interpreted by a community pathologist, a hypothetical intervention to improve histopathology agreement reduced the number of benign lesions 'over-called' as melanoma from 308 to 164 and the number of melanomas 'under-called' from 289 to 240. If all uncertain diagnoses were sent for expert review, the number of referrals would decrease from 1500 to 737 cases if formal second community pathologist review was used, and to 701 cases if the hypothetical intervention was additionally used. CONCLUSIONS Interventions to improve histopathology agreement may reduce melanoma 'over-calling' and 'under-calling'.
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Affiliation(s)
- M Gibson
- School of Public Health, Sydney Medical School, The University of Sydney, Camperdown, NSW, Australia.,Central Sydney Clinical School, Sydney Medical School, The University of Sydney, Camperdown, NSW, Australia.,Department of Dermatology, Royal Prince Alfred Hospital Sydney, Camperdown, NSW, Australia
| | - R A Scolyer
- Central Sydney Clinical School, Sydney Medical School, The University of Sydney, Camperdown, NSW, Australia.,Melanoma Institute of Australia, The University of Sydney, Camperdown, NSW, Australia.,Department of Tissue Pathology and Diagnostic Oncology, Royal Prince Alfred Hospital and New South Wales Health Pathology, Camperdown, NSW, Australia
| | - H P Soyer
- Dermatology Research Centre, The University of Queensland Diamantina Institute, The University of Queensland, Brisbane, Qld, Australia.,Dermatology Department, Princess Alexandra Hospital, Brisbane, Qld, Australia
| | - P Ferguson
- Central Sydney Clinical School, Sydney Medical School, The University of Sydney, Camperdown, NSW, Australia.,Melanoma Institute of Australia, The University of Sydney, Camperdown, NSW, Australia.,Department of Tissue Pathology and Diagnostic Oncology, Royal Prince Alfred Hospital and New South Wales Health Pathology, Camperdown, NSW, Australia
| | - K McGeechan
- School of Public Health, Sydney Medical School, The University of Sydney, Camperdown, NSW, Australia
| | - L Irwig
- School of Public Health, Sydney Medical School, The University of Sydney, Camperdown, NSW, Australia
| | - K J L Bell
- School of Public Health, Sydney Medical School, The University of Sydney, Camperdown, NSW, Australia
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7
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Affiliation(s)
- Katy J L Bell
- Edward Ford Building (A27), School of Public Health, University of Sydney, NSW 2006, Australia
| | - Paul Glasziou
- Institute for Evidence-Based Healthcare, Faculty of Health Sciences and Medicine, Bond University, Robina, QLD 4226, Australia
| | - Fiona Stanaway
- Edward Ford Building (A27), School of Public Health, University of Sydney, NSW 2006, Australia
| | - Patrick Bossuyt
- Department of Epidemiology and Data Science, Amsterdam Public Health, Amsterdam University Medical Centers, Amsterdam, Netherlands
| | - Les Irwig
- Edward Ford Building (A27), School of Public Health, University of Sydney, NSW 2006, Australia
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8
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Bell K, Doust J, McGeechan K, Horvath AR, Barratt A, Hayen A, Semsarian C, Irwig L. The potential for overdiagnosis and underdiagnosis because of blood pressure variability: a comparison of the 2017 ACC/AHA, 2018 ESC/ESH and 2019 NICE hypertension guidelines. J Hypertens 2021; 39:236-242. [PMID: 32773652 PMCID: PMC7810411 DOI: 10.1097/hjh.0000000000002614] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2020] [Revised: 07/02/2020] [Accepted: 07/12/2020] [Indexed: 11/25/2022]
Abstract
OBJECTIVE To estimate the extent that BP measurement variability may drive over- and underdiagnosis of 'hypertension' when measurements are made according to current guidelines. METHODS Using data from the National Health and Nutrition Examination Survey and empirical estimates of within-person variability, we simulated annual SBP measurement sets for 1 000 000 patients over 5 years. For each measurement set, we used an average of multiple readings, as recommended by guidelines. RESULTS The mean true SBP for the simulated population was 118.8 mmHg with a standard deviation of 17.5 mmHg. The proportion overdiagnosed with 'hypertension' after five sets of office or nonoffice measurements using the 2017 American College of Cardiology guideline was 3-5% for people with a true SBP less than 120 mmHg, and 65-72% for people with a true SBP 120-130 mmHg. These proportions were less than 1% and 14-33% using the 2018 European Society of Hypertension and 2019 National Institute for Health and Care Excellence guidelines (true SBP <120 and 120-130 mmHg, respectively). The proportion underdiagnosed with 'hypertension' was less than 3% for people with true SBP at least 140 mmHg after one set of office or nonoffice measurements using the 2017 American College of Cardiology guideline, and less than 18% using the other two guidelines. CONCLUSION More people are at risk of overdiagnosis under the 2017 American College of Cardiology guideline than the other two guidelines, even if nonoffice measurements are used. Making clinical decisions about cardiovascular prediction based primarily on absolute risk, minimizes the impact of blood pressure variability on overdiagnosis.
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Affiliation(s)
- Katy Bell
- School of Public Health, Faculty of Medicine and Health, The University of Sydney
| | - Jenny Doust
- New South Wales Health Pathology, Department of Clinical Chemistry and Endocrinology
| | - Kevin McGeechan
- School of Public Health, Faculty of Medicine and Health, The University of Sydney
| | | | - Alexandra Barratt
- School of Public Health, Faculty of Medicine and Health, The University of Sydney
| | - Andrew Hayen
- Australian Centre for Public and Population Health Research, University of Technology Sydney (UTS)
| | - Christopher Semsarian
- Agnes Ginges Centre for Molecular Cardiology at Centenary Institute
- Sydney Medical School, Faculty of Medicine and Health, The University of Sydney
- Department of Cardiology, Royal Prince Alfred Hospital, Sydney, Australia
| | - Les Irwig
- School of Public Health, Faculty of Medicine and Health, The University of Sydney
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9
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Walter SD, Turner RM, Macaskill P, McCaffery KJ, Irwig L. Correction to: Estimation of treatment preference effects in clinical trials when some participants are indifferent to treatment choice. BMC Med Res Methodol 2020; 20:82. [PMID: 32290817 PMCID: PMC7155340 DOI: 10.1186/s12874-020-00967-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
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10
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Bell KJL, Irwig L, Nickel B, Hersch J, Hayen A, Barratt A. Mammography screening for breast cancer-the UK Age trial. Lancet Oncol 2020; 21:e504. [PMID: 33152296 DOI: 10.1016/s1470-2045(20)30528-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2020] [Revised: 08/21/2020] [Accepted: 08/21/2020] [Indexed: 10/23/2022]
Affiliation(s)
- Katy J L Bell
- School of Public Health, Faculty of Medicine and Health, University of Sydney, Sydney, NSW 2006, Australia.
| | - Les Irwig
- School of Public Health, Faculty of Medicine and Health, University of Sydney, Sydney, NSW 2006, Australia
| | - Brooke Nickel
- School of Public Health, Faculty of Medicine and Health, University of Sydney, Sydney, NSW 2006, Australia
| | - Jolyn Hersch
- School of Public Health, Faculty of Medicine and Health, University of Sydney, Sydney, NSW 2006, Australia
| | - Andrew Hayen
- Australian Centre for Public and Population Health Research, University of Technology Sydney, Sydney, NSW, Australia
| | - Alexandra Barratt
- School of Public Health, Faculty of Medicine and Health, University of Sydney, Sydney, NSW 2006, Australia
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11
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Bell KJL, Azizi L, Nilsson PM, Hayen A, Irwig L, Östgren CJ, Sundström J. Correction: Prognostic impact of systolic blood pressure variability in people with diabetes. PLoS One 2019; 14:e0224538. [PMID: 31648270 PMCID: PMC6812757 DOI: 10.1371/journal.pone.0224538] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Abstract
[This corrects the article DOI: 10.1371/journal.pone.0194084.].
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12
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Dieng M, Smit AK, Hersch J, Morton RL, Cust AE, Irwig L, Low D, Low C, Bell KJL. Patients' Views About Skin Self-examination After Treatment for Localized Melanoma. JAMA Dermatol 2019; 155:914-921. [PMID: 31090868 DOI: 10.1001/jamadermatol.2019.0434] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Abstract
Importance Skin self-examination (SSE) is a key factor in the early detection of melanoma, and many new and recurrent melanomas are first detected by patients themselves or their family members. Objective To explore the views of patients with melanoma regarding SSE in general, as well as their attitudes toward using novel digital technologies to support their own SSE. Design, Setting, and Participants Qualitative study with semistructured interviews that were conducted from June 20 to December 12, 2016, with 37 individuals in Sydney, Australia, who were previously treated for a first primary localized melanoma during 2014 and had not had a recurrence or new primary melanoma in the time since treatment. Main Outcomes and Measures Patients' views and experiences, analyzed thematically. Results A total of 37 patients (11 women and 26 men; median age, 67 years [interquartile range, 59.5-72 years]) were interviewed. Participants perceived SSE as important for the early identification of local recurrence or new primary melanomas. Despite this belief, participants did not report undertaking full-body SSE on a regular basis. Factors that influenced their low engagement in thorough SSE included lack of self-efficacy, reliance on clinician consultations as the primary means of melanoma detection, and fear of cancer recurrence. Regarding the use of digital technology to assist with SSE, the key motivating factors in favor of such tools were the ability to track changes in lesions over time and the use of automated reminders to undertake SSE. Deterrents included a lack of confidence in undertaking SSE and in using new technology. Conclusions and Relevance Patients with melanoma are aware of the importance of thorough skin examinations. However, a lack of confidence in their ability to undertake SSE and reliance on clinicians as the primary means of melanoma detection may inhibit patients from undertaking regular and thorough SSE. Patients may benefit from new digital technologies that assist them in undertaking SSE, provided they have appropriate education and technical support.
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Affiliation(s)
- Mbathio Dieng
- National Health and Medical Research Council Clinical Trials Centre, The University of Sydney, Sydney, New South Wales, Australia.,Melanoma Institute Australia, The University of Sydney, Sydney, New South Wales, Australia
| | - Amelia K Smit
- Melanoma Institute Australia, The University of Sydney, Sydney, New South Wales, Australia.,Cancer Epidemiology and Prevention Research, The University of Sydney, Sydney, New South Wales, Australia
| | - Jolyn Hersch
- School of Public Health, The University of Sydney, Sydney, New South Wales, Australia
| | - Rachael L Morton
- National Health and Medical Research Council Clinical Trials Centre, The University of Sydney, Sydney, New South Wales, Australia.,Melanoma Institute Australia, The University of Sydney, Sydney, New South Wales, Australia
| | - Anne E Cust
- Melanoma Institute Australia, The University of Sydney, Sydney, New South Wales, Australia.,Cancer Epidemiology and Prevention Research, The University of Sydney, Sydney, New South Wales, Australia
| | - Les Irwig
- School of Public Health, The University of Sydney, Sydney, New South Wales, Australia
| | - Donald Low
- Cancer Voices New South Wales, Sydney, New South Wales, Australia
| | - Cynthia Low
- Cancer Voices New South Wales, Sydney, New South Wales, Australia
| | - Katy J L Bell
- School of Public Health, The University of Sydney, Sydney, New South Wales, Australia
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13
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Lim WY, Morton RL, Turner RM, Jenkins MC, Guitera P, Irwig L, Webster AC, Dieng M, Saw RPM, Low D, Low C, Bell KJL. Patient Preferences for Follow-up After Recent Excision of a Localized Melanoma. JAMA Dermatol 2019; 154:420-427. [PMID: 29490373 DOI: 10.1001/jamadermatol.2018.0021] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
Importance The standard model of follow-up posttreatment of localized melanoma relies on clinician detection of recurrent or new melanoma, through routinely scheduled clinics (clinician-led surveillance). An alternative model is to increase reliance on patient detection of melanoma, with fewer scheduled visits and increased support for patients' skin self-examination (SSE) (eg, using smartphone apps to instruct, prompt and record SSE, and facilitate teledermatology; patient-led surveillance). Objective To determine the proportion of adults treated for localized melanoma who prefer the standard scheduled visit frequency (as per Australian guideline recommendations) or fewer scheduled visits (adapted from the Melanoma Follow-up [MELFO] study of reduced follow-up). Design, Setting, and Participants This survey study used a telephone interview for surveillance following excision of localized melanoma at an Australian specialist center. We invited a random sample of 400 patients who had completed treatment for localized melanoma in 2014 to participate. They were asked about their preferences for scheduled follow-up, and experience of follow-up in the past 12 months. Those with a recurrent or new primary melanoma diagnosed by the time of interview (0.8-1.7 years since first diagnosis) were asked about how it was first detected and treated. SSE practices were also assessed. Main Outcomes and Measures Proportion preferring standard vs fewer scheduled clinic visits, median delay between detection and treatment of recurrent or new primary melanoma, and SSE practices. Results Of the 262 people who agreed to be interviewed, the mean (SD) age was 64.3 (14.3) years, and 93 (36%) were women. Among the 230 people who did not have a recurrent or new primary melanoma, 149 vs 81 preferred the standard vs fewer scheduled clinic visits option (70% vs 30% after adjusting for sampling frame). Factors independently associated with preferring fewer visits were a higher disease stage, melanoma on a limb, living with others, not having private health insurance, and seeing a specialist for another chronic condition. The median delay between first detection and treatment of recurrent or new primary melanoma was 7 and 3 weeks, respectively. Only 8% missed a scheduled visit, while 40% did not perform SSE or did so at greater than 3-month intervals. Conclusions and Relevance Some patients with melanoma may prefer fewer scheduled visits, if they are supported to do SSE and there is rapid clinical review of anything causing concern (patient-led surveillance).
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Affiliation(s)
- Wei-Yin Lim
- Clinical Research Centre Perak, Ministry of Health Malaysia, Ipoh, Perak, Malaysia.,School of Public Health, The University of Sydney, Sydney, New South Wales, Australia
| | - Rachael L Morton
- NHMRC Clinical Trials Centre, The University of Sydney, Sydney, New South Wales, Australia
| | - Robin M Turner
- School of Public Health and Community Medicine, University of New South Wales, Sydney, New South Wales, Australia
| | - Marisa C Jenkins
- School of Public Health, The University of Sydney, Sydney, New South Wales, Australia
| | - Pascale Guitera
- Melanoma Institute Australia, Sydney, New South Wales, Australia.,Discipline of Dermatology, The University of Sydney, Sydney, New South Wales, Australia.,The Sydney Melanoma Diagnostic Centre, Royal Prince Alfred Hospital, Camperdown, New South Wales, Australia
| | - Les Irwig
- School of Public Health, The University of Sydney, Sydney, New South Wales, Australia
| | - Angela C Webster
- School of Public Health, The University of Sydney, Sydney, New South Wales, Australia
| | - Mbathio Dieng
- School of Public Health, The University of Sydney, Sydney, New South Wales, Australia.,NHMRC Clinical Trials Centre, The University of Sydney, Sydney, New South Wales, Australia
| | - Robyn P M Saw
- Melanoma Institute Australia, Sydney, New South Wales, Australia.,Discipline of Surgery, The University of Sydney, Sydney, New South Wales, Australia.,Division of Surgery, Royal Prince Alfred Hospital, Camperdown, New South Wales, Australia
| | - Donald Low
- Cancer Voices NSW, Sydney, New South Wales, Australia
| | - Cynthia Low
- Cancer Voices NSW, Sydney, New South Wales, Australia
| | - Katy J L Bell
- School of Public Health, The University of Sydney, Sydney, New South Wales, Australia.,Centre for Evidence Based Practice, Bond University, Gold Coast, Queensland, Australia
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14
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Nayak A, Hayen A, Zhu L, McGeechan K, Glasziou P, Irwig L, Doust J, Gregory G, Bell K. Legacy effects of statins on cardiovascular and all-cause mortality: a meta-analysis. BMJ Open 2018; 8:e020584. [PMID: 30287603 PMCID: PMC6173243 DOI: 10.1136/bmjopen-2017-020584] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/10/2017] [Revised: 05/18/2018] [Accepted: 07/31/2018] [Indexed: 12/29/2022] Open
Abstract
OBJECTIVES To assess evidence for 'legacy' (post-trial) effects on cardiovascular disease (CVD) mortality and all-cause mortality among adult participants of placebo-controlled randomised controlled trials (RCTs) of statins. DESIGN Meta-analysis of aggregate data. SETTING/PARTICIPANTS Placebo-controlled statin RCTS for primary and secondary CVD prevention. METHODS Data sources: PubMed, Embase from inception and forward citations of Cholesterol Treatment Trialists' Collaborators RCTs to 16 June 2016. STUDY SELECTION Two independent reviewers identified all statin RCT follow-up reports including ≥1000 participants, and cardiovascular and all-cause mortality. DATA EXTRACTION AND SYNTHESIS Two independent reviewers extracted data in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. MAIN OUTCOMES Post-trial CVD and all-cause mortality. RESULTS We included eight trials, with mean post-trial follow-up ranging from 1.6 to 15.1 years, and including 13 781 post-trial deaths (6685 CVD). Direct effects of statins within trials were greater than legacy effects post-trials. The pooled data from all eight studies showed no evidence overall of legacy effects on CVD mortality, but some evidence of legacy effects on all-cause mortality (p=0.01). Exploratory subgroup analysis found possible differences in legacy effect for primary prevention trials compared with secondary prevention trials for both CVD mortality (p=0.15) and all-cause mortality (p=0.02). Pooled post-trial HR for the three primary prevention studies demonstrated possible post-trial legacy effects on CVD mortality (HR=0.87; 95% CI 0.79 to 0.95) and on all-cause mortality (HR=0.90; 95% CI 0.85 to 0.96). CONCLUSIONS Possible post-trial statin legacy effects on all-cause mortality appear to be driven by the primary prevention studies. Although these relative benefits were smaller than those observed within the trial, the absolute benefits may be similar for the two time periods. Analysis of individual patient data from follow-up studies after placebo-controlled statin RCTs in lower-risk populations may provide more definitive evidence on whether early treatment of subclinical atherosclerosis is likely to be beneficial.
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Affiliation(s)
- Agnish Nayak
- UNSW Medicine, University of New South Wales, Sydney, New South Wales, Australia
| | - Andrew Hayen
- Australian Centre for Public and Population Health Research, University of Technology Sydney, Sydney, New South Wales, Australia
| | - Lin Zhu
- Australian Centre for Public and Population Health Research, University of Technology Sydney, Sydney, New South Wales, Australia
| | - Kevin McGeechan
- University of Sydney School of Public Health, The University of Sydney, Sydney, New South Wales, Australia
| | - Paul Glasziou
- Centre for Research in Evidence Based Practice, Bond University, Gold Coast, Queensland, Australia
| | - Les Irwig
- University of Sydney School of Public Health, The University of Sydney, Sydney, New South Wales, Australia
| | - Jenny Doust
- Centre for Research in Evidence Based Practice, Bond University, Gold Coast, Queensland, Australia
| | - Gabriel Gregory
- The University of Sydney School of Medicine, The University of Sydney, Sydney, New South Wales, Australia
| | - Katy Bell
- University of Sydney School of Public Health, The University of Sydney, Sydney, New South Wales, Australia
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15
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Lim WY, Turner RM, Morton RL, Jenkins MC, Irwig L, Webster AC, Dieng M, Saw RPM, Guitera P, Low D, Low C, Bell KJL. Use of shared care and routine tests in follow-up after treatment for localised cutaneous melanoma. BMC Health Serv Res 2018; 18:477. [PMID: 29925350 PMCID: PMC6011416 DOI: 10.1186/s12913-018-3291-7] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2018] [Accepted: 06/11/2018] [Indexed: 11/22/2022] Open
Abstract
BACKGROUND Patients may decide to undertake shared care with a general practitioner (GP) during follow-up after treatment for localised melanoma. Routine imaging tests for surveillance may be commonly used despite no evidence of clinical utility. This study describes the frequency of shared care and routine tests during follow-up after treatment for localised melanoma. METHODS We randomly sampled 351 people with localised melanoma [American Joint Cancer Committee (AJCC) substages 0 - II] who had not had recurrent or new primary melanoma diagnosed from a total of 902 people diagnosed and treated for localised melanoma at a specialist centre in 2014. We interviewed participants by telephone about their experience of follow-up in the past year, and documented the proportion of patients who were undertaking shared care follow-up with a GP. We also recorded the frequency and type of investigations during follow-up. We calculated weighted estimates that are representative of the full inception cohort. RESULTS Of the 351 people who were invited to participate, 230 (66%) people consented to the telephone interview. The majority undertook shared care follow-up with a GP (61%). People who choose to have shared care follow-up with a GP are more likely to be male (p = 0.006), have lower AJCC stage (p for trend = 0.02), reside in more remote areas (p for trend< 0.001), and are less likely to have completed secondary school (p < 0.001). Few people saw a non-doctor health practitioner as part of their follow-up (9%). Many people report undergoing tests for melanoma, much of which may be routine tests for surveillance (37%). CONCLUSIONS The majority of people treated for a first primary localised melanoma at a specialist centre, without recurrent or new melanoma, choose to undertake shared care follow-up with a GP. Many appear to have routine diagnostic imaging as part of their melanoma surveillance.
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Affiliation(s)
- Wei-Yin Lim
- Clinical Research Centre Perak, Ministry of Health Malaysia, Ipoh, Perak Malaysia
- School of Public Health, The University of Sydney, Sydney, NSW Australia
| | - Robin M. Turner
- Dunedin School of Medicine, University of Otago, Dunedin, New Zealand
| | - Rachael L. Morton
- NHMRC Clinical Trials Centre, The University of Sydney, Sydney, NSW Australia
| | - Marisa C. Jenkins
- School of Public Health, The University of Sydney, Sydney, NSW Australia
| | - Les Irwig
- School of Public Health, The University of Sydney, Sydney, NSW Australia
| | - Angela C. Webster
- School of Public Health, The University of Sydney, Sydney, NSW Australia
| | - Mbathio Dieng
- School of Public Health, The University of Sydney, Sydney, NSW Australia
- NHMRC Clinical Trials Centre, The University of Sydney, Sydney, NSW Australia
| | - Robyn P. M. Saw
- Melanoma Institute Australia, Sydney, NSW Australia
- Discipline of Surgery, The University of Sydney, Sydney, NSW Australia
- Division of Surgery, Royal Prince Alfred Hospital, Camperdown, NSW Australia
| | - Pascale Guitera
- Melanoma Institute Australia, Sydney, NSW Australia
- Discipline of Dermatology, The University of Sydney, Sydney, NSW Australia
- The Sydney Melanoma Diagnostic Centre, Royal Prince Alfred Hospital, Camperdown, NSW Australia
| | - Donald Low
- Cancer Voices NSW, Sydney, NSW Australia
| | | | - Katy J. L. Bell
- School of Public Health, The University of Sydney, Sydney, NSW Australia
- Centre for Evidence Based Practice, Bond University, Gold Coast, QLD Australia
- The University of Sydney, Rm 333 Edward Ford Building (A27), Sydney, NSW 2006 Australia
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16
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Bell KJL, Azizi L, Nilsson PM, Hayen A, Irwig L, Östgren CJ, Sundröm J. Prognostic impact of systolic blood pressure variability in people with diabetes. PLoS One 2018; 13:e0194084. [PMID: 29641538 PMCID: PMC5894975 DOI: 10.1371/journal.pone.0194084] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2017] [Accepted: 02/24/2018] [Indexed: 11/19/2022] Open
Abstract
Objective Blood pressure variability (BPV) has been associated with risk of cardiovascular events in observational studies, independently of mean BP levels. In states with higher autonomic imbalance, such as in diabetes, the importance of BP variability may theoretically be even greater. We aimed to investigate the incremental value of BPV for prediction of cardiovascular and all-cause mortality in patients with type 2 diabetes. Methods We identified 9,855 patients without pre-existing cardiovascular disease who did not change BP-lowering treatment during the observation period from a Swedish primary health care cohort of patients with type 2 diabetes. BPV was summarized as the standard deviation (SD), coefficient of variation (CV), or variation independent of mean (VIM). Patients were followed for a median of 4 years and associations with cardiovascular and all-cause mortality were investigated using Cox proportional hazards models. Results BPV was not associated with cardiovascular specific or all-cause mortality in the total sample. In patients who were not on BP-lowering drugs during the observation period (n = 2,949), variability measures were associated with all-cause mortality: hazard ratios were 1.05, 1.04 and 1.05 for 50% increases in SD, CV and VIM, respectively, adjusted for Framingham risk score risk factors, including mean BP. However, the addition of the variability measures in this subgroup only led to very minimal improvement in discrimination, indicating they may have limited clinical usefulness (change in C-statistic ranged from 0.000–0.003 in all models). Conclusions Although BPV was independently associated with all-cause mortality in diabetes patients in primary care who did not have pre-existing cardiovascular disease or BP-lowering drugs, it may be of minimal clinical usefulness above and beyond that of other routinely measured predictors, including mean BP.
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Affiliation(s)
- Katy J. L. Bell
- Sydney School of Public Health, University of Sydney, Sydney, New South Wales, Australia
- * E-mail:
| | - Lamiae Azizi
- School of Mathematics and Statistics, University of Sydney, Sydney, New South Wales, Australia
| | - Peter M. Nilsson
- Department of Clinical Sciences, Lund University, Malmo, University Hospital, Malmo, Sweden
| | - Andrew Hayen
- Australian Centre for Public and Population Health Research University of Technology Sydney (UTS), Sydney, New South Wales, Australia
| | - Les Irwig
- Sydney School of Public Health, University of Sydney, Sydney, New South Wales, Australia
| | - Carl J. Östgren
- Department of Medical and Health Sciences, Linkoping University, Linkoping, Sweden
| | - Johan Sundröm
- Department of Medical Sciences, Uppsala University, Uppsala, Sweden
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17
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Bonner C, Bell K, Jansen J, Glasziou P, Irwig L, Doust J, McCaffery K. Should heart age calculators be used alongside absolute cardiovascular disease risk assessment? BMC Cardiovasc Disord 2018; 18:19. [PMID: 29409444 PMCID: PMC5801811 DOI: 10.1186/s12872-018-0760-1] [Citation(s) in RCA: 31] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2017] [Accepted: 01/26/2018] [Indexed: 12/27/2022] Open
Abstract
Background National estimates of ‘heart age’ by government health organisations in the US, UK and China show most people have an older heart age than current age. While most heart age calculators are promoted as a communication tool for lifestyle change, they may also be used to justify medication when clinical guidelines advocate their use alongside absolute risk assessment. However, only those at high absolute risk of a heart attack or stroke are likely to benefit from medication, and it is not always clear how heart age relates to absolute risk. This article aims to: 1) explain how heart age calculation methods relate to absolute risk guidelines; 2) summarise research investigating whether heart age improves risk communication; and 3) discuss implications for the use of medication and shared decision making in clinical practice. Main body There is a large and growing number of heart age models and online calculators, but the clinical meaning of an older heart age result is highly variable. An older heart age result may indicate low, moderate or high absolute risk of a heart attack or stroke in the next 5-10 years, and the same individual may receive a younger or older heart age result depending on which calculator is used. Heart age may help doctors convey the need to change lifestyle, but it cannot help patients make an informed choice about medication to reduce CVD risk. Conclusion Interactive heart age tools may be helpful as a communication tool to initiate lifestyle change to reduce risk factors. However, absolute risk should be used instead of heart age to enable informed decision making about medication, to avoid unnecessary treatment of low risk people. Evidence-based decision aids that improve patient understanding of absolute risk should be considered as alternatives to heart age calculators for lifestyle and medication decisions.
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Affiliation(s)
- Carissa Bonner
- Wiser Healthcare Program, Sydney School of Public Health, The University of Sydney, Camperdown, NSW, 2006, Australia. .,Centre for Medical Psychology and Evidence-based Decision-making (CeMPED), The University of Sydney, Camperdown, NSW, 2006, Australia.
| | - Katy Bell
- Wiser Healthcare Program, Sydney School of Public Health, The University of Sydney, Camperdown, NSW, 2006, Australia.,Faculty of Health Sciences and Medicine, Bond University, Robina, QLD, 4229, Australia
| | - Jesse Jansen
- Wiser Healthcare Program, Sydney School of Public Health, The University of Sydney, Camperdown, NSW, 2006, Australia.,Centre for Medical Psychology and Evidence-based Decision-making (CeMPED), The University of Sydney, Camperdown, NSW, 2006, Australia
| | - Paul Glasziou
- Wiser Healthcare Program, Sydney School of Public Health, The University of Sydney, Camperdown, NSW, 2006, Australia.,Faculty of Health Sciences and Medicine, Bond University, Robina, QLD, 4229, Australia
| | - Les Irwig
- Wiser Healthcare Program, Sydney School of Public Health, The University of Sydney, Camperdown, NSW, 2006, Australia
| | - Jenny Doust
- Wiser Healthcare Program, Sydney School of Public Health, The University of Sydney, Camperdown, NSW, 2006, Australia.,Faculty of Health Sciences and Medicine, Bond University, Robina, QLD, 4229, Australia
| | - Kirsten McCaffery
- Wiser Healthcare Program, Sydney School of Public Health, The University of Sydney, Camperdown, NSW, 2006, Australia.,Centre for Medical Psychology and Evidence-based Decision-making (CeMPED), The University of Sydney, Camperdown, NSW, 2006, Australia
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18
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Hersch J, McGeechan K, Barratt A, Jansen J, Irwig L, Jacklyn G, Houssami N, Dhillon H, McCaffery K. How information about overdetection changes breast cancer screening decisions: a mediation analysis within a randomised controlled trial. BMJ Open 2017; 7:e016246. [PMID: 28988168 PMCID: PMC5640026 DOI: 10.1136/bmjopen-2017-016246] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/02/2017] [Revised: 08/14/2017] [Accepted: 08/17/2017] [Indexed: 11/11/2022] Open
Abstract
OBJECTIVES In a randomised controlled trial, we found that informing women about overdetection changed their breast screening decisions. We now present a mediation analysis exploring the psychological pathways through which study participants who received the intervention processed information about overdetection and how this influenced their decision-making. We examined a series of potential mediators in the causal chain between exposure to overdetection information and women's subsequently reported breast screening intentions. DESIGN Serial multiple mediation analysis within a randomised controlled trial. SETTING New South Wales, Australia. PARTICIPANTS 811 women aged 48-50 years with no personal history of breast cancer. INTERVENTIONS Two versions of a decision aid giving women information about breast cancer deaths averted and false positives from mammography screening, either with (intervention) or without (control) information on overdetection. MAIN OUTCOME Intentions to undergo breast cancer screening in the next 2-3 years. MEDIATORS Knowledge about overdetection, worry about breast cancer, attitudes towards breast screening and anticipated regret. RESULTS The effect of information about overdetection on women's breast screening intentions was mediated through multiple cognitive and affective processes. In particular, the information led to substantial improvements in women's understanding of overdetection, and it influenced-both directly and indirectly via its effect on knowledge-their attitudes towards having screening. Mediation analysis showed that the mechanisms involving knowledge and attitudes were particularly important in determining women's intentions about screening participation. CONCLUSIONS Even in this emotive context, new information influenced women's decision-making by changing their understanding of possible consequences of screening and their attitudes towards undergoing it. These findings emphasise the need to provide good-quality information on screening outcomes and to communicate this information effectively, so that women can make well-informed decisions. TRIAL REGISTRATION NUMBER This study was prospectively registered with the Australian New Zealand Clinical Trials Registry (ACTRN12613001035718) on 17 September 2013.
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Affiliation(s)
- Jolyn Hersch
- School of Public Health, The University of Sydney, Sydney, New South Wales, Australia
- Wiser Healthcare, The University of Sydney, Sydney, New South Wales, Australia
- Centre for Medical Psychology and Evidence-based Decision-making (CeMPED), The University of Sydney, Sydney, New South Wales, Australia
| | - Kevin McGeechan
- School of Public Health, The University of Sydney, Sydney, New South Wales, Australia
- Wiser Healthcare, The University of Sydney, Sydney, New South Wales, Australia
- Centre for Medical Psychology and Evidence-based Decision-making (CeMPED), The University of Sydney, Sydney, New South Wales, Australia
| | - Alexandra Barratt
- School of Public Health, The University of Sydney, Sydney, New South Wales, Australia
- Wiser Healthcare, The University of Sydney, Sydney, New South Wales, Australia
- Centre for Medical Psychology and Evidence-based Decision-making (CeMPED), The University of Sydney, Sydney, New South Wales, Australia
| | - Jesse Jansen
- School of Public Health, The University of Sydney, Sydney, New South Wales, Australia
- Wiser Healthcare, The University of Sydney, Sydney, New South Wales, Australia
- Centre for Medical Psychology and Evidence-based Decision-making (CeMPED), The University of Sydney, Sydney, New South Wales, Australia
| | - Les Irwig
- School of Public Health, The University of Sydney, Sydney, New South Wales, Australia
- Wiser Healthcare, The University of Sydney, Sydney, New South Wales, Australia
| | - Gemma Jacklyn
- School of Public Health, The University of Sydney, Sydney, New South Wales, Australia
- Wiser Healthcare, The University of Sydney, Sydney, New South Wales, Australia
| | - Nehmat Houssami
- School of Public Health, The University of Sydney, Sydney, New South Wales, Australia
- Wiser Healthcare, The University of Sydney, Sydney, New South Wales, Australia
| | - Haryana Dhillon
- Centre for Medical Psychology and Evidence-based Decision-making (CeMPED), The University of Sydney, Sydney, New South Wales, Australia
- Central Clinical School, The University of Sydney, Sydney, New South Wales, Australia
| | - Kirsten McCaffery
- School of Public Health, The University of Sydney, Sydney, New South Wales, Australia
- Wiser Healthcare, The University of Sydney, Sydney, New South Wales, Australia
- Centre for Medical Psychology and Evidence-based Decision-making (CeMPED), The University of Sydney, Sydney, New South Wales, Australia
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Jacklyn G, Morrell S, McGeechan K, Houssami N, Irwig L, Pathmanathan N, Barratt A. Carcinoma in situ of the breast in New South Wales, Australia: Current status and trends over the last 40 year. Breast 2017; 37:170-178. [PMID: 28882419 DOI: 10.1016/j.breast.2017.08.005] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2017] [Accepted: 08/17/2017] [Indexed: 10/18/2022] Open
Abstract
BACKGROUND The incidence of non-invasive breast cancer has increased substantially over time. We aim to describe temporal trends in the incidence of carcinoma in situ of the breast in New South Wales (NSW), Australia. METHODS Descriptive study of trends in the incidence of ductal carcinoma in situ (DCIS) and lobular carcinoma in situ (LCIS) in women who received a diagnosis from 1972 to 2012, recorded in the NSW Cancer Registry. RESULTS Carcinoma in situ as a proportion of all breast cancer was 0.4% during the prescreening period 1972 to 1987 and is currently 14.1% (2006 to 2012). Among 10,810 women diagnosed with DCIS, incidence across all ages rose from 0.15 per 100,000 during 1972 to 1983 to 16.81 per 100,000 over 2006 to 2012, representing a 100-fold increase (IRR 113.10; 95% CI 81.94 to 156.08). Among women in the target age group for screening (50-69 years) incidence rose from 0.27 per 100,000 to 51.96 over the same period (IRR 195.50; 95% CI 117.26 to 325.89). DCIS incidence peaks in women aged 60-69 years. DCIS incidence has not stabilized despite screening being well established for over 20 years, and participation rates in the target age range remaining stable. CONCLUSIONS Our findings raise questions about the value of the increasing detection of DCIS and aggressive treatment of these lesions, especially among older women, and support trials of de-escalated treatment.
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Affiliation(s)
- Gemma Jacklyn
- Wiser Healthcare, Sydney School of Public Health, The University of Sydney, NSW, 2006, Australia.
| | - Stephen Morrell
- School of Public Health and Community Medicine, Faculty of Medicine, University of New South Wales, Sydney, NSW, 2052, Australia
| | - Kevin McGeechan
- Sydney School of Public Health, The University of Sydney, NSW, 2006, Australia
| | - Nehmat Houssami
- Sydney School of Public Health, The University of Sydney, NSW, 2006, Australia
| | - Les Irwig
- Sydney School of Public Health, The University of Sydney, NSW, 2006, Australia
| | - Nirmala Pathmanathan
- Sydney Medical School - Westmead, The University of Sydney, Westmead, NSW, 2145, Australia; Westmead Breast Cancer Institute, Westmead Hospital, Westmead, NSW, Australia
| | - Alexandra Barratt
- Wiser Healthcare, Sydney School of Public Health, The University of Sydney, NSW, 2006, Australia
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20
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Jacklyn G, McGeechan K, Irwig L, Houssami N, Morrell S, Bell K, Barratt A. Trends in stage-specific breast cancer incidence in New South Wales, Australia: insights into the effects of 25 years of screening mammography. Breast Cancer Res Treat 2017; 166:843-854. [PMID: 28822001 DOI: 10.1007/s10549-017-4443-x] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2017] [Accepted: 08/04/2017] [Indexed: 02/06/2023]
Abstract
PURPOSE Screening mammography aims to improve breast cancer (BC) prognosis by increasing the incidence of early-stage tumours in order to decrease the incidence of late-stage cancer, but no reports have investigated these potential effects in an Australian population. Therefore we aimed to identify temporal trends in stage-specific BC in New South Wales (NSW), Australia, between 1972 and 2012. METHODS An observational study of women who received a diagnosis of BC from 1972-2012 as recorded in the NSW Cancer Registry, a population-based registry with almost complete coverage and high rates of histological verification. We analysed trends in stage-specific incidence before screening and compared them to periods after screening began. Our primary group of interest was women in the target age range of 50-69 years, though trends in women outside the target age were also assessed. RESULTS Screening was not associated with lower incidence of late-stage BC at diagnosis. Incidence for all stages remained higher than prescreening levels. In women aged 50-69 years, the incidence of carcinoma in situ (CIS), localised and regional BC has more than doubled compared to the prescreening era, with incidence rate ratios ranging from 2.0 for regional (95% CI 1.95-2.13) to 121.8 for CIS (95% CI 82.58-179.72). Before the introduction of screening, there was a downward trend in distant metastatic BC incidence, and after the introduction of screening there was an increase (IRR 1.8; 95% CI 1.62-2.00). In women too young to screen the incidence of late-stage BC at diagnosis also increased, whereas localised disease was stable. CONCLUSIONS The incidence of all stages of BC has increased over the past 40 years, with the greatest rise seen during the established screening period for women aged 50-69 years. Our findings suggest that some of the expected benefits of screening may not have been realised and are consistent with overdiagnosis.
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Affiliation(s)
- Gemma Jacklyn
- Wiser Healthcare, Sydney School of Public Health, The University of Sydney, Sydney, NSW, 2006, Australia.
| | - Kevin McGeechan
- Sydney School of Public Health, The University of Sydney, Edward Ford Building (A27), Sydney, NSW, 2006, Australia.,Wiser Healthcare, Sydney School of Public Health, The University of Sydney, Sydney, NSW, 2006, Australia
| | - Les Irwig
- Sydney School of Public Health, The University of Sydney, Edward Ford Building (A27), Sydney, NSW, 2006, Australia
| | - Nehmat Houssami
- Sydney School of Public Health, The University of Sydney, Edward Ford Building (A27), Sydney, NSW, 2006, Australia
| | - Stephen Morrell
- School of Public Health and Community Medicine, Faculty of Medicine, University of New South Wales, Sydney, NSW, 2052, Australia
| | - Katy Bell
- Wiser Healthcare, Sydney School of Public Health, The University of Sydney, Sydney, NSW, 2006, Australia
| | - Alexandra Barratt
- Wiser Healthcare, Sydney School of Public Health, The University of Sydney, Sydney, NSW, 2006, Australia
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21
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Jacklyn G, Howard K, Irwig L, Houssami N, Hersch J, Barratt A. Impact of extending screening mammography to older women: Information to support informed choices. Int J Cancer 2017; 141:1540-1550. [PMID: 28662267 DOI: 10.1002/ijc.30858] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2017] [Revised: 04/24/2017] [Accepted: 06/22/2017] [Indexed: 01/19/2023]
Abstract
From 2013 through 2017, the Australian national breast cancer screening programme is gradually inviting women aged 70-74 years to attend screening, following a policy decision to extend invitations to older women. We estimate the benefits and harms of the new package of biennial screening from age 50-74 compared with the previous programme of screening from age 50-69. Using a Markov model, we applied estimates of the relative risk reduction for breast cancer mortality and the risk of overdiagnosis from the Independent UK Panel on Breast Cancer Screening review to Australian breast cancer incidence and mortality data. We estimated screening specific outcomes (recalls for further imaging, biopsies, false positives, and interval cancer rates) from data published by BreastScreen Australia. When compared with stopping at age 69, screening 1,000 women to age 74 is likely to avert one more breast cancer death, with an additional 78 women receiving a false positive result and another 28 women diagnosed with breast cancer, of whom eight will be overdiagnosed and overtreated. The extra 5 years of screening results in approximately 7 more overdiagnosed cancers to avert one more breast cancer death. Thus extending screening mammography in Australia to older women results in a less favourable harm to benefit ratio than stopping at age 69. Supporting informed decision making for this age group should be a public health priority.
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Affiliation(s)
- Gemma Jacklyn
- Wiser Healthcare, Sydney School of Public Health, The University of Sydney, NSW, 2006, Australia
| | - Kirsten Howard
- Sydney School of Public Health, The University of Sydney, NSW, 2006, Australia
| | - Les Irwig
- Wiser Healthcare, Sydney School of Public Health, The University of Sydney, NSW, 2006, Australia
| | - Nehmat Houssami
- Sydney School of Public Health, The University of Sydney, NSW, 2006, Australia
| | - Jolyn Hersch
- Wiser Healthcare, Sydney School of Public Health, The University of Sydney, NSW, 2006, Australia.,Centre for Medical Psychology and Evidence-based Decision-making (CeMPED), Sydney School of Public Health, The University of Sydney, NSW, 2006, Australia
| | - Alexandra Barratt
- Wiser Healthcare, Sydney School of Public Health, The University of Sydney, NSW, 2006, Australia.,Centre for Medical Psychology and Evidence-based Decision-making (CeMPED), Sydney School of Public Health, The University of Sydney, NSW, 2006, Australia
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22
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Walter SD, Turner RM, Macaskill P, McCaffery KJ, Irwig L. Estimation of treatment preference effects in clinical trials when some participants are indifferent to treatment choice. BMC Med Res Methodol 2017; 17:29. [PMID: 28219326 PMCID: PMC5319089 DOI: 10.1186/s12874-017-0304-x] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2016] [Accepted: 02/02/2017] [Indexed: 11/19/2022] Open
Abstract
Background In the two-stage randomised trial design, a randomly sampled subset of study participants are permitted to choose their own treatment, while the remaining participants are randomised to treatment in the usual way. Appropriate analysis of the data from both arms of the study allows investigators to estimate the impact on study outcomes of treatment preferences that patients may have, in addition to evaluating the usual direct effect of treatment. In earlier work, we showed how to optimise this design by making a suitable choice of the proportion of participants who should be assigned to the choice arm of the trial. However, we ignored the possibility of some participants being indifferent to the treatments under study. In this paper, we extend our earlier work to consider the analysis of two-stage randomised trials when some participants have no treatment preference, even if they are assigned to the choice arm and allowed to choose. Methods We compare alternative characterisations of the response profiles of the indifferent or undecided participants, and derive estimates of the treatment and preference effects on study outcomes. We also present corresponding test statistics for these parameters. The methods are illustrated with data from a clinical trial contrasting medical and surgical interventions. Results Expressions are obtained to estimate and test the impact of treatment choices on study outcomes, as well as the impact of the actual treatment received. Contrasts are defined between patients with stated treatment preferences and those with no preference. Alternative assumptions concerning the outcomes of undecided participants are described, and an approach leading to unbiased estimation and testing is identified. Conclusions Use of the two-stage design can provide important insights into determinants of study outcomes that are not identifiable with other designs. The design can remain attractive even in the presence of participants with no stated treatment preference. Electronic supplementary material The online version of this article (doi:10.1186/s12874-017-0304-x) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Stephen D Walter
- Department of Clinical Epidemiology and Biostatistics, McMaster University, CRL 233, Hamilton, ON, Canada, L8N 3Z5.
| | - Robin M Turner
- School of Public Health and Community Medicine, University of New South Wales, Sydney,, NSW 2052, Australia
| | - Petra Macaskill
- Screening and Test Evaluation Program, Sydney School of Public Health, Sydney Medical School, University of Sydney, Sydney, NSW 2006, Australia
| | - Kirsten J McCaffery
- Screening and Test Evaluation Program, Sydney School of Public Health, Sydney Medical School, University of Sydney, Sydney, NSW 2006, Australia
| | - Les Irwig
- Screening and Test Evaluation Program, Sydney School of Public Health, Sydney Medical School, University of Sydney, Sydney, NSW 2006, Australia
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23
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Bell KJ, Mehta Y, Turner RM, Morton RL, Dieng M, Saw R, Guitera P, McCaffery K, Low D, Low C, Jenkins M, Irwig L, Webster AC. Fear of new or recurrent melanoma after treatment for localised melanoma. Psychooncology 2017; 26:1784-1791. [DOI: 10.1002/pon.4366] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2016] [Revised: 12/01/2016] [Accepted: 12/30/2016] [Indexed: 11/10/2022]
Affiliation(s)
- Katy J.L. Bell
- The School of Public Health; The University of Sydney; Sydney New South Wales Australia
- Center for Evidence Based Practice; Bond University; Gold Coast Queensland Australia
| | - Yachna Mehta
- Australia New Zealand Melanoma Trials Group; Melanoma Institute Australia; Sydney New South Wales Australia
| | - Robin M. Turner
- School of Public Health and Community Medicine; University of New South Wales; Sydney New South Wales Australia
| | - Rachael L. Morton
- NHMRC Clinical Trials Centre; The University of Sydney; Sydney New South Wales Australia
| | - Mbathio Dieng
- The School of Public Health; The University of Sydney; Sydney New South Wales Australia
- Macquarie University; Sydney New South Wales Australia
| | - Robyn Saw
- Melanoma Institute Australia; Sydney New South Wales Australia
- Discipline of Surgery; The University of Sydney; Sydney New South Wales Australia
- Division of Surgery; Royal Prince Alfred Hospital; Camperdown New South Wales Australia
| | - Pascale Guitera
- Melanoma Institute Australia; Sydney New South Wales Australia
- Discipline of Dermatology; The University of Sydney; Sydney New South Wales Australia
- The Sydney Melanoma Diagnostic Centre; Royal Prince Alfred Hospital; Camperdown New South Wales Australia
| | - Kirsten McCaffery
- The School of Public Health; The University of Sydney; Sydney New South Wales Australia
| | - Donald Low
- Cancer Voices NSW; Sydney New South Wales Australia
| | - Cynthia Low
- Cancer Voices NSW; Sydney New South Wales Australia
| | - Marisa Jenkins
- The School of Public Health; The University of Sydney; Sydney New South Wales Australia
| | - Les Irwig
- The School of Public Health; The University of Sydney; Sydney New South Wales Australia
| | - Angela C. Webster
- The School of Public Health; The University of Sydney; Sydney New South Wales Australia
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Bell KJL, Hayen A, Glasziou P, Irwig L, Bauer DC. Change in Bone Mineral Density Is an Indicator of Treatment-Related Antifracture Effect. Ann Intern Med 2017; 166:152. [PMID: 28114470 DOI: 10.7326/l16-0528] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Affiliation(s)
- Katy J L Bell
- From The University of Sydney, Sydney, New South Wales, Australia; University of Technology Sydney, Sydney, New South Wales, Australia; Bond University, Bond, Queensland, Australia; and University of California, San Francisco, School of Medicine, San Francisco, California
| | - Andrew Hayen
- From The University of Sydney, Sydney, New South Wales, Australia; University of Technology Sydney, Sydney, New South Wales, Australia; Bond University, Bond, Queensland, Australia; and University of California, San Francisco, School of Medicine, San Francisco, California
| | - Paul Glasziou
- From The University of Sydney, Sydney, New South Wales, Australia; University of Technology Sydney, Sydney, New South Wales, Australia; Bond University, Bond, Queensland, Australia; and University of California, San Francisco, School of Medicine, San Francisco, California
| | - Les Irwig
- From The University of Sydney, Sydney, New South Wales, Australia; University of Technology Sydney, Sydney, New South Wales, Australia; Bond University, Bond, Queensland, Australia; and University of California, San Francisco, School of Medicine, San Francisco, California
| | - Douglas C Bauer
- From The University of Sydney, Sydney, New South Wales, Australia; University of Technology Sydney, Sydney, New South Wales, Australia; Bond University, Bond, Queensland, Australia; and University of California, San Francisco, School of Medicine, San Francisco, California
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25
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Jansen J, McKinn S, Bonner C, Irwig L, Doust J, Glasziou P, Bell K, Naganathan V, McCaffery K. General Practitioners' Decision Making about Primary Prevention of Cardiovascular Disease in Older Adults: A Qualitative Study. PLoS One 2017; 12:e0170228. [PMID: 28085944 PMCID: PMC5234831 DOI: 10.1371/journal.pone.0170228] [Citation(s) in RCA: 36] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2016] [Accepted: 12/30/2016] [Indexed: 12/31/2022] Open
Abstract
BACKGROUND Primary cardiovascular disease (CVD) prevention in older people is challenging as they are a diverse group with varying needs, frequent presence of comorbidities, and are more susceptible to treatment harms. Moreover the potential benefits and harms of preventive medication for older people are uncertain. We explored GPs' decision making about primary CVD prevention in patients aged 75 years and older. METHOD 25 GPs participated in semi-structured interviews in New South Wales, Australia. Transcribed audio-recordings were thematically coded and Framework Analysis was used. RESULTS Analysis identified factors that are likely to contribute to variation in the management of CVD risk in older people. Some GPs based CVD prevention on guidelines regardless of patient age. Others tailored management based on factors such as perceptions of prevention in older age, knowledge of limited evidence, comorbidities, polypharmacy, frailty, and life expectancy. GPs were more confident about: 1) medication and lifestyle change for fit/healthy older patients, and 2) stopping or avoiding medication for frail/nursing home patients. Decision making for older patients outside of these categories was less clear. CONCLUSION Older patients receive different care depending on their GP's perceptions of ageing and CVD prevention, and their knowledge of available evidence. GPs consider CVD prevention for older patients challenging and would welcome more guidance in this area.
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Affiliation(s)
- Jesse Jansen
- Screening and Test Evaluation Program (STEP), Sydney School of Public Health, The University of Sydney, Sydney, New South Wales, Australia
- Centre for Medical Psychology and Evidence-based Decision-making (CeMPED), The University of Sydney, Sydney, New South Wales, Australia
- * E-mail:
| | - Shannon McKinn
- Screening and Test Evaluation Program (STEP), Sydney School of Public Health, The University of Sydney, Sydney, New South Wales, Australia
- Centre for Medical Psychology and Evidence-based Decision-making (CeMPED), The University of Sydney, Sydney, New South Wales, Australia
| | - Carissa Bonner
- Screening and Test Evaluation Program (STEP), Sydney School of Public Health, The University of Sydney, Sydney, New South Wales, Australia
- Centre for Medical Psychology and Evidence-based Decision-making (CeMPED), The University of Sydney, Sydney, New South Wales, Australia
| | - Les Irwig
- Screening and Test Evaluation Program (STEP), Sydney School of Public Health, The University of Sydney, Sydney, New South Wales, Australia
| | - Jenny Doust
- Screening and Test Evaluation Program (STEP), Sydney School of Public Health, The University of Sydney, Sydney, New South Wales, Australia
- Faculty of Health Sciences and Medicine, Bond University, Robina, Queensland, Australia
| | - Paul Glasziou
- Screening and Test Evaluation Program (STEP), Sydney School of Public Health, The University of Sydney, Sydney, New South Wales, Australia
- Faculty of Health Sciences and Medicine, Bond University, Robina, Queensland, Australia
| | - Katy Bell
- Screening and Test Evaluation Program (STEP), Sydney School of Public Health, The University of Sydney, Sydney, New South Wales, Australia
| | - Vasi Naganathan
- Centre for Education and Research on Ageing (CERA), Ageing and Alzheimer’s Institute, Concord Hospital, The University of Sydney, Sydney, New South Wales, Australia
| | - Kirsten McCaffery
- Screening and Test Evaluation Program (STEP), Sydney School of Public Health, The University of Sydney, Sydney, New South Wales, Australia
- Centre for Medical Psychology and Evidence-based Decision-making (CeMPED), The University of Sydney, Sydney, New South Wales, Australia
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Cohen JF, Korevaar DA, Altman DG, Bruns DE, Gatsonis CA, Hooft L, Irwig L, Levine D, Reitsma JB, de Vet HCW, Bossuyt PMM. STARD 2015 guidelines for reporting diagnostic accuracy studies: explanation and elaboration. BMJ Open 2016; 6:e012799. [PMID: 28137831 PMCID: PMC5128957 DOI: 10.1136/bmjopen-2016-012799] [Citation(s) in RCA: 1190] [Impact Index Per Article: 148.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/26/2016] [Revised: 08/03/2016] [Accepted: 08/25/2016] [Indexed: 12/11/2022] Open
Abstract
Diagnostic accuracy studies are, like other clinical studies, at risk of bias due to shortcomings in design and conduct, and the results of a diagnostic accuracy study may not apply to other patient groups and settings. Readers of study reports need to be informed about study design and conduct, in sufficient detail to judge the trustworthiness and applicability of the study findings. The STARD statement (Standards for Reporting of Diagnostic Accuracy Studies) was developed to improve the completeness and transparency of reports of diagnostic accuracy studies. STARD contains a list of essential items that can be used as a checklist, by authors, reviewers and other readers, to ensure that a report of a diagnostic accuracy study contains the necessary information. STARD was recently updated. All updated STARD materials, including the checklist, are available at http://www.equator-network.org/reporting-guidelines/stard Here, we present the STARD 2015 explanation and elaboration document. Through commented examples of appropriate reporting, we clarify the rationale for each of the 30 items on the STARD 2015 checklist, and describe what is expected from authors in developing sufficiently informative study reports.
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Affiliation(s)
- Jérémie F Cohen
- Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Centre, University of Amsterdam, Amsterdam, The Netherlands
- Department of Pediatrics, INSERM UMR 1153, Necker Hospital, AP-HP, Paris Descartes University, Paris, France
| | - Daniël A Korevaar
- Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Centre, University of Amsterdam, Amsterdam, The Netherlands
| | - Douglas G Altman
- Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, Centre for Statistics in Medicine, University of Oxford, Oxford, UK
| | - David E Bruns
- Department of Pathology, University of Virginia School of Medicine, Charlottesville, Virginia, USA
| | - Constantine A Gatsonis
- Department of Biostatistics, Brown University School of Public Health, Providence, Rhode Island, USA
| | - Lotty Hooft
- Cochrane Netherlands, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, University of Utrecht, Utrecht, The Netherlands
| | - Les Irwig
- Screening and Diagnostic Test Evaluation Program, School of Public Health, University of Sydney, Sydney, New South Wales, Australia
| | - Deborah Levine
- Department of Radiology, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA
- Radiology Editorial Office, Boston, Massachusetts, USA
| | - Johannes B Reitsma
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, University of Utrecht, Utrecht, The Netherlands
| | - Henrica C W de Vet
- Department of Epidemiology and Biostatistics, EMGO Institute for Health and Care Research, VU University Medical Center, Amsterdam, The Netherlands
| | - Patrick M M Bossuyt
- Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Centre, University of Amsterdam, Amsterdam, The Netherlands
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Marinovich ML, Azizi L, Macaskill P, Irwig L, Morrow M, Solin LJ, Houssami N. The Association of Surgical Margins and Local Recurrence in Women with Ductal Carcinoma In Situ Treated with Breast-Conserving Therapy: A Meta-Analysis. Ann Surg Oncol 2016; 23:3811-3821. [PMID: 27527715 PMCID: PMC5160992 DOI: 10.1245/s10434-016-5446-2] [Citation(s) in RCA: 107] [Impact Index Per Article: 13.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2016] [Indexed: 01/01/2023]
Abstract
PURPOSE There is no consensus on adequate negative margins in breast-conserving surgery (BCS) for ductal carcinoma in situ (DCIS). We systematically reviewed the evidence on margins in BCS for DCIS. METHODS A study-level meta-analysis of local recurrence (LR), microscopic margin status and threshold distance for negative margins. LR proportion was modeled using random-effects logistic meta-regression (frequentist) and network meta-analysis (Bayesian) that allows for multiple margin distances per study, adjusting for follow-up time. RESULTS Based on 20 studies (LR: 865 of 7883), odds of LR were associated with margin status [logistic: odds ratio (OR) 0.53 for negative vs. positive/close (p < 0.001); network: OR 0.45 for negative vs. positive]. In logistic meta-regression, relative to >0 or 1 mm, ORs for 2 mm (0.51), 3 or 5 mm (0.42) and 10 mm (0.60) showed comparable significant reductions in the odds of LR. In the network analysis, ORs relative to positive margins for 2 (0.32), 3 (0.30) and 10 mm (0.32) showed similar reductions in the odds of LR that were greater than for >0 or 1 mm (0.45). There was weak evidence of lower odds at 2 mm compared with >0 or 1 mm [relative OR (ROR) 0.72, 95 % credible interval (CrI) 0.47-1.08], and no evidence of a difference between 2 and 10 mm (ROR 0.99, 95 % CrI 0.61-1.64). Adjustment for covariates, and analyses based only on studies using whole-breast radiotherapy, did not change the findings. CONCLUSION Negative margins in BCS for DCIS reduce the odds of LR; however, minimum margin distances above 2 mm are not significantly associated with further reduced odds of LR in women receiving radiation.
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Affiliation(s)
- M Luke Marinovich
- Screening and Test Evaluation Program (STEP), Sydney School of Public Health, Sydney Medical School, The University of Sydney, Sydney, NSW, Australia.
| | - Lamiae Azizi
- Screening and Test Evaluation Program (STEP), Sydney School of Public Health, Sydney Medical School, The University of Sydney, Sydney, NSW, Australia
| | - Petra Macaskill
- Screening and Test Evaluation Program (STEP), Sydney School of Public Health, Sydney Medical School, The University of Sydney, Sydney, NSW, Australia
| | - Les Irwig
- Screening and Test Evaluation Program (STEP), Sydney School of Public Health, Sydney Medical School, The University of Sydney, Sydney, NSW, Australia
| | - Monica Morrow
- Department of Surgery, Memorial Sloan-Kettering Cancer Center, New York, NY, USA
| | - Lawrence J Solin
- Department of Radiation Oncology, Albert Einstein Healthcare Network, Philadelphia, PA, USA
| | - Nehmat Houssami
- Screening and Test Evaluation Program (STEP), Sydney School of Public Health, Sydney Medical School, The University of Sydney, Sydney, NSW, Australia
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Bell KJ, Hayen A, Glasziou P, Irwig L, Eastell R, Harrison SL, Black DM, Bauer DC. Potential Usefulness of BMD and Bone Turnover Monitoring of Zoledronic Acid Therapy Among Women With Osteoporosis: Secondary Analysis of Randomized Controlled Trial Data. J Bone Miner Res 2016; 31:1767-73. [PMID: 27027655 DOI: 10.1002/jbmr.2847] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/11/2016] [Revised: 03/17/2016] [Accepted: 03/26/2016] [Indexed: 11/10/2022]
Abstract
We aimed to compare the clinical validity and the detectability of response of short-term changes in bone mineral density (BMD; hip and spine) and bone turnover markers (serum PINP and CTX) through secondary analysis of trial data. We analyzed data on 7765 women with osteoporosis randomized to 5-mg once-yearly infusions of zoledronic acid or placebo in the Health Outcomes and Reduced Incidence with Zoledronic Acid Once Yearly Pivotal Fracture Trial (HORIZON-PFT; trial ran from 2002 to 2006) and the first extension trial (trial ran from 2006 to 2009). We assessed the clinical validity and detectability of response for 1-year measurements of the following monitoring tests: total hip and lumbar spine BMD, serum N-terminal propeptide of type I collagen (sPINP), and serum C-telopeptide of type I collagen (sCTX; 6-month measurement used). Clinical validity was assessed by examining prediction of clinical fracture in Cox models; detectability of response to treatment was assessed by the ratio of signal to noise, estimated from the distributions of change in zoledronic acid and placebo groups. Baseline measurements were available for 7683 women with hip BMD, 558 with spine BMD, 1246 with sPINP, and 517 women with sCTX. Hip BMD and sPINP ranked highly for prediction of clinical fracture, whereas sPINP and sCTX ranked highly for detectability of response to treatment. Serum PINP had the highest overall ranking. In conclusion, serum PINP is potentially useful in monitoring response to zoledronic acid. Further research is needed to evaluate the effects of monitoring PINP on treatment decisions and other clinically relevant outcomes. © 2016 American Society for Bone and Mineral Research.
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Affiliation(s)
- Katy Jl Bell
- The Screening and Diagnostic Test Evaluation Program (STEP), Sydney School of Public Health, The University of Sydney, Sydney, Australia.,Faculty of Health Sciences and Medicine, Bond University, Robina, Australia
| | - Andrew Hayen
- School of Public Health and Community Medicine, University of New South Wales, Sydney, Australia
| | - Paul Glasziou
- Faculty of Health Sciences and Medicine, Bond University, Robina, Australia
| | - Les Irwig
- The Screening and Diagnostic Test Evaluation Program (STEP), Sydney School of Public Health, The University of Sydney, Sydney, Australia
| | - Richard Eastell
- Department of Oncology and Metabolism, The University of Sheffield, Sheffield, UK
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29
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McKinn S, Bonner C, Jansen J, Teixeira-Pinto A, So M, Irwig L, Doust J, Glasziou P, McCaffery K. Factors influencing general practitioners' decisions about cardiovascular disease risk reassessment: findings from experimental and interview studies. BMC Fam Pract 2016; 17:107. [PMID: 27495325 PMCID: PMC4974805 DOI: 10.1186/s12875-016-0499-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 12/06/2015] [Accepted: 07/21/2016] [Indexed: 11/25/2022]
Abstract
Background Guidelines on cardiovascular disease (CVD) risk reassessment intervals are unclear, potentially leading to detrimental practice variation: too frequent can result in overtreatment and greater strain on the healthcare system; too infrequent could result in the neglect of high risk patients who require medication. This study aimed to understand the different factors that general practitioners (GPs) consider when deciding on the reassessment interval for patients previously assessed for primary CVD risk. Methods This paper combines quantitative and qualitative data regarding reassessment intervals from two separate studies of CVD risk management. Experimental study: 144 Australian GPs viewed a random selection of hypothetical cases via a paper-based questionnaire, in which blood pressure, cholesterol and 5-year absolute risk (AR) were systematically varied to appear lower or higher. GPs were asked how they would manage each case, including an open-ended response for when they would reassess the patient. Interview study: Semi-structured interviews were conducted with a purposive sample of 25 Australian GPs, recruited separately from the GPs in the experimental study. Transcribed audio-recordings were thematically coded, using the Framework Analysis method. Results Experiment: GPs stated that they would reassess the majority of patients across all absolute risk categories in 6 months or less (low AR = 52 % [CI95% = 47–57 %], moderate AR = 82 % [CI95% = 76–86 %], high AR = 87 % [CI95% = 82–90 %], total = 71 % [CI95% = 67–75 %]), with 48 % (CI95% = 43–53 %) of patients reassessed in under 3 months. The majority (75 % [CI95% = 70–79 %]) of patients with low-moderate AR (≤15 %) and an elevated risk factor would be reassessed in under 6 months. Interviews: GPs identified different functions for reassessment and risk factor monitoring, which affected recommended intervals. These included perceived psychosocial benefits to patients, preparing the patient for medication, and identifying barriers to lifestyle change and medication adherence. Reassessment and monitoring intervals were driven by patient motivation to change lifestyle, patient demand, individual risk factors, and GP attitudes. Conclusions There is substantial variation in reassessment intervals for patients with the same risk profile. This suggests that GPs are not following reassessment recommendations in the Australian guidelines. The use of shorter intervals for low-moderate AR contradicts research on optimal monitoring intervals, and may result in unnecessary costs and over-treatment. Electronic supplementary material The online version of this article (doi:10.1186/s12875-016-0499-7) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Shannon McKinn
- Screening and Test Evaluation Program (STEP), Sydney School of Public Health, The University of Sydney, Sydney, NSW, Australia.,Centre for Medical Psychology & Evidence-based Decision-making (CeMPED), The University of Sydney, Sydney, NSW, Australia
| | - Carissa Bonner
- Screening and Test Evaluation Program (STEP), Sydney School of Public Health, The University of Sydney, Sydney, NSW, Australia.,Centre for Medical Psychology & Evidence-based Decision-making (CeMPED), The University of Sydney, Sydney, NSW, Australia
| | - Jesse Jansen
- Screening and Test Evaluation Program (STEP), Sydney School of Public Health, The University of Sydney, Sydney, NSW, Australia.,Centre for Medical Psychology & Evidence-based Decision-making (CeMPED), The University of Sydney, Sydney, NSW, Australia
| | - Armando Teixeira-Pinto
- Screening and Test Evaluation Program (STEP), Sydney School of Public Health, The University of Sydney, Sydney, NSW, Australia
| | - Matthew So
- Screening and Test Evaluation Program (STEP), Sydney School of Public Health, The University of Sydney, Sydney, NSW, Australia.,Centre for Medical Psychology & Evidence-based Decision-making (CeMPED), The University of Sydney, Sydney, NSW, Australia
| | - Les Irwig
- Screening and Test Evaluation Program (STEP), Sydney School of Public Health, The University of Sydney, Sydney, NSW, Australia
| | - Jenny Doust
- Screening and Test Evaluation Program (STEP), Sydney School of Public Health, The University of Sydney, Sydney, NSW, Australia.,Faculty of Health Sciences and Medicine, Bond University, Robina, QLD, Australia
| | - Paul Glasziou
- Screening and Test Evaluation Program (STEP), Sydney School of Public Health, The University of Sydney, Sydney, NSW, Australia.,Faculty of Health Sciences and Medicine, Bond University, Robina, QLD, Australia
| | - Kirsten McCaffery
- Screening and Test Evaluation Program (STEP), Sydney School of Public Health, The University of Sydney, Sydney, NSW, Australia. .,Centre for Medical Psychology & Evidence-based Decision-making (CeMPED), The University of Sydney, Sydney, NSW, Australia.
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30
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Perera R, McFadden E, McLellan J, Lung T, Clarke P, Pérez T, Fanshawe T, Dalton A, Farmer A, Glasziou P, Takahashi O, Stevens J, Irwig L, Hirst J, Stevens S, Leslie A, Ohde S, Deshpande G, Urayama K, Shine B, Stevens R. Optimal strategies for monitoring lipid levels in patients at risk or with cardiovascular disease: a systematic review with statistical and cost-effectiveness modelling. Health Technol Assess 2016; 19:1-401, vii-viii. [PMID: 26680162 DOI: 10.3310/hta191000] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023] Open
Abstract
BACKGROUND Various lipid measurements in monitoring/screening programmes can be used, alone or in cardiovascular risk scores, to guide treatment for prevention of cardiovascular disease (CVD). Because some changes in lipids are due to variability rather than true change, the value of lipid-monitoring strategies needs evaluation. OBJECTIVE To determine clinical value and cost-effectiveness of different monitoring intervals and different lipid measures for primary and secondary prevention of CVD. DATA SOURCES We searched databases and clinical trials registers from 2007 (including the Cochrane Central Register of Controlled Trials, MEDLINE, EMBASE, the Clinical Trials Register, the Current Controlled Trials register, and the Cumulative Index to Nursing and Allied Health Literature) to update and extend previous systematic reviews. Patient-level data from the Clinical Practice Research Datalink and St Luke's Hospital, Japan, were used in statistical modelling. Utilities and health-care costs were drawn from the literature. METHODS In two meta-analyses, we used prospective studies to examine associations of lipids with CVD and mortality, and randomised controlled trials to estimate lipid-lowering effects of atorvastatin doses. Patient-level data were used to estimate progression and variability of lipid measurements over time, and hence to model lipid-monitoring strategies. Results are expressed as rates of true-/false-positive and true-/false-negative tests for high lipid or high CVD risk. We estimated incremental costs per quality-adjusted life-year. RESULTS A total of 115 publications reported strength of association between different lipid measures and CVD events in 138 data sets. The summary adjusted hazard ratio per standard deviation of total cholesterol (TC) to high-density lipoprotein (HDL) cholesterol ratio was 1.25 (95% confidence interval 1.15 to 1.35) for CVD in a primary prevention population but heterogeneity was high (I(2) = 98%); similar results were observed for non-HDL cholesterol, apolipoprotein B and other ratio measures. Associations were smaller for other single lipid measures. Across 10 trials, low-dose atorvastatin (10 and 20 mg) effects ranged from a TC reduction of 0.92 mmol/l to 2.07 mmol/l, and low-density lipoprotein reduction of between 0.88 mmol/l and 1.86 mmol/l. Effects of 40 mg and 80 mg were reported by one trial each. For primary prevention, over a 3-year period, we estimate annual monitoring would unnecessarily treat 9 per 1000 more men (28 vs. 19 per 1000) and 5 per 1000 more women (17 vs. 12 per 1000) than monitoring every 3 years. However, annual monitoring would also undertreat 9 per 1000 fewer men (7 vs. 16 per 1000) and 4 per 1000 fewer women (7 vs. 11 per 1000) than monitoring at 3-year intervals. For secondary prevention, over a 3-year period, annual monitoring would increase unnecessary treatment changes by 66 per 1000 men and 31 per 1000 women, and decrease undertreatment by 29 per 1000 men and 28 per 1000 men, compared with monitoring every 3 years. In cost-effectiveness, strategies with increased screening/monitoring dominate. Exploratory analyses found that any unknown harms of statins would need utility decrements as large as 0.08 (men) to 0.11 (women) per statin user to reverse this finding in primary prevention. LIMITATION Heterogeneity in meta-analyses. CONCLUSIONS While acknowledging known and potential unknown harms of statins, we find that more frequent monitoring strategies are cost-effective compared with others. Regular lipid monitoring in those with and without CVD is likely to be beneficial to patients and to the health service. Future research should include trials of the benefits and harms of atorvastatin 40 and 80 mg, large-scale surveillance of statin safety, and investigation of the effect of monitoring on medication adherence. STUDY REGISTRATION This study is registered as PROSPERO CRD42013003727. FUNDING The National Institute for Health Research Health Technology Assessment programme.
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Affiliation(s)
- Rafael Perera
- National Institute for Health Research School for Primary Care Research, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Emily McFadden
- National Institute for Health Research School for Primary Care Research, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Julie McLellan
- National Institute for Health Research School for Primary Care Research, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Tom Lung
- Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Australia
| | - Philip Clarke
- Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Australia
| | - Teresa Pérez
- National Institute for Health Research School for Primary Care Research, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Thomas Fanshawe
- National Institute for Health Research School for Primary Care Research, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Andrew Dalton
- National Institute for Health Research School for Primary Care Research, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Andrew Farmer
- National Institute for Health Research School for Primary Care Research, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | | | - Osamu Takahashi
- St Luke's International University Center for Clinical Epidemiology, Tokyo, Japan
| | | | - Les Irwig
- Sydney School of Public Health, University of Sydney, Sydney, Australia
| | - Jennifer Hirst
- National Institute for Health Research School for Primary Care Research, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Sarah Stevens
- National Institute for Health Research School for Primary Care Research, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Asuka Leslie
- St Luke's International University Center for Clinical Epidemiology, Tokyo, Japan
| | - Sachiko Ohde
- St Luke's International University Center for Clinical Epidemiology, Tokyo, Japan
| | - Gautam Deshpande
- St Luke's International University Center for Clinical Epidemiology, Tokyo, Japan
| | - Kevin Urayama
- St Luke's International University Center for Clinical Epidemiology, Tokyo, Japan
| | - Brian Shine
- Oxford University Hospitals Trust, Oxford, UK
| | - Richard Stevens
- National Institute for Health Research School for Primary Care Research, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
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31
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Walter SD, Turner R, Macaskill P, McCaffery KJ, Irwig L. Beyond the treatment effect: Evaluating the effects of patient preferences in randomised trials. Stat Methods Med Res 2016; 26:489-507. [DOI: 10.1177/0962280214550516] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
The treatments under comparison in a randomised trial should ideally have equal value and acceptability – a position of equipoise – to study participants. However, it is unlikely that true equipoise exists in practice, because at least some participants may have preferences for one treatment or the other, for a variety of reasons. These preferences may be related to study outcomes, and hence affect the estimation of the treatment effect. Furthermore, the effects of preferences can sometimes be substantial, and may even be larger than the direct effect of treatment. Preference effects are of interest in their own right, but they cannot be assessed in the standard parallel group design for a randomised trial. In this paper, we describe a model to represent the impact of preferences on trial outcomes, in addition to the usual treatment effect. In particular, we describe how outcomes might differ between participants who would choose one treatment or the other, if they were free to do so. Additionally, we investigate the difference in outcomes depending on whether or not a participant receives his or her preferred treatment, which we characterise through a so-called preference effect. We then discuss several study designs that have been proposed to measure and exploit data on preferences, and which constitute alternatives to the conventional parallel group design. Based on the model framework, we determine which of the various preference effects can or cannot be estimated with each design. We also illustrate these ideas with some examples of preference designs from the literature.
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Affiliation(s)
- SD Walter
- Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, Ontario, Canada
| | - R Turner
- Screening and Test Evaluation Program, Sydney School of Public Health, University of Sydney, Sydney, New South Wales, Australia
| | - P Macaskill
- Screening and Test Evaluation Program, Sydney School of Public Health, University of Sydney, Sydney, New South Wales, Australia
| | - KJ McCaffery
- Screening and Test Evaluation Program, Sydney School of Public Health, University of Sydney, Sydney, New South Wales, Australia
| | - L Irwig
- Screening and Test Evaluation Program, Sydney School of Public Health, University of Sydney, Sydney, New South Wales, Australia
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Abstract
Background: In many countries high participation is an explicit target in screening programmes. The desire for high participation often appears to drive screening policy, although it is increasingly recognized that encouraging high participation may impinge upon the rights of an individual to make an informed choice. One argument offered in support of high participation is that it improves the cost-effectiveness of screening. This is questionable on theoretical grounds, and empirically there are conflicting results. Two recent cost-effectiveness models of faecal occult blood test (FOBT) screening for colorectal cancer (CRC) showed that cost-effectiveness was improved, another showed that cost-effectiveness was worsened and a fourth indicated that cost-effectiveness was unaffected by increasing the participation rate. Methods: We assessed the extent to which different levels and patterns of participation affect cost-effectiveness, using decision modelling of three CRC screening with FOBT scenarios. We estimate the incremental cost-effectiveness (value for money) ratios for each scenario. Results: The way in which participation is modelled, particularly assumptions made about the subsequent screening behaviour of non-participants ('if' and 'when' a non-participant attends for subsequent screening), affects the cost-effectiveness estimates for FOBT screening programmes. 100% participation in all screening rounds gives a cost per life year saved (LYS) of US$9705. Cost-effectiveness is worst when people who do not take part in one screening round (initial or subsequent) never take part in any future rounds of screening. Under this scenario, a participation rate of 20% in second and subsequent rounds gives a cost per LYS of US$29,500. Under more realistic assumptions, for example the attendance of even a small proportion of non-participants in subsequent rounds, cost-effectiveness is more favourable and similar to that achieved for full participation: the scenario with a random participation rate of 20% in second and subsequent rounds for both participants and non-participants has a cost per LYS of US$11,270. Conclusions: Contrary to a commonly held view, high participation in screening programmes is not necessary to achieve cost-effectiveness. Setting high target participation rates in screening programmes does not guarantee cost-effectiveness and may in certain circumstances reduce the cost-effectiveness.
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Affiliation(s)
- Kirsten Howard
- Health Economics, Screening and Test Evaluation Program (STEP), School of Public Health, Edward Ford Building A27, University of Sydney, Australia.
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33
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Korevaar DA, Cohen JF, Reitsma JB, Bruns DE, Gatsonis CA, Glasziou PP, Irwig L, Moher D, de Vet HCW, Altman DG, Hooft L, Bossuyt PMM. Updating standards for reporting diagnostic accuracy: the development of STARD 2015. Res Integr Peer Rev 2016; 1:7. [PMID: 29451535 PMCID: PMC5803584 DOI: 10.1186/s41073-016-0014-7] [Citation(s) in RCA: 43] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2016] [Accepted: 04/12/2016] [Indexed: 01/17/2023] Open
Abstract
Background Although the number of reporting guidelines has grown rapidly, few have gone through an updating process. The STARD statement (Standards for Reporting Diagnostic Accuracy), published in 2003 to help improve the transparency and completeness of reporting of diagnostic accuracy studies, was recently updated in a systematic way. Here, we describe the steps taken and a justification for the changes made. Results A 4-member Project Team coordinated the updating process; a 14-member Steering Committee was regularly solicited by the Project Team when making critical decisions. First, a review of the literature was performed to identify topics and items potentially relevant to the STARD updating process. After this, the 85 members of the STARD Group were invited to participate in two online surveys to identify items that needed to be modified, removed from, or added to the STARD checklist. Based on the results of the literature review process, 33 items were presented to the STARD Group in the online survey: 25 original items and 8 new items; 73 STARD Group members (86 %) completed the first survey, and 79 STARD Group members (93 %) completed the second survey.Then, an in-person consensus meeting was organized among the members of the Project Team and Steering Committee to develop a consensual draft version of STARD 2015. This version was piloted in three rounds among a total of 32 expert and non-expert users. Piloting mostly led to rewording of items. After this, the update was finalized. The updated STARD 2015 list now consists of 30 items. Compared to the previous version of STARD, three original items were each converted into two new items, four original items were incorporated into other items, and seven new items were added. Conclusions After a systematic updating process, STARD 2015 provides an updated list of 30 essential items for reporting diagnostic accuracy studies.
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Affiliation(s)
- Daniël A Korevaar
- 1Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Centre, University of Amsterdam, Amsterdam, The Netherlands
| | - Jérémie F Cohen
- 1Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Centre, University of Amsterdam, Amsterdam, The Netherlands.,2INSERM UMR 1153 and Department of Pediatrics, Necker Hospital, AP-HP, Paris Descartes University, Paris, France
| | - Johannes B Reitsma
- 3Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, University of Utrecht, Utrecht, The Netherlands
| | - David E Bruns
- 4Department of Pathology, University of Virginia School of Medicine, Charlottesville, VA USA
| | - Constantine A Gatsonis
- 5Center for Statistical Sciences, Brown University School of Public Health, Providence, RI USA
| | - Paul P Glasziou
- 6Centre for Research in Evidence-Based Practice, Faculty of Health Sciences and Medicine, Bond University, Gold Coast, Queensland Australia
| | - Les Irwig
- 7Screening and Diagnostic Test Evaluation Program, School of Public Health, University of Sydney, Sydney, New South Wales Australia
| | - David Moher
- 8Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada.,9School of Epidemiology, Public Health and Preventive Medicine, University of Ottawa, Ottawa, Canada
| | - Henrica C W de Vet
- 10Department of Epidemiology and Biostatistics, EMGO Institute for Health and Care Research, VU University Medical Center, Amsterdam, The Netherlands
| | - Douglas G Altman
- 11Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK
| | - Lotty Hooft
- 12Dutch Cochrane Centre, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, University of Utrecht, Utrecht, The Netherlands
| | - Patrick M M Bossuyt
- 1Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Centre, University of Amsterdam, Amsterdam, The Netherlands
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Jansen J, Naganathan V, Carter SM, McLachlan AJ, Nickel B, Irwig L, Bonner C, Doust J, Colvin J, Heaney A, Turner R, McCaffery K. Too much medicine in older people? Deprescribing through shared decision making. BMJ 2016; 353:i2893. [PMID: 27260319 DOI: 10.1136/bmj.i2893] [Citation(s) in RCA: 171] [Impact Index Per Article: 21.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Affiliation(s)
- Jesse Jansen
- Screening and Test Evaluation Program, Sydney School of Public Health, University of Sydney, NSW 2006, Australia Centre for Medical Psychology and Evidence Based Decision Making, University of Sydney
| | - Vasi Naganathan
- Centre for Education and Research on Ageing, Ageing and Alzheimer's Institute, Concord Hospital, University of Sydney
| | - Stacy M Carter
- Centre for Values, Ethics and the Law in Medicine, University of Sydney
| | - Andrew J McLachlan
- Centre for Education and Research on Ageing, Ageing and Alzheimer's Institute, Concord Hospital, University of Sydney Faculty of Pharmacy, University of Sydney
| | - Brooke Nickel
- Screening and Test Evaluation Program, Sydney School of Public Health, University of Sydney, NSW 2006, Australia Centre for Medical Psychology and Evidence Based Decision Making, University of Sydney
| | - Les Irwig
- Screening and Test Evaluation Program, Sydney School of Public Health, University of Sydney, NSW 2006, Australia
| | - Carissa Bonner
- Screening and Test Evaluation Program, Sydney School of Public Health, University of Sydney, NSW 2006, Australia Centre for Medical Psychology and Evidence Based Decision Making, University of Sydney
| | - Jenny Doust
- Centre for Research in Evidence Based Practice, Bond University, Queensland, Australia
| | - Jim Colvin
- Health Consumers New South Wales, Australia
| | - Aine Heaney
- NPS MedicineWise, Surry Hills, NSW, Australia
| | - Robin Turner
- School of Public Health and Community Medicine, University of New South Wales, Australia
| | - Kirsten McCaffery
- Screening and Test Evaluation Program, Sydney School of Public Health, University of Sydney, NSW 2006, Australia Centre for Medical Psychology and Evidence Based Decision Making, University of Sydney
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35
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Marinovich ML, Azizi L, Macaskill P, Irwig L, Morrow M, Solin LJ, Houssami N. The association of surgical margins and local recurrence in women with ductal carcinoma in situ treated with breast-conserving therapy: A meta-analysis. J Clin Oncol 2016. [DOI: 10.1200/jco.2016.34.15_suppl.1020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Affiliation(s)
| | - Lamiae Azizi
- Screening and Test Evaluation Program (STEP), The University of Sydney, Australia
| | - Petra Macaskill
- Screening and Test Evaluation Program (STEP), The University of Sydney, Australia
| | - Les Irwig
- Screening and Test Evaluation Program (STEP), The University of Sydney, Australia
| | - Monica Morrow
- Memorial Sloan Kettering Cancer Center, New York, NY
| | | | - Nehmat Houssami
- Screening and Test Evaluation Program (STEP), The University of Sydney, Australia
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Bossuyt PM, Reitsma JB, Bruns DE, Gatsonis CA, Glasziou PP, Irwig L, Lijmer JG, Moher D, Rennie D, de Vet HCW, Kressel HY, Rifai N, Golub RM, Altman DG, Hooft L, Korevaar DA, Cohen JF. STARD 2015: An Updated List of Essential Items for Reporting Diagnostic Accuracy Studies. Clin Chem 2015; 61:1446-52. [PMID: 26510957 DOI: 10.1373/clinchem.2015.246280] [Citation(s) in RCA: 373] [Impact Index Per Article: 41.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2015] [Accepted: 09/18/2015] [Indexed: 12/18/2022]
Abstract
Incomplete reporting has been identified as a major source of avoidable waste in biomedical research. Essential information is often not provided in study reports, impeding the identification, critical appraisal, and replication of studies. To improve the quality of reporting of diagnostic accuracy studies, the Standards for Reporting of Diagnostic Accuracy Studies (STARD) statement was developed. Here we present STARD 2015, an updated list of 30 essential items that should be included in every report of a diagnostic accuracy study. This update incorporates recent evidence about sources of bias and variability in diagnostic accuracy and is intended to facilitate the use of STARD. As such, STARD 2015 may help to improve completeness and transparency in reporting of diagnostic accuracy studies.
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Affiliation(s)
- Patrick M Bossuyt
- Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Centre, University of Amsterdam, Amsterdam, the Netherlands;
| | - Johannes B Reitsma
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, University of Utrecht, Utrecht, the Netherlands
| | - David E Bruns
- Department of Pathology, University of Virginia School of Medicine, Charlottesville, VA
| | - Constantine A Gatsonis
- Center for Statistical Sciences, Brown University School of Public Health, Providence, RI
| | - Paul P Glasziou
- Centre for Research in Evidence-Based Practice, Faculty of Health Sciences and Medicine, Bond University, Gold Coast, Queensland, Australia
| | - Les Irwig
- Screening and Diagnostic Test Evaluation Program, School of Public Health, University of Sydney, Sydney, New South Wales, Australia
| | - Jeroen G Lijmer
- Department of Psychiatry, Onze Lieve Vrouwe Gasthuis, Amsterdam, the Netherlands
| | - David Moher
- Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada; School of Epidemiology, Public Health and Preventive Medicine, University of Ottawa, Ottawa, Canada
| | - Drummond Rennie
- Peer Review Congress, Chicago, IL; Philip R. Lee Institute for Health Policy Studies, University of California, San Francisco, CA
| | - Henrica C W de Vet
- Department of Epidemiology and Biostatistics, EMGO Institute for Health and Care Research, VU University Medical Center, Amsterdam, the Netherlands
| | - Herbert Y Kressel
- Department of Radiology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA; Radiology Editorial Office, Oak Brook, IL
| | - Nader Rifai
- Department of Laboratory Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA; Clinical Chemistry Editorial Office, Washington, DC
| | - Robert M Golub
- Division of General Internal Medicine and Geriatrics and Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL; JAMA Editorial Office, Chicago, IL
| | - Douglas G Altman
- Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK
| | - Lotty Hooft
- Dutch Cochrane Centre, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, University of Utrecht, Utrecht, the Netherlands
| | - Daniël A Korevaar
- Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Centre, University of Amsterdam, Amsterdam, the Netherlands
| | - Jérémie F Cohen
- Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Centre, University of Amsterdam, Amsterdam, the Netherlands; INSERM UMR 1153 and Department of Pediatrics, Necker Hospital, AP-HP, Paris Descartes University, Paris, France
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37
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Bossuyt PM, Reitsma JB, Bruns DE, Gatsonis CA, Glasziou PP, Irwig L, Lijmer JG, Moher D, Rennie D, de Vet HCW, Kressel HY, Rifai N, Golub RM, Altman DG, Hooft L, Korevaar DA, Cohen JF. STARD 2015: An Updated List of Essential Items for Reporting Diagnostic Accuracy Studies. Radiology 2015; 277:826-32. [PMID: 26509226 DOI: 10.1148/radiol.2015151516] [Citation(s) in RCA: 425] [Impact Index Per Article: 47.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Incomplete reporting has been identified as a major source of avoidable waste in biomedical research. Essential information is often not provided in study reports, impeding the identification, critical appraisal, and replication of studies. To improve the quality of reporting of diagnostic accuracy studies, the Standards for Reporting of Diagnostic Accuracy Studies (STARD) statement was developed. Here we present STARD 2015, an updated list of 30 essential items that should be included in every report of a diagnostic accuracy study. This update incorporates recent evidence about sources of bias and variability in diagnostic accuracy and is intended to facilitate the use of STARD. As such, STARD 2015 may help to improve completeness and transparency in reporting of diagnostic accuracy studies.
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Affiliation(s)
- Patrick M Bossuyt
- From the Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Centre, University of Amsterdam, PO Box 22700, 1100 DE Amsterdam, the Netherlands (P.M.B., D.A.K.); Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, University of Utrecht, Utrecht, the Netherlands (J.B.R.); Department of Pathology, University of Virginia School of Medicine, Charlottesville, Va (D.E.B.); Center for Statistical Sciences, Brown University School of Public Health, Providence, RI (C.A.G.); Centre for Research in Evidence-Based Practice, Faculty of Health Sciences and Medicine, Bond University, Gold Coast, Queensland, Australia (P.P.G.); Screening and Diagnostic Test Evaluation Program, School of Public Health, University of Sydney, Sydney, New South Wales, Australia (L.I.); Department of Psychiatry, Onze Lieve Vrouwe Gasthuis, Amsterdam, the Netherlands (J.G.L.); Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada (D.M.); School of Epidemiology, Public Health and Preventive Medicine, University of Ottawa, Ottawa, Canada (D.M.); Peer Review Congress, Chicago, Ill (D.R.); Philip R. Lee Institute for Health Policy Studies, University of California, San Francisco, Calif (D.R.); Department of Epidemiology and Biostatistics, EMGO Institute for Health and Care Research, VU University Medical Center, Amsterdam, the Netherlands (H.C.W.d.V.); Department of Radiology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Mass (H.Y.K.); Radiology Editorial Office, Boston, Mass (H.Y.K.); Department of Laboratory Medicine, Boston Children's Hospital, Harvard Medical School, Boston, Mass (N.R.); Clinical Chemistry Editorial Office, Washington, DC (N.R.); Division of General Internal Medicine and Geriatrics and Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Ill (R.M.G.); JAMA Editorial Office, Chicago, Ill (R.M.G.); Centre for Statistics in Me
| | - Johannes B Reitsma
- From the Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Centre, University of Amsterdam, PO Box 22700, 1100 DE Amsterdam, the Netherlands (P.M.B., D.A.K.); Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, University of Utrecht, Utrecht, the Netherlands (J.B.R.); Department of Pathology, University of Virginia School of Medicine, Charlottesville, Va (D.E.B.); Center for Statistical Sciences, Brown University School of Public Health, Providence, RI (C.A.G.); Centre for Research in Evidence-Based Practice, Faculty of Health Sciences and Medicine, Bond University, Gold Coast, Queensland, Australia (P.P.G.); Screening and Diagnostic Test Evaluation Program, School of Public Health, University of Sydney, Sydney, New South Wales, Australia (L.I.); Department of Psychiatry, Onze Lieve Vrouwe Gasthuis, Amsterdam, the Netherlands (J.G.L.); Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada (D.M.); School of Epidemiology, Public Health and Preventive Medicine, University of Ottawa, Ottawa, Canada (D.M.); Peer Review Congress, Chicago, Ill (D.R.); Philip R. Lee Institute for Health Policy Studies, University of California, San Francisco, Calif (D.R.); Department of Epidemiology and Biostatistics, EMGO Institute for Health and Care Research, VU University Medical Center, Amsterdam, the Netherlands (H.C.W.d.V.); Department of Radiology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Mass (H.Y.K.); Radiology Editorial Office, Boston, Mass (H.Y.K.); Department of Laboratory Medicine, Boston Children's Hospital, Harvard Medical School, Boston, Mass (N.R.); Clinical Chemistry Editorial Office, Washington, DC (N.R.); Division of General Internal Medicine and Geriatrics and Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Ill (R.M.G.); JAMA Editorial Office, Chicago, Ill (R.M.G.); Centre for Statistics in Me
| | - David E Bruns
- From the Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Centre, University of Amsterdam, PO Box 22700, 1100 DE Amsterdam, the Netherlands (P.M.B., D.A.K.); Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, University of Utrecht, Utrecht, the Netherlands (J.B.R.); Department of Pathology, University of Virginia School of Medicine, Charlottesville, Va (D.E.B.); Center for Statistical Sciences, Brown University School of Public Health, Providence, RI (C.A.G.); Centre for Research in Evidence-Based Practice, Faculty of Health Sciences and Medicine, Bond University, Gold Coast, Queensland, Australia (P.P.G.); Screening and Diagnostic Test Evaluation Program, School of Public Health, University of Sydney, Sydney, New South Wales, Australia (L.I.); Department of Psychiatry, Onze Lieve Vrouwe Gasthuis, Amsterdam, the Netherlands (J.G.L.); Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada (D.M.); School of Epidemiology, Public Health and Preventive Medicine, University of Ottawa, Ottawa, Canada (D.M.); Peer Review Congress, Chicago, Ill (D.R.); Philip R. Lee Institute for Health Policy Studies, University of California, San Francisco, Calif (D.R.); Department of Epidemiology and Biostatistics, EMGO Institute for Health and Care Research, VU University Medical Center, Amsterdam, the Netherlands (H.C.W.d.V.); Department of Radiology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Mass (H.Y.K.); Radiology Editorial Office, Boston, Mass (H.Y.K.); Department of Laboratory Medicine, Boston Children's Hospital, Harvard Medical School, Boston, Mass (N.R.); Clinical Chemistry Editorial Office, Washington, DC (N.R.); Division of General Internal Medicine and Geriatrics and Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Ill (R.M.G.); JAMA Editorial Office, Chicago, Ill (R.M.G.); Centre for Statistics in Me
| | - Constantine A Gatsonis
- From the Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Centre, University of Amsterdam, PO Box 22700, 1100 DE Amsterdam, the Netherlands (P.M.B., D.A.K.); Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, University of Utrecht, Utrecht, the Netherlands (J.B.R.); Department of Pathology, University of Virginia School of Medicine, Charlottesville, Va (D.E.B.); Center for Statistical Sciences, Brown University School of Public Health, Providence, RI (C.A.G.); Centre for Research in Evidence-Based Practice, Faculty of Health Sciences and Medicine, Bond University, Gold Coast, Queensland, Australia (P.P.G.); Screening and Diagnostic Test Evaluation Program, School of Public Health, University of Sydney, Sydney, New South Wales, Australia (L.I.); Department of Psychiatry, Onze Lieve Vrouwe Gasthuis, Amsterdam, the Netherlands (J.G.L.); Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada (D.M.); School of Epidemiology, Public Health and Preventive Medicine, University of Ottawa, Ottawa, Canada (D.M.); Peer Review Congress, Chicago, Ill (D.R.); Philip R. Lee Institute for Health Policy Studies, University of California, San Francisco, Calif (D.R.); Department of Epidemiology and Biostatistics, EMGO Institute for Health and Care Research, VU University Medical Center, Amsterdam, the Netherlands (H.C.W.d.V.); Department of Radiology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Mass (H.Y.K.); Radiology Editorial Office, Boston, Mass (H.Y.K.); Department of Laboratory Medicine, Boston Children's Hospital, Harvard Medical School, Boston, Mass (N.R.); Clinical Chemistry Editorial Office, Washington, DC (N.R.); Division of General Internal Medicine and Geriatrics and Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Ill (R.M.G.); JAMA Editorial Office, Chicago, Ill (R.M.G.); Centre for Statistics in Me
| | - Paul P Glasziou
- From the Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Centre, University of Amsterdam, PO Box 22700, 1100 DE Amsterdam, the Netherlands (P.M.B., D.A.K.); Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, University of Utrecht, Utrecht, the Netherlands (J.B.R.); Department of Pathology, University of Virginia School of Medicine, Charlottesville, Va (D.E.B.); Center for Statistical Sciences, Brown University School of Public Health, Providence, RI (C.A.G.); Centre for Research in Evidence-Based Practice, Faculty of Health Sciences and Medicine, Bond University, Gold Coast, Queensland, Australia (P.P.G.); Screening and Diagnostic Test Evaluation Program, School of Public Health, University of Sydney, Sydney, New South Wales, Australia (L.I.); Department of Psychiatry, Onze Lieve Vrouwe Gasthuis, Amsterdam, the Netherlands (J.G.L.); Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada (D.M.); School of Epidemiology, Public Health and Preventive Medicine, University of Ottawa, Ottawa, Canada (D.M.); Peer Review Congress, Chicago, Ill (D.R.); Philip R. Lee Institute for Health Policy Studies, University of California, San Francisco, Calif (D.R.); Department of Epidemiology and Biostatistics, EMGO Institute for Health and Care Research, VU University Medical Center, Amsterdam, the Netherlands (H.C.W.d.V.); Department of Radiology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Mass (H.Y.K.); Radiology Editorial Office, Boston, Mass (H.Y.K.); Department of Laboratory Medicine, Boston Children's Hospital, Harvard Medical School, Boston, Mass (N.R.); Clinical Chemistry Editorial Office, Washington, DC (N.R.); Division of General Internal Medicine and Geriatrics and Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Ill (R.M.G.); JAMA Editorial Office, Chicago, Ill (R.M.G.); Centre for Statistics in Me
| | - Les Irwig
- From the Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Centre, University of Amsterdam, PO Box 22700, 1100 DE Amsterdam, the Netherlands (P.M.B., D.A.K.); Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, University of Utrecht, Utrecht, the Netherlands (J.B.R.); Department of Pathology, University of Virginia School of Medicine, Charlottesville, Va (D.E.B.); Center for Statistical Sciences, Brown University School of Public Health, Providence, RI (C.A.G.); Centre for Research in Evidence-Based Practice, Faculty of Health Sciences and Medicine, Bond University, Gold Coast, Queensland, Australia (P.P.G.); Screening and Diagnostic Test Evaluation Program, School of Public Health, University of Sydney, Sydney, New South Wales, Australia (L.I.); Department of Psychiatry, Onze Lieve Vrouwe Gasthuis, Amsterdam, the Netherlands (J.G.L.); Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada (D.M.); School of Epidemiology, Public Health and Preventive Medicine, University of Ottawa, Ottawa, Canada (D.M.); Peer Review Congress, Chicago, Ill (D.R.); Philip R. Lee Institute for Health Policy Studies, University of California, San Francisco, Calif (D.R.); Department of Epidemiology and Biostatistics, EMGO Institute for Health and Care Research, VU University Medical Center, Amsterdam, the Netherlands (H.C.W.d.V.); Department of Radiology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Mass (H.Y.K.); Radiology Editorial Office, Boston, Mass (H.Y.K.); Department of Laboratory Medicine, Boston Children's Hospital, Harvard Medical School, Boston, Mass (N.R.); Clinical Chemistry Editorial Office, Washington, DC (N.R.); Division of General Internal Medicine and Geriatrics and Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Ill (R.M.G.); JAMA Editorial Office, Chicago, Ill (R.M.G.); Centre for Statistics in Me
| | - Jeroen G Lijmer
- From the Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Centre, University of Amsterdam, PO Box 22700, 1100 DE Amsterdam, the Netherlands (P.M.B., D.A.K.); Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, University of Utrecht, Utrecht, the Netherlands (J.B.R.); Department of Pathology, University of Virginia School of Medicine, Charlottesville, Va (D.E.B.); Center for Statistical Sciences, Brown University School of Public Health, Providence, RI (C.A.G.); Centre for Research in Evidence-Based Practice, Faculty of Health Sciences and Medicine, Bond University, Gold Coast, Queensland, Australia (P.P.G.); Screening and Diagnostic Test Evaluation Program, School of Public Health, University of Sydney, Sydney, New South Wales, Australia (L.I.); Department of Psychiatry, Onze Lieve Vrouwe Gasthuis, Amsterdam, the Netherlands (J.G.L.); Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada (D.M.); School of Epidemiology, Public Health and Preventive Medicine, University of Ottawa, Ottawa, Canada (D.M.); Peer Review Congress, Chicago, Ill (D.R.); Philip R. Lee Institute for Health Policy Studies, University of California, San Francisco, Calif (D.R.); Department of Epidemiology and Biostatistics, EMGO Institute for Health and Care Research, VU University Medical Center, Amsterdam, the Netherlands (H.C.W.d.V.); Department of Radiology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Mass (H.Y.K.); Radiology Editorial Office, Boston, Mass (H.Y.K.); Department of Laboratory Medicine, Boston Children's Hospital, Harvard Medical School, Boston, Mass (N.R.); Clinical Chemistry Editorial Office, Washington, DC (N.R.); Division of General Internal Medicine and Geriatrics and Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Ill (R.M.G.); JAMA Editorial Office, Chicago, Ill (R.M.G.); Centre for Statistics in Me
| | - David Moher
- From the Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Centre, University of Amsterdam, PO Box 22700, 1100 DE Amsterdam, the Netherlands (P.M.B., D.A.K.); Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, University of Utrecht, Utrecht, the Netherlands (J.B.R.); Department of Pathology, University of Virginia School of Medicine, Charlottesville, Va (D.E.B.); Center for Statistical Sciences, Brown University School of Public Health, Providence, RI (C.A.G.); Centre for Research in Evidence-Based Practice, Faculty of Health Sciences and Medicine, Bond University, Gold Coast, Queensland, Australia (P.P.G.); Screening and Diagnostic Test Evaluation Program, School of Public Health, University of Sydney, Sydney, New South Wales, Australia (L.I.); Department of Psychiatry, Onze Lieve Vrouwe Gasthuis, Amsterdam, the Netherlands (J.G.L.); Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada (D.M.); School of Epidemiology, Public Health and Preventive Medicine, University of Ottawa, Ottawa, Canada (D.M.); Peer Review Congress, Chicago, Ill (D.R.); Philip R. Lee Institute for Health Policy Studies, University of California, San Francisco, Calif (D.R.); Department of Epidemiology and Biostatistics, EMGO Institute for Health and Care Research, VU University Medical Center, Amsterdam, the Netherlands (H.C.W.d.V.); Department of Radiology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Mass (H.Y.K.); Radiology Editorial Office, Boston, Mass (H.Y.K.); Department of Laboratory Medicine, Boston Children's Hospital, Harvard Medical School, Boston, Mass (N.R.); Clinical Chemistry Editorial Office, Washington, DC (N.R.); Division of General Internal Medicine and Geriatrics and Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Ill (R.M.G.); JAMA Editorial Office, Chicago, Ill (R.M.G.); Centre for Statistics in Me
| | - Drummond Rennie
- From the Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Centre, University of Amsterdam, PO Box 22700, 1100 DE Amsterdam, the Netherlands (P.M.B., D.A.K.); Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, University of Utrecht, Utrecht, the Netherlands (J.B.R.); Department of Pathology, University of Virginia School of Medicine, Charlottesville, Va (D.E.B.); Center for Statistical Sciences, Brown University School of Public Health, Providence, RI (C.A.G.); Centre for Research in Evidence-Based Practice, Faculty of Health Sciences and Medicine, Bond University, Gold Coast, Queensland, Australia (P.P.G.); Screening and Diagnostic Test Evaluation Program, School of Public Health, University of Sydney, Sydney, New South Wales, Australia (L.I.); Department of Psychiatry, Onze Lieve Vrouwe Gasthuis, Amsterdam, the Netherlands (J.G.L.); Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada (D.M.); School of Epidemiology, Public Health and Preventive Medicine, University of Ottawa, Ottawa, Canada (D.M.); Peer Review Congress, Chicago, Ill (D.R.); Philip R. Lee Institute for Health Policy Studies, University of California, San Francisco, Calif (D.R.); Department of Epidemiology and Biostatistics, EMGO Institute for Health and Care Research, VU University Medical Center, Amsterdam, the Netherlands (H.C.W.d.V.); Department of Radiology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Mass (H.Y.K.); Radiology Editorial Office, Boston, Mass (H.Y.K.); Department of Laboratory Medicine, Boston Children's Hospital, Harvard Medical School, Boston, Mass (N.R.); Clinical Chemistry Editorial Office, Washington, DC (N.R.); Division of General Internal Medicine and Geriatrics and Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Ill (R.M.G.); JAMA Editorial Office, Chicago, Ill (R.M.G.); Centre for Statistics in Me
| | - Henrica C W de Vet
- From the Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Centre, University of Amsterdam, PO Box 22700, 1100 DE Amsterdam, the Netherlands (P.M.B., D.A.K.); Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, University of Utrecht, Utrecht, the Netherlands (J.B.R.); Department of Pathology, University of Virginia School of Medicine, Charlottesville, Va (D.E.B.); Center for Statistical Sciences, Brown University School of Public Health, Providence, RI (C.A.G.); Centre for Research in Evidence-Based Practice, Faculty of Health Sciences and Medicine, Bond University, Gold Coast, Queensland, Australia (P.P.G.); Screening and Diagnostic Test Evaluation Program, School of Public Health, University of Sydney, Sydney, New South Wales, Australia (L.I.); Department of Psychiatry, Onze Lieve Vrouwe Gasthuis, Amsterdam, the Netherlands (J.G.L.); Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada (D.M.); School of Epidemiology, Public Health and Preventive Medicine, University of Ottawa, Ottawa, Canada (D.M.); Peer Review Congress, Chicago, Ill (D.R.); Philip R. Lee Institute for Health Policy Studies, University of California, San Francisco, Calif (D.R.); Department of Epidemiology and Biostatistics, EMGO Institute for Health and Care Research, VU University Medical Center, Amsterdam, the Netherlands (H.C.W.d.V.); Department of Radiology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Mass (H.Y.K.); Radiology Editorial Office, Boston, Mass (H.Y.K.); Department of Laboratory Medicine, Boston Children's Hospital, Harvard Medical School, Boston, Mass (N.R.); Clinical Chemistry Editorial Office, Washington, DC (N.R.); Division of General Internal Medicine and Geriatrics and Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Ill (R.M.G.); JAMA Editorial Office, Chicago, Ill (R.M.G.); Centre for Statistics in Me
| | - Herbert Y Kressel
- From the Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Centre, University of Amsterdam, PO Box 22700, 1100 DE Amsterdam, the Netherlands (P.M.B., D.A.K.); Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, University of Utrecht, Utrecht, the Netherlands (J.B.R.); Department of Pathology, University of Virginia School of Medicine, Charlottesville, Va (D.E.B.); Center for Statistical Sciences, Brown University School of Public Health, Providence, RI (C.A.G.); Centre for Research in Evidence-Based Practice, Faculty of Health Sciences and Medicine, Bond University, Gold Coast, Queensland, Australia (P.P.G.); Screening and Diagnostic Test Evaluation Program, School of Public Health, University of Sydney, Sydney, New South Wales, Australia (L.I.); Department of Psychiatry, Onze Lieve Vrouwe Gasthuis, Amsterdam, the Netherlands (J.G.L.); Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada (D.M.); School of Epidemiology, Public Health and Preventive Medicine, University of Ottawa, Ottawa, Canada (D.M.); Peer Review Congress, Chicago, Ill (D.R.); Philip R. Lee Institute for Health Policy Studies, University of California, San Francisco, Calif (D.R.); Department of Epidemiology and Biostatistics, EMGO Institute for Health and Care Research, VU University Medical Center, Amsterdam, the Netherlands (H.C.W.d.V.); Department of Radiology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Mass (H.Y.K.); Radiology Editorial Office, Boston, Mass (H.Y.K.); Department of Laboratory Medicine, Boston Children's Hospital, Harvard Medical School, Boston, Mass (N.R.); Clinical Chemistry Editorial Office, Washington, DC (N.R.); Division of General Internal Medicine and Geriatrics and Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Ill (R.M.G.); JAMA Editorial Office, Chicago, Ill (R.M.G.); Centre for Statistics in Me
| | - Nader Rifai
- From the Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Centre, University of Amsterdam, PO Box 22700, 1100 DE Amsterdam, the Netherlands (P.M.B., D.A.K.); Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, University of Utrecht, Utrecht, the Netherlands (J.B.R.); Department of Pathology, University of Virginia School of Medicine, Charlottesville, Va (D.E.B.); Center for Statistical Sciences, Brown University School of Public Health, Providence, RI (C.A.G.); Centre for Research in Evidence-Based Practice, Faculty of Health Sciences and Medicine, Bond University, Gold Coast, Queensland, Australia (P.P.G.); Screening and Diagnostic Test Evaluation Program, School of Public Health, University of Sydney, Sydney, New South Wales, Australia (L.I.); Department of Psychiatry, Onze Lieve Vrouwe Gasthuis, Amsterdam, the Netherlands (J.G.L.); Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada (D.M.); School of Epidemiology, Public Health and Preventive Medicine, University of Ottawa, Ottawa, Canada (D.M.); Peer Review Congress, Chicago, Ill (D.R.); Philip R. Lee Institute for Health Policy Studies, University of California, San Francisco, Calif (D.R.); Department of Epidemiology and Biostatistics, EMGO Institute for Health and Care Research, VU University Medical Center, Amsterdam, the Netherlands (H.C.W.d.V.); Department of Radiology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Mass (H.Y.K.); Radiology Editorial Office, Boston, Mass (H.Y.K.); Department of Laboratory Medicine, Boston Children's Hospital, Harvard Medical School, Boston, Mass (N.R.); Clinical Chemistry Editorial Office, Washington, DC (N.R.); Division of General Internal Medicine and Geriatrics and Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Ill (R.M.G.); JAMA Editorial Office, Chicago, Ill (R.M.G.); Centre for Statistics in Me
| | - Robert M Golub
- From the Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Centre, University of Amsterdam, PO Box 22700, 1100 DE Amsterdam, the Netherlands (P.M.B., D.A.K.); Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, University of Utrecht, Utrecht, the Netherlands (J.B.R.); Department of Pathology, University of Virginia School of Medicine, Charlottesville, Va (D.E.B.); Center for Statistical Sciences, Brown University School of Public Health, Providence, RI (C.A.G.); Centre for Research in Evidence-Based Practice, Faculty of Health Sciences and Medicine, Bond University, Gold Coast, Queensland, Australia (P.P.G.); Screening and Diagnostic Test Evaluation Program, School of Public Health, University of Sydney, Sydney, New South Wales, Australia (L.I.); Department of Psychiatry, Onze Lieve Vrouwe Gasthuis, Amsterdam, the Netherlands (J.G.L.); Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada (D.M.); School of Epidemiology, Public Health and Preventive Medicine, University of Ottawa, Ottawa, Canada (D.M.); Peer Review Congress, Chicago, Ill (D.R.); Philip R. Lee Institute for Health Policy Studies, University of California, San Francisco, Calif (D.R.); Department of Epidemiology and Biostatistics, EMGO Institute for Health and Care Research, VU University Medical Center, Amsterdam, the Netherlands (H.C.W.d.V.); Department of Radiology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Mass (H.Y.K.); Radiology Editorial Office, Boston, Mass (H.Y.K.); Department of Laboratory Medicine, Boston Children's Hospital, Harvard Medical School, Boston, Mass (N.R.); Clinical Chemistry Editorial Office, Washington, DC (N.R.); Division of General Internal Medicine and Geriatrics and Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Ill (R.M.G.); JAMA Editorial Office, Chicago, Ill (R.M.G.); Centre for Statistics in Me
| | - Douglas G Altman
- From the Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Centre, University of Amsterdam, PO Box 22700, 1100 DE Amsterdam, the Netherlands (P.M.B., D.A.K.); Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, University of Utrecht, Utrecht, the Netherlands (J.B.R.); Department of Pathology, University of Virginia School of Medicine, Charlottesville, Va (D.E.B.); Center for Statistical Sciences, Brown University School of Public Health, Providence, RI (C.A.G.); Centre for Research in Evidence-Based Practice, Faculty of Health Sciences and Medicine, Bond University, Gold Coast, Queensland, Australia (P.P.G.); Screening and Diagnostic Test Evaluation Program, School of Public Health, University of Sydney, Sydney, New South Wales, Australia (L.I.); Department of Psychiatry, Onze Lieve Vrouwe Gasthuis, Amsterdam, the Netherlands (J.G.L.); Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada (D.M.); School of Epidemiology, Public Health and Preventive Medicine, University of Ottawa, Ottawa, Canada (D.M.); Peer Review Congress, Chicago, Ill (D.R.); Philip R. Lee Institute for Health Policy Studies, University of California, San Francisco, Calif (D.R.); Department of Epidemiology and Biostatistics, EMGO Institute for Health and Care Research, VU University Medical Center, Amsterdam, the Netherlands (H.C.W.d.V.); Department of Radiology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Mass (H.Y.K.); Radiology Editorial Office, Boston, Mass (H.Y.K.); Department of Laboratory Medicine, Boston Children's Hospital, Harvard Medical School, Boston, Mass (N.R.); Clinical Chemistry Editorial Office, Washington, DC (N.R.); Division of General Internal Medicine and Geriatrics and Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Ill (R.M.G.); JAMA Editorial Office, Chicago, Ill (R.M.G.); Centre for Statistics in Me
| | - Lotty Hooft
- From the Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Centre, University of Amsterdam, PO Box 22700, 1100 DE Amsterdam, the Netherlands (P.M.B., D.A.K.); Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, University of Utrecht, Utrecht, the Netherlands (J.B.R.); Department of Pathology, University of Virginia School of Medicine, Charlottesville, Va (D.E.B.); Center for Statistical Sciences, Brown University School of Public Health, Providence, RI (C.A.G.); Centre for Research in Evidence-Based Practice, Faculty of Health Sciences and Medicine, Bond University, Gold Coast, Queensland, Australia (P.P.G.); Screening and Diagnostic Test Evaluation Program, School of Public Health, University of Sydney, Sydney, New South Wales, Australia (L.I.); Department of Psychiatry, Onze Lieve Vrouwe Gasthuis, Amsterdam, the Netherlands (J.G.L.); Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada (D.M.); School of Epidemiology, Public Health and Preventive Medicine, University of Ottawa, Ottawa, Canada (D.M.); Peer Review Congress, Chicago, Ill (D.R.); Philip R. Lee Institute for Health Policy Studies, University of California, San Francisco, Calif (D.R.); Department of Epidemiology and Biostatistics, EMGO Institute for Health and Care Research, VU University Medical Center, Amsterdam, the Netherlands (H.C.W.d.V.); Department of Radiology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Mass (H.Y.K.); Radiology Editorial Office, Boston, Mass (H.Y.K.); Department of Laboratory Medicine, Boston Children's Hospital, Harvard Medical School, Boston, Mass (N.R.); Clinical Chemistry Editorial Office, Washington, DC (N.R.); Division of General Internal Medicine and Geriatrics and Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Ill (R.M.G.); JAMA Editorial Office, Chicago, Ill (R.M.G.); Centre for Statistics in Me
| | - Daniël A Korevaar
- From the Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Centre, University of Amsterdam, PO Box 22700, 1100 DE Amsterdam, the Netherlands (P.M.B., D.A.K.); Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, University of Utrecht, Utrecht, the Netherlands (J.B.R.); Department of Pathology, University of Virginia School of Medicine, Charlottesville, Va (D.E.B.); Center for Statistical Sciences, Brown University School of Public Health, Providence, RI (C.A.G.); Centre for Research in Evidence-Based Practice, Faculty of Health Sciences and Medicine, Bond University, Gold Coast, Queensland, Australia (P.P.G.); Screening and Diagnostic Test Evaluation Program, School of Public Health, University of Sydney, Sydney, New South Wales, Australia (L.I.); Department of Psychiatry, Onze Lieve Vrouwe Gasthuis, Amsterdam, the Netherlands (J.G.L.); Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada (D.M.); School of Epidemiology, Public Health and Preventive Medicine, University of Ottawa, Ottawa, Canada (D.M.); Peer Review Congress, Chicago, Ill (D.R.); Philip R. Lee Institute for Health Policy Studies, University of California, San Francisco, Calif (D.R.); Department of Epidemiology and Biostatistics, EMGO Institute for Health and Care Research, VU University Medical Center, Amsterdam, the Netherlands (H.C.W.d.V.); Department of Radiology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Mass (H.Y.K.); Radiology Editorial Office, Boston, Mass (H.Y.K.); Department of Laboratory Medicine, Boston Children's Hospital, Harvard Medical School, Boston, Mass (N.R.); Clinical Chemistry Editorial Office, Washington, DC (N.R.); Division of General Internal Medicine and Geriatrics and Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Ill (R.M.G.); JAMA Editorial Office, Chicago, Ill (R.M.G.); Centre for Statistics in Me
| | - Jérémie F Cohen
- From the Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Centre, University of Amsterdam, PO Box 22700, 1100 DE Amsterdam, the Netherlands (P.M.B., D.A.K.); Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, University of Utrecht, Utrecht, the Netherlands (J.B.R.); Department of Pathology, University of Virginia School of Medicine, Charlottesville, Va (D.E.B.); Center for Statistical Sciences, Brown University School of Public Health, Providence, RI (C.A.G.); Centre for Research in Evidence-Based Practice, Faculty of Health Sciences and Medicine, Bond University, Gold Coast, Queensland, Australia (P.P.G.); Screening and Diagnostic Test Evaluation Program, School of Public Health, University of Sydney, Sydney, New South Wales, Australia (L.I.); Department of Psychiatry, Onze Lieve Vrouwe Gasthuis, Amsterdam, the Netherlands (J.G.L.); Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada (D.M.); School of Epidemiology, Public Health and Preventive Medicine, University of Ottawa, Ottawa, Canada (D.M.); Peer Review Congress, Chicago, Ill (D.R.); Philip R. Lee Institute for Health Policy Studies, University of California, San Francisco, Calif (D.R.); Department of Epidemiology and Biostatistics, EMGO Institute for Health and Care Research, VU University Medical Center, Amsterdam, the Netherlands (H.C.W.d.V.); Department of Radiology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Mass (H.Y.K.); Radiology Editorial Office, Boston, Mass (H.Y.K.); Department of Laboratory Medicine, Boston Children's Hospital, Harvard Medical School, Boston, Mass (N.R.); Clinical Chemistry Editorial Office, Washington, DC (N.R.); Division of General Internal Medicine and Geriatrics and Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Ill (R.M.G.); JAMA Editorial Office, Chicago, Ill (R.M.G.); Centre for Statistics in Me
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Hersch J, Barratt A, Jansen J, Irwig L, McGeechan K, Jacklyn G, Thornton H, Dhillon H, Houssami N, McCaffery K. The importance of enabling informed decision making for women considering breast cancer screening. J Med Screen 2015; 23:55. [PMID: 26582494 DOI: 10.1177/0969141315612818] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Affiliation(s)
- Jolyn Hersch
- Screening & Test Evaluation Program (STEP), School of Public Health, The University of Sydney, Australia Centre for Medical Psychology & Evidence-based Decision-making (CeMPED), The University of Sydney, Australia
| | - Alexandra Barratt
- Centre for Medical Psychology & Evidence-based Decision-making (CeMPED), The University of Sydney, Australia
| | - Jesse Jansen
- Screening & Test Evaluation Program (STEP), School of Public Health, The University of Sydney, Australia Centre for Medical Psychology & Evidence-based Decision-making (CeMPED), The University of Sydney, Australia
| | - Les Irwig
- Screening & Test Evaluation Program (STEP), School of Public Health, The University of Sydney, Australia
| | - Kevin McGeechan
- Centre for Medical Psychology & Evidence-based Decision-making (CeMPED), The University of Sydney, Australia
| | - Gemma Jacklyn
- Screening & Test Evaluation Program (STEP), School of Public Health, The University of Sydney, Australia
| | - Hazel Thornton
- Department of Health Sciences, University of Leicester, UK
| | - Haryana Dhillon
- Centre for Medical Psychology & Evidence-based Decision-making (CeMPED), The University of Sydney, Australia
| | - Nehmat Houssami
- Screening & Test Evaluation Program (STEP), School of Public Health, The University of Sydney, Australia
| | - Kirsten McCaffery
- Screening & Test Evaluation Program (STEP), School of Public Health, The University of Sydney, Australia Centre for Medical Psychology & Evidence-based Decision-making (CeMPED), The University of Sydney, Australia
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McCaffery K, Nickel B, Moynihan R, Hersch J, Teixeira-Pinto A, Irwig L, Barratt A. How different terminology for ductal carcinoma in situ impacts women's concern and treatment preferences: a randomised comparison within a national community survey. BMJ Open 2015; 5:e008094. [PMID: 26525720 PMCID: PMC4636630 DOI: 10.1136/bmjopen-2015-008094] [Citation(s) in RCA: 40] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/02/2023] Open
Abstract
OBJECTIVE There have been calls to remove 'carcinoma' from terminology for in situ cancers such as ductal carcinoma in situ (DCIS), to reduce overdiagnosis and overtreatment. We investigated the effect of describing DCIS as 'abnormal cells' versus 'pre-invasive breast cancer cells' on women's concern and treatment preferences. SETTING AND PARTICIPANTS Community sample of Australian women (n=269) who spoke English as their main language at home. DESIGN Randomised comparison within a community survey. Women considered a hypothetical scenario involving a diagnosis of DCIS described as either 'abnormal cells' (arm A) or 'pre-invasive breast cancer cells' (arm B). Within each arm, the initial description was followed by the alternative term and outcomes reassessed. RESULTS Women in both arms indicated high concern, but still indicated strong initial preferences for watchful waiting (64%). There were no differences in initial concern or preferences by trial arm. However, more women in arm A ('abnormal cells' first term) indicated they would feel more concerned if given the alternative term ('pre-invasive breast cancer cells') compared to women in arm B who received the terms in the opposite order (67% arm A vs 52% arm B would feel more concerned, p=0.001). More women in arm A also changed their preference towards treatment when the terminology was switched from 'abnormal cells' to 'pre-invasive breast cancer cells' compared to arm B. In arm A, 18% of women changed their preference to treatment while only 6% changed to watchful waiting (p=0.008). In contrast, there were no significant changes in treatment preference in arm B when the terminology was switched (9% vs 8% changed their stated preference). CONCLUSIONS In a hypothetical scenario, interest in watchful waiting for DCIS was high, and changing terminology impacted women's concern and treatment preferences. Removal of the cancer term from DCIS may assist in efforts towards reducing overtreatment.
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Affiliation(s)
- Kirsten McCaffery
- Screening and Test Evaluation Program (STEP), Sydney School of Public Health, The University of Sydney, Sydney, New South Wales, Australia
- Centre for Medical Psychology and Evidence-based Decision-making (CeMPED), The University of Sydney, New South Wales, Australia
| | - Brooke Nickel
- Screening and Test Evaluation Program (STEP), Sydney School of Public Health, The University of Sydney, Sydney, New South Wales, Australia
- Centre for Medical Psychology and Evidence-based Decision-making (CeMPED), The University of Sydney, New South Wales, Australia
| | - Ray Moynihan
- Faculty of Health Sciences and Medicine, Bond University, Gold Coast, Queensland, Australia
| | - Jolyn Hersch
- Screening and Test Evaluation Program (STEP), Sydney School of Public Health, The University of Sydney, Sydney, New South Wales, Australia
- Centre for Medical Psychology and Evidence-based Decision-making (CeMPED), The University of Sydney, New South Wales, Australia
| | - Armando Teixeira-Pinto
- Screening and Test Evaluation Program (STEP), Sydney School of Public Health, The University of Sydney, Sydney, New South Wales, Australia
| | - Les Irwig
- Screening and Test Evaluation Program (STEP), Sydney School of Public Health, The University of Sydney, Sydney, New South Wales, Australia
| | - Alexandra Barratt
- Screening and Test Evaluation Program (STEP), Sydney School of Public Health, The University of Sydney, Sydney, New South Wales, Australia
- Centre for Medical Psychology and Evidence-based Decision-making (CeMPED), The University of Sydney, New South Wales, Australia
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Bossuyt PM, Reitsma JB, Bruns DE, Gatsonis CA, Glasziou PP, Irwig L, Lijmer JG, Moher D, Rennie D, de Vet HCW, Kressel HY, Rifai N, Golub RM, Altman DG, Hooft L, Korevaar DA, Cohen JF. STARD 2015: An Updated List of Essential Items for Reporting Diagnostic Accuracy Studies. Clin Chem 2015. [PMID: 26510957 DOI: 10.1373/clinchem.2015.246280.] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Incomplete reporting has been identified as a major source of avoidable waste in biomedical research. Essential information is often not provided in study reports, impeding the identification, critical appraisal, and replication of studies. To improve the quality of reporting of diagnostic accuracy studies, the Standards for Reporting of Diagnostic Accuracy Studies (STARD) statement was developed. Here we present STARD 2015, an updated list of 30 essential items that should be included in every report of a diagnostic accuracy study. This update incorporates recent evidence about sources of bias and variability in diagnostic accuracy and is intended to facilitate the use of STARD. As such, STARD 2015 may help to improve completeness and transparency in reporting of diagnostic accuracy studies.
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Affiliation(s)
- Patrick M Bossuyt
- Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Centre, University of Amsterdam, Amsterdam, the Netherlands;
| | - Johannes B Reitsma
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, University of Utrecht, Utrecht, the Netherlands
| | - David E Bruns
- Department of Pathology, University of Virginia School of Medicine, Charlottesville, VA
| | - Constantine A Gatsonis
- Center for Statistical Sciences, Brown University School of Public Health, Providence, RI
| | - Paul P Glasziou
- Centre for Research in Evidence-Based Practice, Faculty of Health Sciences and Medicine, Bond University, Gold Coast, Queensland, Australia
| | - Les Irwig
- Screening and Diagnostic Test Evaluation Program, School of Public Health, University of Sydney, Sydney, New South Wales, Australia
| | - Jeroen G Lijmer
- Department of Psychiatry, Onze Lieve Vrouwe Gasthuis, Amsterdam, the Netherlands
| | - David Moher
- Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada; School of Epidemiology, Public Health and Preventive Medicine, University of Ottawa, Ottawa, Canada
| | - Drummond Rennie
- Peer Review Congress, Chicago, IL; Philip R. Lee Institute for Health Policy Studies, University of California, San Francisco, CA
| | - Henrica C W de Vet
- Department of Epidemiology and Biostatistics, EMGO Institute for Health and Care Research, VU University Medical Center, Amsterdam, the Netherlands
| | - Herbert Y Kressel
- Department of Radiology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA; Radiology Editorial Office, Oak Brook, IL
| | - Nader Rifai
- Department of Laboratory Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA; Clinical Chemistry Editorial Office, Washington, DC
| | - Robert M Golub
- Division of General Internal Medicine and Geriatrics and Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL; JAMA Editorial Office, Chicago, IL
| | - Douglas G Altman
- Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK
| | - Lotty Hooft
- Dutch Cochrane Centre, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, University of Utrecht, Utrecht, the Netherlands
| | - Daniël A Korevaar
- Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Centre, University of Amsterdam, Amsterdam, the Netherlands
| | - Jérémie F Cohen
- Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Centre, University of Amsterdam, Amsterdam, the Netherlands; INSERM UMR 1153 and Department of Pediatrics, Necker Hospital, AP-HP, Paris Descartes University, Paris, France
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41
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Bossuyt PM, Reitsma JB, Bruns DE, Gatsonis CA, Glasziou PP, Irwig L, Lijmer JG, Moher D, Rennie D, de Vet HCW, Kressel HY, Rifai N, Golub RM, Altman DG, Hooft L, Korevaar DA, Cohen JF. STARD 2015: an updated list of essential items for reporting diagnostic accuracy studies. BMJ 2015; 351:h5527. [PMID: 26511519 PMCID: PMC4623764 DOI: 10.1136/bmj.h5527] [Citation(s) in RCA: 1723] [Impact Index Per Article: 191.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 09/18/2015] [Indexed: 02/06/2023]
Affiliation(s)
- Patrick M Bossuyt
- Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Centre, University of Amsterdam, Amsterdam, the Netherlands
| | - Johannes B Reitsma
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, University of Utrecht, Utrecht, the Netherlands
| | - David E Bruns
- Department of Pathology, University of Virginia School of Medicine, Charlottesville, VA, USA
| | - Constantine A Gatsonis
- Center for Statistical Sciences, Brown University School of Public Health, Providence, RI, USA
| | - Paul P Glasziou
- Centre for Research in Evidence-Based Practice, Faculty of Health Sciences and Medicine, Bond University, Gold Coast, Queensland, Australia
| | - Les Irwig
- Screening and Diagnostic Test Evaluation Program, School of Public Health, University of Sydney, Sydney, New South Wales, Australia
| | - Jeroen G Lijmer
- Department of Psychiatry, Onze Lieve Vrouwe Gasthuis, Amsterdam, the Netherlands
| | - David Moher
- Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada School of Epidemiology, Public Health and Preventive Medicine, University of Ottawa, Ottawa, Canada
| | - Drummond Rennie
- Peer Review Congress, Chicago, IL, USA Philip R Lee Institute for Health Policy Studies, University of California, San Francisco, CA, USA
| | - Henrica C W de Vet
- Department of Epidemiology and Biostatistics, EMGO Institute for Health and Care Research, VU University Medical Center, Amsterdam, the Netherlands
| | - Herbert Y Kressel
- Department of Radiology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA Radiology Editorial Office, Boston, MA, USA
| | - Nader Rifai
- Department of Laboratory Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA Clinical Chemistry Editorial Office, Washington, DC, USA
| | - Robert M Golub
- Division of General Internal Medicine and Geriatrics and Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA JAMA Editorial Office, Chicago, IL, USA
| | - Douglas G Altman
- Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK
| | - Lotty Hooft
- Dutch Cochrane Centre, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, University of Utrecht, Utrecht, the Netherlands
| | - Daniël A Korevaar
- Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Centre, University of Amsterdam, Amsterdam, the Netherlands
| | - Jérémie F Cohen
- Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Centre, University of Amsterdam, Amsterdam, the Netherlands INSERM UMR 1153 and Department of Pediatrics, Necker Hospital, AP-HP, Paris Descartes University, Paris, France
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Marinovich ML, Macaskill P, Irwig L, Sardanelli F, Mamounas E, von Minckwitz G, Guarneri V, Partridge SC, Wright FC, Choi JH, Bhattacharyya M, Martincich L, Yeh E, Londero V, Houssami N. Agreement between MRI and pathologic breast tumor size after neoadjuvant chemotherapy, and comparison with alternative tests: individual patient data meta-analysis. BMC Cancer 2015; 15:662. [PMID: 26449630 PMCID: PMC4599727 DOI: 10.1186/s12885-015-1664-4] [Citation(s) in RCA: 86] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2015] [Accepted: 09/29/2015] [Indexed: 11/25/2022] Open
Abstract
Background Magnetic resonance imaging (MRI) may guide breast cancer surgery by measuring residual tumor size post-neoadjuvant chemotherapy (NAC). Accurate measurement may avoid overly radical surgery or reduce the need for repeat surgery. This individual patient data (IPD) meta-analysis examines MRI’s agreement with pathology in measuring the longest tumor diameter and compares MRI with alternative tests. Methods A systematic review of MEDLINE, EMBASE, PREMEDLINE, Database of Abstracts of Reviews of Effects, Heath Technology Assessment, and Cochrane databases identified eligible studies. Primary study authors supplied IPD in a template format constructed a priori. Mean differences (MDs) between tests and pathology (i.e. systematic bias) were calculated and pooled by the inverse variance method; limits of agreement (LOA) were estimated. Test measurements of 0.0 cm in the presence of pathologic residual tumor, and measurements >0.0 cm despite pathologic complete response (pCR) were described for MRI and alternative tests. Results Eight studies contributed IPD (N = 300). The pooled MD for MRI was 0.0 cm (LOA: +/−3.8 cm). Ultrasound underestimated pathologic size (MD: −0.3 cm) relative to MRI (MD: 0.1 cm), with comparable LOA. MDs were similar for MRI (0.1 cm) and mammography (0.0 cm), with wider LOA for mammography. Clinical examination underestimated size (MD: −0.8 cm) relative to MRI (MD: 0.0 cm), with wider LOA. Tumors “missed” by MRI typically measured 2.0 cm or less at pathology; tumors >2.0 cm were more commonly “missed” by clinical examination (9.3 %). MRI measurements >5.0 cm occurred in 5.3 % of patients with pCR, but were more frequent for mammography (46.2 %). Conclusions There was no systematic bias in MRI tumor measurement, but LOA are large enough to be clinically important. MRI’s performance was generally superior to ultrasound, mammography, and clinical examination, and it may be considered the most appropriate test in this setting. Test combinations should be explored in future studies. Electronic supplementary material The online version of this article (doi:10.1186/s12885-015-1664-4) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Michael L Marinovich
- Screening and Test Evaluation Program (STEP), Sydney School of Public Health, The University of Sydney, A27, Edward Ford Building, Sydney, NSW, 2006, Australia.
| | - Petra Macaskill
- Screening and Test Evaluation Program (STEP), Sydney School of Public Health, The University of Sydney, A27, Edward Ford Building, Sydney, NSW, 2006, Australia.
| | - Les Irwig
- Screening and Test Evaluation Program (STEP), Sydney School of Public Health, The University of Sydney, A27, Edward Ford Building, Sydney, NSW, 2006, Australia.
| | - Francesco Sardanelli
- Dipartimento di Scienze Biomediche per la Salute, Università degli Studi di Milano, Unità di Radiologia, IRCCS Policlinico San Donato, Piazza E. Malan 2, San Donato Milanese, Milano, Italy.
| | - Eleftherios Mamounas
- MD Anderson Cancer Center Orlando, 1400 South Orange Avenue, MP 700, Orlando, FL, 32806, USA.
| | - Gunter von Minckwitz
- German Breast Group & Universitäts-Frauenklinik Frankfurt, Martin-Behaim-Str. 12, 63263, Neu-Isenburg, Germany.
| | - Valentina Guarneri
- University of Padova, Division of Medical Oncology 2, Istituto Oncologico Veneto IRCCS, Padova, Italy.
| | - Savannah C Partridge
- Department of Radiology, University of Washington, 825 Eastlake Ave E, G3-200, Seattle, WA, 98109-1023, USA.
| | - Frances C Wright
- Division of General Surgery, Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, Toronto, ON, M4C 5T2, Canada.
| | - Jae Hyuck Choi
- School of Medicine, Jeju National University Hospital, Aran 13gil 15(ara-1 dong), Jeju-si, Jeju-do, South Korea.
| | - Madhumita Bhattacharyya
- Berkshire Cancer Centre, Royal Berkshire NHS Foundation Trust, London Road, Reading, RG1 5AN, UK.
| | - Laura Martincich
- Direzione Radiodiagnostica, Fondazione del Piemonte per l'Oncologia-IRCCS, Str. Prov.142, Candiolo, Torino, Italy.
| | - Eren Yeh
- Department of Radiology, Brigham and Women's Hospital, 75 Francis St, Boston, MA, 02115, USA.
| | - Viviana Londero
- Institute of Radiology, University of Udine, p.le S.M. della Misericordia, 15, 33100, Udine, Italy.
| | - Nehmat Houssami
- Screening and Test Evaluation Program (STEP), Sydney School of Public Health, The University of Sydney, A27, Edward Ford Building, Sydney, NSW, 2006, Australia.
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Nickel B, Barratt A, Hersch J, Moynihan R, Irwig L, McCaffery K. How different terminology for ductal carcinoma in situ (DCIS) impacts women's concern and management preferences: A qualitative study. Breast 2015; 24:673-9. [PMID: 26376460 DOI: 10.1016/j.breast.2015.08.004] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2015] [Revised: 08/14/2015] [Accepted: 08/19/2015] [Indexed: 10/23/2022] Open
Abstract
OBJECTIVE There are increasing rates of mastectomy and bi-lateral mastectomy in women diagnosed with ductal carcinoma in situ (DCIS). To help women avoid decisions that lead to unnecessary aggressive treatments, there have been recent calls to remove the cancer terminology from descriptions of DCIS. We investigated how different proposed terminologies for DCIS affect women's perceived concern and management preferences. MATERIALS AND METHODS Qualitative study using semi-structured interviews with a community sample of 26 Australian women varying by education and cancer screening experience. Women responded to a hypothetical scenario using terminology with and without the cancer term to describe DCIS. RESULTS Among a sample of women with no experience of a DCIS diagnosis, a hypothetical scenario involving a diagnosis of DCIS elicited high concern regardless of the terminology used to describe it. Women generally exhibited stronger negative reactions when a cancer term was used to describe DCIS compared to a non-cancer term, and most preferred the diagnosis be given as a description of abnormal cells. Overall women expressed interest in watchful waiting for DCIS but displayed preferences for very frequent monitoring with this management approach. CONCLUSION Communicating a diagnosis of DCIS using terminology that does not include the cancer term was preferred by many women and may enable discussions about more conservative management options. However, women's preference for frequent monitoring during watchful waiting suggests women need more education and reassurance about this management approach.
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Affiliation(s)
- Brooke Nickel
- Screening and Test Evaluation Program (STEP), Sydney School of Public Health, The University of Sydney, NSW 2006, Australia; Centre for Medical Psychology and Evidence-based Decision-making (CeMPED), The University of Sydney, NSW 2006, Australia
| | - Alexandra Barratt
- Screening and Test Evaluation Program (STEP), Sydney School of Public Health, The University of Sydney, NSW 2006, Australia; Centre for Medical Psychology and Evidence-based Decision-making (CeMPED), The University of Sydney, NSW 2006, Australia
| | - Jolyn Hersch
- Screening and Test Evaluation Program (STEP), Sydney School of Public Health, The University of Sydney, NSW 2006, Australia; Centre for Medical Psychology and Evidence-based Decision-making (CeMPED), The University of Sydney, NSW 2006, Australia
| | - Ray Moynihan
- Faculty of Health Sciences and Medicine, Bond University, QLD 4229, Australia
| | - Les Irwig
- Screening and Test Evaluation Program (STEP), Sydney School of Public Health, The University of Sydney, NSW 2006, Australia
| | - Kirsten McCaffery
- Screening and Test Evaluation Program (STEP), Sydney School of Public Health, The University of Sydney, NSW 2006, Australia; Centre for Medical Psychology and Evidence-based Decision-making (CeMPED), The University of Sydney, NSW 2006, Australia.
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Jansen J, McKinn S, Bonner C, Irwig L, Doust J, Glasziou P, Nickel B, van Munster B, McCaffery K. Systematic review of clinical practice guidelines recommendations about primary cardiovascular disease prevention for older adults. BMC Fam Pract 2015; 16:104. [PMID: 26289559 PMCID: PMC4546022 DOI: 10.1186/s12875-015-0310-1] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/10/2015] [Accepted: 07/22/2015] [Indexed: 01/01/2023]
Abstract
BACKGROUND Clinical care for older adults is complex and represents a growing problem. They are a diverse patient group with varying needs, frequent presence of multiple comorbidities, and are more susceptible to treatment harms. Thus Clinical Practice Guidelines (CPGs) need to carefully consider older adults in order to guide clinicians. We reviewed CPG recommendations for primary cardiovascular disease (CVD) prevention and examined the extent to which CPGs address issues important for older people identified in the literature. METHODS We searched: 1) two systematic reviews on CPGs for CVD prevention and 2) the National CPG Clearinghouse, G-I-N International CPG Library and Trip databases for CPGs for CVD prevention, hypertension and cholesterol. We conducted our search between April and December 2013. We excluded CPGs for diabetes, chronic kidney disease, HIV, lifestyle, general screening/prevention, and pregnant or pediatric populations. Three authors independently screened citations for inclusion and extracted data. The primary outcomes were presence and extent of recommendations for older people including discussion of: (1) available evidence, (2) barriers to implementation of the CPG, and (3) tailoring management for this group. RESULTS We found 47 eligible CPGs. There was no mention of older people in 4 (9 %) of the CPGs. Benefits were discussed more frequently than harms. Twenty-three CPGs (49 %) discussed evidence about potential benefits and 18 (38 %) discussed potential harms of CVD prevention in older people. Most CPGs addressed one or more barriers to implementation, often as a short statement. Although 27 CPGs (58 %) mentioned tailoring management to the older patient context (e.g. comorbidities), concrete guidance was rare. CONCLUSION Although most CVD prevention CPGs mention the older population to some extent, the information provided is vague and very limited. Older adults represent a growing proportion of the population. Guideline developers must ensure they consider older patients' needs and provide appropriate advice to clinicians in order to support high quality care for this group. CPGs should at a minimum address the available evidence about CVD prevention for older people, and acknowledge the importance of patient involvement.
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Affiliation(s)
- Jesse Jansen
- Screening & Test Evaluation Program (STEP), Sydney School of Public Health, The University of Sydney, Edward Ford Building A27, Sydney, NSW 2006, Australia.
- Centre for Medical Psychology and Evidence-based Decision-making (CeMPED), The University of Sydney, Edward Ford Building A27, Sydney, NSW 2006, Australia.
| | - Shannon McKinn
- Screening & Test Evaluation Program (STEP), Sydney School of Public Health, The University of Sydney, Edward Ford Building A27, Sydney, NSW 2006, Australia.
- Centre for Medical Psychology and Evidence-based Decision-making (CeMPED), The University of Sydney, Edward Ford Building A27, Sydney, NSW 2006, Australia.
| | - Carissa Bonner
- Screening & Test Evaluation Program (STEP), Sydney School of Public Health, The University of Sydney, Edward Ford Building A27, Sydney, NSW 2006, Australia.
- Centre for Medical Psychology and Evidence-based Decision-making (CeMPED), The University of Sydney, Edward Ford Building A27, Sydney, NSW 2006, Australia.
| | - Les Irwig
- Screening & Test Evaluation Program (STEP), Sydney School of Public Health, The University of Sydney, Edward Ford Building A27, Sydney, NSW 2006, Australia.
| | - Jenny Doust
- Screening & Test Evaluation Program (STEP), Sydney School of Public Health, The University of Sydney, Edward Ford Building A27, Sydney, NSW 2006, Australia.
- Faculty of Health Sciences and Medicine, Bond University, Robina, QLD 4226, Australia.
| | - Paul Glasziou
- Screening & Test Evaluation Program (STEP), Sydney School of Public Health, The University of Sydney, Edward Ford Building A27, Sydney, NSW 2006, Australia.
- Faculty of Health Sciences and Medicine, Bond University, Robina, QLD 4226, Australia.
| | - Brooke Nickel
- Screening & Test Evaluation Program (STEP), Sydney School of Public Health, The University of Sydney, Edward Ford Building A27, Sydney, NSW 2006, Australia.
- Centre for Medical Psychology and Evidence-based Decision-making (CeMPED), The University of Sydney, Edward Ford Building A27, Sydney, NSW 2006, Australia.
| | - Barbara van Munster
- Academic Medical Centre, Department of Internal Medicine, University of Amsterdam, Meibergdreef 9, 1105 AZ, Amsterdam, Netherlands.
- Department of Geriatrics, Gelre Hospitaal, Albert Schweitzerlaan 31, 7334 DZ, Apeldoorn, Netherlands.
| | - Kirsten McCaffery
- Screening & Test Evaluation Program (STEP), Sydney School of Public Health, The University of Sydney, Edward Ford Building A27, Sydney, NSW 2006, Australia.
- Centre for Medical Psychology and Evidence-based Decision-making (CeMPED), The University of Sydney, Edward Ford Building A27, Sydney, NSW 2006, Australia.
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Bonner C, Jansen J, Newell BR, Irwig L, Teixeira-Pinto A, Glasziou P, Doust J, McKinn S, McCaffery K. Is the “Heart Age” Concept Helpful or Harmful Compared to Absolute Cardiovascular Disease Risk? An Experimental Study. Med Decis Making 2015; 35:967-78. [DOI: 10.1177/0272989x15597224] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2014] [Accepted: 05/28/2015] [Indexed: 11/16/2022]
Abstract
Background. Cardiovascular disease (CVD) prevention guidelines are generally based on the absolute risk of a CVD event, but there is increasing interest in using ‘heart age’ to motivate lifestyle change when absolute risk is low. Previous studies have not compared heart age to 5-year absolute risk, or investigated the impact of younger heart age, graphical format, and numeracy. Objective. Compare heart age versus 5-year absolute risk on psychological and behavioral outcomes. Design. 2 (heart age, absolute risk) × 3 (text only, bar graph, line graph) experiment. Setting. Online. Participants. 570 Australians aged 45–64 years, not taking CVD-related medication. Intervention. CVD risk assessment. Measurements. Intention to change lifestyle, recall, risk perception, emotional response, perceived credibility, and lifestyle behaviors after 2 weeks. Results. Most participants had lifestyle risk factors (95%) but low 5-year absolute risk (94%). Heart age did not improve lifestyle intentions and behaviors compared to absolute risk, was more often interpreted as a higher-risk category by low-risk participants (47% vs 23%), and decreased perceived credibility and positive emotional response. Overall, correct recall dropped from 65% to 24% after 2 weeks, with heart age recalled better than absolute risk at 2 weeks (32% vs 16%). These results were found across younger and older heart age results, graphical format, and numeracy. Limitations. Communicating CVD risk in a consultation rather than online may produce different results. Conclusions. There is no evidence that heart age motivates lifestyle change more than 5-year absolute risk in individuals with low CVD risk. Five-year absolute risk may be a better way to explain CVD risk, because it is more credible, does not inflate risk perception, and is consistent with clinical guidelines that base lifestyle and medication recommendations on absolute risk.
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Affiliation(s)
- Carissa Bonner
- Screening and Test Evaluation Program (STEP), Sydney School of Public Health, The University of Sydney, Sydney, NSW, Australia (CB, JJ, LI, ATP, PG, JD, SM, KM)
- Centre for Medical Psychology and Evidence-based Decision-making (CeMPED), The University of Sydney, Sydney, NSW, Australia (CB, JJ, SM, KM)
- School of Psychology, University of New South Wales, Sydney, NSW, Australia (BRN)
- Faculty of Health Sciences and Medicine, Bond University, Robina, QLD, Australia (PG, JD)
| | - Jesse Jansen
- Screening and Test Evaluation Program (STEP), Sydney School of Public Health, The University of Sydney, Sydney, NSW, Australia (CB, JJ, LI, ATP, PG, JD, SM, KM)
- Centre for Medical Psychology and Evidence-based Decision-making (CeMPED), The University of Sydney, Sydney, NSW, Australia (CB, JJ, SM, KM)
- School of Psychology, University of New South Wales, Sydney, NSW, Australia (BRN)
- Faculty of Health Sciences and Medicine, Bond University, Robina, QLD, Australia (PG, JD)
| | - Ben R. Newell
- Screening and Test Evaluation Program (STEP), Sydney School of Public Health, The University of Sydney, Sydney, NSW, Australia (CB, JJ, LI, ATP, PG, JD, SM, KM)
- Centre for Medical Psychology and Evidence-based Decision-making (CeMPED), The University of Sydney, Sydney, NSW, Australia (CB, JJ, SM, KM)
- School of Psychology, University of New South Wales, Sydney, NSW, Australia (BRN)
- Faculty of Health Sciences and Medicine, Bond University, Robina, QLD, Australia (PG, JD)
| | - Les Irwig
- Screening and Test Evaluation Program (STEP), Sydney School of Public Health, The University of Sydney, Sydney, NSW, Australia (CB, JJ, LI, ATP, PG, JD, SM, KM)
- Centre for Medical Psychology and Evidence-based Decision-making (CeMPED), The University of Sydney, Sydney, NSW, Australia (CB, JJ, SM, KM)
- School of Psychology, University of New South Wales, Sydney, NSW, Australia (BRN)
- Faculty of Health Sciences and Medicine, Bond University, Robina, QLD, Australia (PG, JD)
| | - Armando Teixeira-Pinto
- Screening and Test Evaluation Program (STEP), Sydney School of Public Health, The University of Sydney, Sydney, NSW, Australia (CB, JJ, LI, ATP, PG, JD, SM, KM)
- Centre for Medical Psychology and Evidence-based Decision-making (CeMPED), The University of Sydney, Sydney, NSW, Australia (CB, JJ, SM, KM)
- School of Psychology, University of New South Wales, Sydney, NSW, Australia (BRN)
- Faculty of Health Sciences and Medicine, Bond University, Robina, QLD, Australia (PG, JD)
| | - Paul Glasziou
- Screening and Test Evaluation Program (STEP), Sydney School of Public Health, The University of Sydney, Sydney, NSW, Australia (CB, JJ, LI, ATP, PG, JD, SM, KM)
- Centre for Medical Psychology and Evidence-based Decision-making (CeMPED), The University of Sydney, Sydney, NSW, Australia (CB, JJ, SM, KM)
- School of Psychology, University of New South Wales, Sydney, NSW, Australia (BRN)
- Faculty of Health Sciences and Medicine, Bond University, Robina, QLD, Australia (PG, JD)
| | - Jenny Doust
- Screening and Test Evaluation Program (STEP), Sydney School of Public Health, The University of Sydney, Sydney, NSW, Australia (CB, JJ, LI, ATP, PG, JD, SM, KM)
- Centre for Medical Psychology and Evidence-based Decision-making (CeMPED), The University of Sydney, Sydney, NSW, Australia (CB, JJ, SM, KM)
- School of Psychology, University of New South Wales, Sydney, NSW, Australia (BRN)
- Faculty of Health Sciences and Medicine, Bond University, Robina, QLD, Australia (PG, JD)
| | - Shannon McKinn
- Screening and Test Evaluation Program (STEP), Sydney School of Public Health, The University of Sydney, Sydney, NSW, Australia (CB, JJ, LI, ATP, PG, JD, SM, KM)
- Centre for Medical Psychology and Evidence-based Decision-making (CeMPED), The University of Sydney, Sydney, NSW, Australia (CB, JJ, SM, KM)
- School of Psychology, University of New South Wales, Sydney, NSW, Australia (BRN)
- Faculty of Health Sciences and Medicine, Bond University, Robina, QLD, Australia (PG, JD)
| | - Kirsten McCaffery
- Screening and Test Evaluation Program (STEP), Sydney School of Public Health, The University of Sydney, Sydney, NSW, Australia (CB, JJ, LI, ATP, PG, JD, SM, KM)
- Centre for Medical Psychology and Evidence-based Decision-making (CeMPED), The University of Sydney, Sydney, NSW, Australia (CB, JJ, SM, KM)
- School of Psychology, University of New South Wales, Sydney, NSW, Australia (BRN)
- Faculty of Health Sciences and Medicine, Bond University, Robina, QLD, Australia (PG, JD)
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Barratt A, Irwig L, Glasziou P. A novel case-control design to estimate the extent of over-diagnosis of breast cancer due to organised population-based mammography screening. Int J Cancer 2015; 136:2486. [DOI: 10.1002/ijc.29270] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2014] [Accepted: 09/12/2014] [Indexed: 11/10/2022]
Affiliation(s)
| | - Les Irwig
- School of Public Health; University of Sydney; Australia
| | - Paul Glasziou
- Centre for Research in Evidence-Based Practice; Bond University; Australia
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47
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Memari N, Hayen A, Bell KJL, Rychetnik L, Morton RL, McCaffery K, Thompson JF, Irwig L, Turner RM. How Often Do Patients with Localized Melanoma Attend Follow-Up at a Specialist Center? Ann Surg Oncol 2015; 22 Suppl 3:S1164-71. [PMID: 25963479 DOI: 10.1245/s10434-015-4589-x] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2014] [Indexed: 11/18/2022]
Abstract
BACKGROUND Post-treatment follow-up for patients with American Joint Committee on Cancer (AJCC) stage I/II melanoma is believed to be important for early detection of disease recurrence and new primary melanomas, but comes with costs to both patients and healthcare providers. We aimed to determine how frequently a cohort of patients attended follow-up after surgical treatment at one Specialist Center. METHODS We used prospectively collected data from the Melanoma Institute Australia (MIA) for patients with AJCC stage I/II melanoma diagnosed between January 2008 and December 2011. The distribution of the number of recorded follow-up visits per patient was analyzed and compared with the number of follow-up visits recommended in the 2008 Australian and New Zealand Melanoma Management Guidelines. RESULTS A total of 3813 patients with stage I/II melanoma were identified. During the first year of follow-up post-surgery, 34 % of stage I patients and 14 % of stage II patients had the number of follow-up visits recommended in the guidelines. A large proportion of melanoma patients did not appear to be routinely followed up at MIA, with 43.2 % of stage I patients and 28.7 % of stage II patients having either no visit or only one visit post-surgery. During all years of follow-up, 13.2 % of stage I patients and 4.1 % of stage II patients had the number of follow-up visits at the specialist center as recommended in the guidelines. CONCLUSIONS The large proportion of patients who had fewer follow-up visits than expected suggests (i) many patients are followed up in clinics elsewhere, and/or (ii) post-surgical surveillance is less frequent in practice.
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Affiliation(s)
- Niloofar Memari
- School of Public Health, The University of Sydney, Sydney, NSW, Australia
| | - Andrew Hayen
- School of Public Health and Community Medicine, UNSW Australia, Sydney, NSW, Australia
| | - Katy J L Bell
- School of Public Health, The University of Sydney, Sydney, NSW, Australia.,Faculty of Health Sciences and Medicine, Bond University, Gold Coast, QLD, Australia
| | - Lucie Rychetnik
- School of Medicine, University of Notre Dame Australia, Sydney, NSW, Australia
| | - Rachael L Morton
- School of Public Health, The University of Sydney, Sydney, NSW, Australia.,Health Economics Research Centre, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Kirsten McCaffery
- School of Public Health, The University of Sydney, Sydney, NSW, Australia
| | - John F Thompson
- Melanoma Institute Australia, Sydney, NSW, Australia.,Sydney Medical School, The University of Sydney, Sydney, NSW, Australia
| | - Les Irwig
- School of Public Health, The University of Sydney, Sydney, NSW, Australia
| | - Robin M Turner
- School of Public Health and Community Medicine, UNSW Australia, Sydney, NSW, Australia.
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Hersch J, Barratt A, Jansen J, Irwig L, McGeechan K, Jacklyn G, Thornton H, Dhillon H, Houssami N, McCaffery K. Use of a decision aid including information on overdetection to support informed choice about breast cancer screening: a randomised controlled trial. Lancet 2015; 385:1642-52. [PMID: 25701273 DOI: 10.1016/s0140-6736(15)60123-4] [Citation(s) in RCA: 190] [Impact Index Per Article: 21.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
BACKGROUND Mammography screening can reduce breast cancer mortality. However, most women are unaware that inconsequential disease can also be detected by screening, leading to overdiagnosis and overtreatment. We aimed to investigate whether including information about overdetection of breast cancer in a decision aid would help women aged around 50 years to make an informed choice about breast screening. METHODS We did a community-based, parallel-group, randomised controlled trial in New South Wales, Australia, using a random cohort of women aged 48-50 years. Recruitment to the study was done by telephone; women were eligible if they had not had mammography in the past 2 years and did not have a personal or strong family history of breast cancer. With a computer program, we randomly assigned 879 participants to either the intervention decision aid (comprising evidence-based explanatory and quantitative information on overdetection, breast cancer mortality reduction, and false positives) or a control decision aid (including information on breast cancer mortality reduction and false positives). Participants and interviewers were masked to group assignment. The primary outcome was informed choice (defined as adequate knowledge and consistency between attitudes and screening intentions), which we assessed by telephone interview about 3 weeks after random allocation. The primary outcome was analysed in all women who completed the relevant follow-up interview questions fully. This trial is registered with the Australian New Zealand Clinical Trials Registry, number ACTRN12613001035718. FINDINGS Between January, 2014, and July, 2014, 440 women were allocated to the intervention group and 439 were assigned to the control group. 21 women in the intervention group and 20 controls were lost to follow-up; a further ten women assigned to the intervention and 11 controls did not answer all questions on attitudes. Therefore, 409 women in the intervention group and 408 controls were analysed for the primary outcome. 99 (24%) of 409 women in the intervention group made an informed choice compared with 63 (15%) of 408 in the control group (difference 9%, 95% CI 3-14; p=0·0017). Compared with controls, more women in the intervention group met the threshold for adequate overall knowledge (122/419 [29%] vs 71/419 [17%]; difference 12%, 95% CI 6-18; p<0·0001), fewer women expressed positive attitudes towards screening (282/409 [69%] vs 340/408 [83%]; 14%, 9-20; p<0·0001), and fewer women intended to be screened (308/419 [74%] vs 363/419 [87%]; 13%, 8-19; p<0·0001). When conceptual knowledge alone was considered, 203 (50%) of 409 women in the intervention group made an informed choice compared with 79 (19%) of 408 in the control group (p<0·0001). INTERPRETATION Information on overdetection of breast cancer provided within a decision aid increased the number of women making an informed choice about breast screening. Becoming better informed might mean women are less likely to choose screening. FUNDING Australian National Health and Medical Research Council.
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Affiliation(s)
- Jolyn Hersch
- Screening & Test Evaluation Program (STEP), The University of Sydney, Sydney, NSW 2006, Australia; Centre for Medical Psychology & Evidence-based Decision-making (CeMPED), The University of Sydney, Sydney, NSW 2006, Australia
| | - Alexandra Barratt
- Centre for Medical Psychology & Evidence-based Decision-making (CeMPED), The University of Sydney, Sydney, NSW 2006, Australia
| | - Jesse Jansen
- Screening & Test Evaluation Program (STEP), The University of Sydney, Sydney, NSW 2006, Australia; Centre for Medical Psychology & Evidence-based Decision-making (CeMPED), The University of Sydney, Sydney, NSW 2006, Australia
| | - Les Irwig
- Screening & Test Evaluation Program (STEP), The University of Sydney, Sydney, NSW 2006, Australia
| | - Kevin McGeechan
- Centre for Medical Psychology & Evidence-based Decision-making (CeMPED), The University of Sydney, Sydney, NSW 2006, Australia
| | - Gemma Jacklyn
- School of Public Health, The University of Sydney, Sydney, NSW 2006, Australia
| | - Hazel Thornton
- Department of Health Sciences, University of Leicester; Leicester, UK
| | - Haryana Dhillon
- Centre for Medical Psychology & Evidence-based Decision-making (CeMPED), The University of Sydney, Sydney, NSW 2006, Australia; Central Clinical School, The University of Sydney, Sydney, NSW 2006, Australia
| | - Nehmat Houssami
- Screening & Test Evaluation Program (STEP), The University of Sydney, Sydney, NSW 2006, Australia
| | - Kirsten McCaffery
- Screening & Test Evaluation Program (STEP), The University of Sydney, Sydney, NSW 2006, Australia; Centre for Medical Psychology & Evidence-based Decision-making (CeMPED), The University of Sydney, Sydney, NSW 2006, Australia.
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Bell K, McCaffery KJ, Irwig L. Screening tests for gonorrhoea should first do no harm. Med J Aust 2015; 202:281-2. [DOI: 10.5694/mja15.00067] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2015] [Accepted: 03/09/2015] [Indexed: 11/17/2022]
Affiliation(s)
- Katy Bell
- Bond University, Gold Coast, QLD
- University of Sydney, Sydney, NSW
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50
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Affiliation(s)
- Katy J L Bell
- Centre for Research in Evidence Based Practice, Bond University, QLD 4229, Australia
| | | | - Paul Glasziou
- Centre for Research in Evidence Based Practice, Bond University, QLD 4229, Australia
| | - Les Irwig
- Screening and Test Evaluation Program, School of Public Health, University of Sydney, Australia
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