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Kennedy J, Alexander P, Taillie LS, Jaacks LM. Estimated effects of reductions in processed meat consumption and unprocessed red meat consumption on occurrences of type 2 diabetes, cardiovascular disease, colorectal cancer, and mortality in the USA: a microsimulation study. Lancet Planet Health 2024; 8:e441-e451. [PMID: 38969472 DOI: 10.1016/s2542-5196(24)00118-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2023] [Revised: 05/03/2024] [Accepted: 05/14/2024] [Indexed: 07/07/2024]
Abstract
BACKGROUND High consumption of processed meat and unprocessed red meat is associated with increased risk of multiple chronic diseases, although there is substantial uncertainty regarding the relationship for unprocessed red meat. We developed a microsimulation model to estimate how reductions in processed meat and unprocessed red meat consumption could affect rates of type 2 diabetes, cardiovascular disease, colorectal cancer, and mortality in the US adult population. METHODS We used data from two versions of the US National Health and Nutrition Examination Survey, one conducted during 2015-16 and one conducted during 2017-18, to create a simulated US population. The starting cohort was restricted to respondents aged 18 years or older who were not pregnant and had 2 days of dietary-recall data. First, we used previously developed risk models to estimate the baseline disease risk of an individual. For type 2 diabetes we used a logistic-regression model and for cardiovascular disease and colorectal cancer we used Cox proportional-hazard models. We then multiplied baseline risk by relative risk associated with individual processed meat and unprocessed red meat consumption. Prevented occurrences of type 2 diabetes, cardiovascular disease, colorectal cancer, and mortality were computed by taking the difference between the incidence in the baseline and intervention scenarios. All stages were repeated for ten iterations to correspond to a 10-year time span. Scenarios were reductions of 5%, 10%, 30%, 50%, 75%, and 100% in grams consumed of processed meat, unprocessed red meat, or both. Each scenario was repeated 50 times for uncertainty analysis. FINDINGS The total number of individual respondents included in the simulated population was 8665, representing 242 021 876 US adults. 4493 (51·9%) of 8665 individuals were female and 4172 (48·1%) were male; mean age was 49·54 years (SD 18·38). At baseline, weighted mean daily consumption of processed meat was 29·1 g, with a 30% reduction being 8·7 g per day, and of unprocessed red meat was 46·7 g, with a 30% reduction being 14·0 g per day. We estimated that a 30% reduction in processed meat intake alone could lead to 352 900 (95% uncertainty interval 345 500-359 900) fewer occurrences of type 2 diabetes, 92 500 (85 600-99 900) fewer occurrences of cardiovascular disease, 53 300 (51 400-55 000) fewer occurrences of colorectal cancer, and 16 700 (15 300-17 700) fewer all-cause deaths during the 10-year period. A 30% reduction in unprocessed red meat intake alone could lead to 732 600 (725 700-740 400) fewer occurrences of type 2 diabetes, 291 500 (283 900-298 800) fewer occurrences of cardiovascular disease, 32 200 (31 500-32 700) fewer occurrences of colorectal cancer, and 46 100 (45 300-47 200) fewer all-cause deaths during the 10-year period. A 30% reduction in both processed meat and unprocessed red meat intake could lead to 1 073 400 (1 060 100-1 084 700) fewer occurrences of type 2 diabetes, 382 400 (372 100-391 000) fewer occurrences of cardiovascular disease, 84 400 (82 100-86 200) fewer occurrences of colorectal cancer, and 62 200 (60 600-64 400) fewer all-cause deaths during the 10-year period. INTERPRETATION Reductions in processed meat consumption could reduce the burden of some chronic diseases in the USA. However, more research is needed to increase certainty in the estimated effects of reducing unprocessed red meat consumption. FUNDING The Wellcome Trust.
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Affiliation(s)
- Joe Kennedy
- Global Academy of Agriculture and Food Systems, University of Edinburgh, Edinburgh, UK.
| | - Peter Alexander
- Global Academy of Agriculture and Food Systems, University of Edinburgh, Edinburgh, UK; School of Geosciences, University of Edinburgh, Edinburgh, UK
| | - Lindsey Smith Taillie
- Carolina Population Center, Department of Nutrition, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
| | - Lindsay M Jaacks
- Global Academy of Agriculture and Food Systems, University of Edinburgh, Edinburgh, UK
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Basu S, Yudkin JS, Jawad M, Ghattas H, Hamad BA, Jamaluddine Z, Safadi G, Ragi ME, Ahmad RES, Vamos EP, Millett C. Reducing non-communicable diseases among Palestinian populations in Gaza: A participatory comparative and cost-effectiveness modeling assessment. PLOS GLOBAL PUBLIC HEALTH 2024; 4:e0003168. [PMID: 38696423 PMCID: PMC11065248 DOI: 10.1371/journal.pgph.0003168] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/20/2023] [Accepted: 04/02/2024] [Indexed: 05/04/2024]
Abstract
We sought to assess the effectiveness and cost-effectiveness of potential new public health and healthcare NCD risk reduction efforts among Palestinians in Gaza. We created a microsimulation model using: (i) a cross-sectional household survey of NCD risk factors among 4,576 Palestinian adults aged ≥40 years old in Gaza; (ii) a modified Delphi process among local public health experts to identify potentially feasible new interventions; and (iii) reviews of intervention cost and effectiveness, modified to the Gazan and refugee contexts. The survey revealed 28.6% tobacco smoking, a 40.4% prevalence of hypertension diagnosis (with a 95.6% medication treatment rate), a 25.6% prevalence of diabetes diagnosis (with 95.3% on treatment), a 21.9% prevalence of dyslipidemia (with 79.6% on a statin), and a 9.8% prevalence of asthma or chronic obstructive pulmonary disease (without known treatment). A calibrated model estimated a loss of 9,516 DALYs per 10,000 population over the 10-year policy horizon. The interventions having an incremental cost-effectiveness ratio (ICER) less than three times the GDP per capita of Palestine per DALY averted (<$10,992 per DALY averted)(<$10,992 per DALY averted) included bans on tobacco smoking in indoor and public places [$34 per incremental DALY averted (95% CI: $17, $50)], treatment of asthma using low dose inhaled beclometasone and short-acting beta-agonists [$140 per DALY averted (95% CI: $77, $207)], treatment of breast cancer stages I and II [$730 per DALY averted (95% CI: $372, $1,100)], implementing a mass media campaign for healthier nutrition [$737 per DALY averted (95% CI: $403, $1,100)], treatment of colorectal cancer stages I and II [$7,657 per DALY averted (95% CI: $3,721, $11,639)], and (screening with mammography [$17,054 per DALY averted (95% CI: $8,693, $25,359)]). Despite high levels of NCD risk factors among Palestinians in Gaza, we estimated that several interventions would be expected to reduce the loss of DALYs within common cost-effectiveness thresholds.
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Affiliation(s)
- Sanjay Basu
- Center for Vulnerable Populations, University of California San Francisco, San Francisco, California, United States of America
- Institute of Health Policy, Management & Evaluation, University of Toronto, Toronto, Canada
| | - John S. Yudkin
- Division of Medicine, Institute of Cardiovascular Science, University College London, London, United Kingdom
| | - Mohammed Jawad
- Public Health Policy Evaluation Unit, School of Public Health, Imperial College London, London, United Kingdom
| | - Hala Ghattas
- Center for Research on Population and Health, American University of Beirut, Beirut, Lebanon
- Arnold School of Public Health, University of South Carolina, Columbia, South Carolina, United States of America
| | | | - Zeina Jamaluddine
- Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, United Kingdom
| | - Gloria Safadi
- Center for Research on Population and Health, American University of Beirut, Beirut, Lebanon
| | - Marie-Elizabeth Ragi
- Center for Research on Population and Health, American University of Beirut, Beirut, Lebanon
| | - Raeda El Sayed Ahmad
- Center for Research on Population and Health, American University of Beirut, Beirut, Lebanon
| | - Eszter P. Vamos
- Public Health Policy Evaluation Unit, School of Public Health, Imperial College London, London, United Kingdom
| | - Christopher Millett
- Public Health Policy Evaluation Unit, School of Public Health, Imperial College London, London, United Kingdom
- National School of Public Health, Public Health Research Centre, Comprehensive Health Research Center, NOVA University Lisbon, Lisbon, Portugal
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Mertens E, Keuchkarian M, Vasquez MS, Vandevijvere S, Peñalvo JL. Lifestyle predictors of colorectal cancer in European populations: a systematic review. BMJ Nutr Prev Health 2024; 7:183-190. [PMID: 38966096 PMCID: PMC11221299 DOI: 10.1136/bmjnph-2022-000554] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2022] [Accepted: 10/10/2023] [Indexed: 07/06/2024] Open
Abstract
Background Colorectal cancer (CRC) is the second most prevalent cancer in Europe, with one-fifth of cases attributable to unhealthy lifestyles. Risk prediction models for quantifying CRC risk and identifying high-risk groups have been developed or validated across European populations, some considering lifestyle as a predictor. Purpose To identify lifestyle predictors considered in existing risk prediction models applicable for European populations and characterise their corresponding parameter values for an improved understanding of their relative contribution to prediction across different models. Methods A systematic review was conducted in PubMed and Web of Science from January 2000 to August 2021. Risk prediction models were included if (1) developed and/or validated in an adult asymptomatic European population, (2) based on non-invasively measured predictors and (3) reported mean estimates and uncertainty for predictors included. To facilitate comparison, model-specific lifestyle predictors were visualised using forest plots. Results A total of 21 risk prediction models for CRC (reported in 16 studies) were eligible, of which 11 were validated in a European adult population but developed elsewhere, mostly USA. All models but two reported at least one lifestyle factor as predictor. Of the lifestyle factors, the most common predictors were body mass index (BMI) and smoking (each present in 13 models), followed by alcohol (11), and physical activity (7), while diet-related factors were less considered with the most commonly present meat (9), vegetables (5) or dairy (2). The independent predictive contribution was generally greater when they were collected with greater detail, although a noticeable variation in effect size estimates for BMI, smoking and alcohol. Conclusions Early identification of high-risk groups based on lifestyle data offers the potential to encourage participation in lifestyle change and screening programmes, hence reduce CRC burden. We propose the commonly shared lifestyle predictors to be further used in public health prediction modelling for improved uptake of the model.
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Affiliation(s)
- Elly Mertens
- Unit of Non-Comunicable Diseases, Department of Public Health, Institute of Tropical Medicine, Antwerp, Belgium
| | - Maria Keuchkarian
- Unit of Non-Comunicable Diseases, Department of Public Health, Institute of Tropical Medicine, Antwerp, Belgium
- Faculty of Bioscience Engineering, Ghent University, Gent, Belgium
| | | | | | - José L Peñalvo
- Unit of Non-Comunicable Diseases, Department of Public Health, Institute of Tropical Medicine, Antwerp, Belgium
- Global Health Institute, University of Antwerp, Wilrijk, Belgium
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Hampton JS, Kenny RP, Rees CJ, Hamilton W, Eastaugh C, Richmond C, Sharp L. The performance of FIT-based and other risk prediction models for colorectal neoplasia in symptomatic patients: a systematic review. EClinicalMedicine 2023; 64:102204. [PMID: 37781155 PMCID: PMC10541467 DOI: 10.1016/j.eclinm.2023.102204] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/22/2023] [Revised: 08/21/2023] [Accepted: 08/28/2023] [Indexed: 10/03/2023] Open
Abstract
Background Colorectal cancer (CRC) incidence and mortality are increasing internationally. Endoscopy services are under significant pressure with many overwhelmed. Faecal immunochemical testing (FIT) has been advocated to identify a high-risk population of symptomatic patients requiring definitive investigation by colonoscopy. Combining FIT with other factors in a risk prediction model could further improve performance in identifying those requiring investigation most urgently. We systematically reviewed performance of models predicting risk of CRC and/or advanced colorectal polyps (ACP) in symptomatic patients, with a particular focus on those models including FIT. Methods The review protocol was published on PROSPERO (CRD42022314710). Searches were conducted from database inception to April 2023 in MEDLINE, EMBASE, Cochrane libraries, SCOPUS and CINAHL. Risk of bias of each study was assessed using The Prediction study Risk Of Bias Assessment Tool. A narrative synthesis based on the guidelines for Synthesis Without Meta-Analysis was performed due to study heterogeneity. Findings We included 62 studies; 23 included FIT (n = 22) or guaiac Faecal Occult Blood Testing (n = 1) combined with one or more other variables. Twenty-one studies were conducted solely in primary care. Generally, prediction models including FIT consistently had good discriminatory ability for CRC/ACP (i.e. AUC >0.8) and performed better than models without FIT although some models without FIT also performed well. However, many studies did not present calibration and internal and external validation were limited. Two studies were rated as low risk of bias; neither model included FIT. Interpretation Risk prediction models, including and not including FIT, show promise for identifying those most at risk of colorectal neoplasia. Substantial limitations in evidence remain, including heterogeneity, high risk of bias, and lack of external validation. Further evaluation in studies adhering to gold standard methodology, in appropriate populations, is required before widespread adoption in clinical practice. Funding National Institute for Health and Care Research (NIHR) [Health Technology Assessment Programme (HTA) Programme (Project number 133852).
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Affiliation(s)
- James S. Hampton
- Population Health Sciences Institute, Newcastle University, United Kingdom
- Department of Gastroenterology, South Tyneside and Sunderland NHS Foundation Trust, United Kingdom
| | - Ryan P.W. Kenny
- Evidence Synthesis Group, The Catalyst, Population Health Sciences Institute, Newcastle University, United Kingdom
- National Institute for Health and Care Research Innovation Observatory, The Catalyst, Newcastle University, United Kingdom
| | - Colin J. Rees
- Population Health Sciences Institute, Newcastle University, United Kingdom
- Department of Gastroenterology, South Tyneside and Sunderland NHS Foundation Trust, United Kingdom
| | - William Hamilton
- College of Medicine and Health, University of Exeter, United Kingdom
| | - Claire Eastaugh
- Evidence Synthesis Group, The Catalyst, Population Health Sciences Institute, Newcastle University, United Kingdom
- National Institute for Health and Care Research Innovation Observatory, The Catalyst, Newcastle University, United Kingdom
| | - Catherine Richmond
- Evidence Synthesis Group, The Catalyst, Population Health Sciences Institute, Newcastle University, United Kingdom
- National Institute for Health and Care Research Innovation Observatory, The Catalyst, Newcastle University, United Kingdom
| | - Linda Sharp
- Population Health Sciences Institute, Newcastle University, United Kingdom
| | - COLOFIT Research Team
- Population Health Sciences Institute, Newcastle University, United Kingdom
- Department of Gastroenterology, South Tyneside and Sunderland NHS Foundation Trust, United Kingdom
- Evidence Synthesis Group, The Catalyst, Population Health Sciences Institute, Newcastle University, United Kingdom
- National Institute for Health and Care Research Innovation Observatory, The Catalyst, Newcastle University, United Kingdom
- College of Medicine and Health, University of Exeter, United Kingdom
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The risk of developing colorectal cancer in individuals aged 50-70 years and behavioral changes in high-risk individuals regarding a fecal occult blood test. JOURNAL OF SURGERY AND MEDICINE 2022. [DOI: 10.28982/josam.868951] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022] Open
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A user-friendly objective prediction model in predicting colorectal cancer based on 234 044 Asian adults in a prospective cohort. ESMO Open 2021; 6:100288. [PMID: 34808523 PMCID: PMC8609147 DOI: 10.1016/j.esmoop.2021.100288] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2021] [Revised: 09/08/2021] [Accepted: 09/27/2021] [Indexed: 11/20/2022] Open
Abstract
BACKGROUND Prediction models of colorectal cancer (CRC) had limited application for not being user-friendly. Whether fecal immunochemical tests (FITs) can help predict CRC has been overlooked. PATIENTS AND METHODS With 1972 CRCs identified, 234 044 adults aged ≥40 years were successively enrolled between 1994 and 2008. Prediction models were developed by questionnaire/medical screening and quantitative FIT. NNS (number needed to scope to find one cancer) is time dependent, spanning entire study period. Significant 'risk factors' were family history, body mass index, smoking, drinking, inactivity, hypertension, diabetes, carcinoembryonic antigen, and C-reactive protein. RESULTS Positive FIT (≥20 μg/g hemoglobin/feces) had cancer risk 10-fold larger than negative FIT, and within each age group, another 10-fold difference. The C statistic of FIT (0.81) with age and sex alone was superior to the 'common risk-factors' model (0.73). NNS, stratified by age and by FIT values, demonstrated a scorecard of cancer risks, like 1/15 or 1/25, in 5 years. When FIT was negative, cancer risk was small (1/750-1/3000 annually). The larger the FIT, the sooner the appearance of CRC. For every 80-μg/g increase of FIT, there were 1.5-year earlier development of CRC incidence and 1-year earlier development of CRC mortality, respectively. Given the same FIT value, CRC events appeared in the proximal colon sooner than the distal colon. CONCLUSIONS A simple user-friendly model based on a single FIT value to predict CRC risk was developed. When positive, NNS offered a simple quantitative value, with a better precision than most risk factors, even combined. When FIT is negative, risk is very small, but requiring a repeat every other year to rule out false negative. FIT values correlated well with CRC prognosis, with worst for proximal CRC.
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7
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Luu XQ, Lee K, Kim J, Sohn DK, Shin A, Choi KS. The classification capability of the Asia Pacific Colorectal Screening score in Korea: an analysis of the Cancer Screenee Cohort. Epidemiol Health 2021; 43:e2021069. [PMID: 34607403 PMCID: PMC8654505 DOI: 10.4178/epih.e2021069] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2021] [Accepted: 09/16/2021] [Indexed: 11/09/2022] Open
Abstract
OBJECTIVES This study aimed to validate a simple risk assessment tool for estimating the advanced colorectal neoplasia (ACN) risk at colonoscopy screenings and potential factors relevant for implementing this tool in the Korean population. METHODS Our study analyzed data from the Cancer Screenee Cohort Study conducted by the National Cancer Center in Korea. The risk level was assessed using the Asia Pacific Colorectal Screening (APCS) score developed by the Asia-Pacific Working Group on Colorectal Cancer. Logistic regression models were used to examine the associations between colorectal-related outcomes and the risk level by APCS score. The discriminatory performance of the APCS score for various colorectal-related outcomes was assessed using C-statistics. RESULTS In 12,520 individuals, 317 ACN cases and 4,528 adenoma cases were found. The APCS tool successfully classified the study population into different risk groups, and significant differences in the ACN rate and other outcomes were observed. The APCS score demonstrated acceptable discrimination capability with area under the curve values ranging from 0.62 to 0.65 for various outcomes. The results of the multivariate logistic regression model revealed that the high-risk group had a 3.1-fold higher risk of ACN (95% confidence interval, 2.08 to 4.67) than the average-risk group. Body mass index (BMI) was identified as a significant predictor of ACN in both multivariate and subgroup analyses. CONCLUSIONS Our study highlighted significant differences in colorectal-related screening outcomes by colorectal risk level measured using the APCS score, and BMI could be used to improve the discriminatory capability of the APCS score.
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Affiliation(s)
- Xuan Quy Luu
- Department of Cancer Control and Population Health, Graduate School of Cancer Science and Policy, National Cancer Center, Goyang, Korea
| | - Kyeongmin Lee
- Department of Cancer Control and Population Health, Graduate School of Cancer Science and Policy, National Cancer Center, Goyang, Korea
| | - Jeongseon Kim
- Department of Cancer Biomedical Science, Graduate School of Cancer Science and Policy, National Cancer Center, Goyang, Korea
| | - Dae Kyung Sohn
- Department of Cancer Control and Population Health, Graduate School of Cancer Science and Policy, National Cancer Center, Goyang, Korea.,Center for Colorectal Cancer, Research Institute and Hospital, National Cancer Center, Goyang, Korea
| | - Aesun Shin
- Department of Preventive Medicine, Seoul National University College of Medicine, Seoul, Korea
| | - Kui Son Choi
- Department of Cancer Control and Population Health, Graduate School of Cancer Science and Policy, National Cancer Center, Goyang, Korea
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Reddy S, Mouchli A, Bierle L, Gerrard M, Walsh C, Mir A, Lebel DP, Mason C, Grider D, Rubio M. Assessing Presenting Symptoms, Co-Morbidities, and Risk Factors for Mortality in Underserved Patients With Non-Hereditary Early-Onset Colorectal Cancer. Cureus 2021; 13:e16117. [PMID: 34350080 PMCID: PMC8325966 DOI: 10.7759/cureus.16117] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/21/2021] [Indexed: 12/27/2022] Open
Abstract
Background The presenting symptoms and co-morbidities contributing to mortality in young patients (age < 50 years old) with colorectal cancer (CRC) are poorly understood. We reviewed these features in our patient population with non-hereditary early-onset CRC (EO-CRC). Study aim This study aimed to assess characteristics of patients with a diagnosis of non-hereditary EO-CRC, including presenting symptoms and metabolic disorders contributing to mortality in underserved areas of southwest Virginia. Methods In this retrospective observational study, we selected patients aged 18-50 years with a diagnosis of non-hereditary EO-CRC from 2008 to 2016 at Carilion Roanoke Memorial Hospital. The electronic medical record was queried to identify demographic data, medical history, histopathology results, lab values, and mortality. The cumulative risks of symptoms and co-morbid metabolic disorders was estimated using Kaplan-Meier curves. Results We identified 139 patients with non-hereditary EO-CRC (mean age 41.6 ± 6.9 years). Almost half of these patients were obese (BMI > 30), 30.9% had a diagnosis of hypertension, 29% had hyperlipidemia (HLD), and 17.35% had diabetes mellitus type 2 (DM2). Diagnosis was delayed by 4.5 months from initial presentation, and 17% had advanced disease (stage III/IV). Also, 68.5% of patients were symptomatic with one to three symptoms, most commonly with rectal bleeding (45.3%). The chronicity of HLD (≥5 years) was associated with reduced survival in our patients with EO-CRC. The survival of females with multiple metabolic disorders was reduced compared to females with a single metabolic disorder. Conclusions Multiple symptoms, chronic HLD, and female gender with multiple metabolic disorders were factors associated with poor outcomes in non-hereditary EO-CRC patients.
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Affiliation(s)
| | - Awf Mouchli
- Gastroenterology, Cleveland Clinic, Cleveland, USA
| | | | - Miranda Gerrard
- Medical Student, Internal Medicine, Virginia Tech Carilion School of Medicine, Roanoke, USA
| | | | - Adil Mir
- Internal Medicine, Carilion Clinic, Roanoke, USA
| | - David P Lebel
- Pathology, Virginia Tech Carilion School of Medicine, Roanoke, USA
| | | | - Douglas Grider
- Pathology, Carilion Roanoke Memorial Hospital, Roanoke, USA
- Basic Science Education, Virginia Tech Carilion School of Medicine, Roanoke, USA
| | - Marrieth Rubio
- Gastroenterology and Hepatology, Virginia Tech Carilion School of Medicine, Roanoke, USA
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Semedo L, Lifford KJ, Edwards A, Seddon K, Brain K, Smits S, Dolwani S. Development and user-testing of a brief decision aid for aspirin as a preventive approach alongside colorectal cancer screening. BMC Med Inform Decis Mak 2021; 21:165. [PMID: 34016116 PMCID: PMC8139147 DOI: 10.1186/s12911-021-01523-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2020] [Accepted: 05/09/2021] [Indexed: 01/22/2023] Open
Abstract
BACKGROUND Several epidemiological and cohort studies suggest that regular low-dose aspirin use independently reduces the long-term incidence and risk of colorectal cancer deaths by approximately 20%. However, there are also risks to aspirin use, mainly gastrointestinal bleeding and haemorrhagic stroke. Making informed decisions depends on the ability to understand and weigh up benefits and risks of available options. A decision aid to support people to consider aspirin therapy alongside participation in the NHS bowel cancer screening programme may have an additional impact on colorectal cancer prevention. This study aims to develop and user-test a brief decision aid about aspirin to enable informed decision-making for colorectal screening-eligible members of the public. METHODS We undertook a qualitative study to develop an aspirin decision aid leaflet to support bowel screening responders in deciding whether to take aspirin to reduce their risk of colorectal cancer. The iterative development process involved two focus groups with public members aged 60-74 years (n = 14) and interviews with clinicians (n = 10). Interviews (n = 11) were used to evaluate its utility for decision-making. Analysis was conducted using a framework approach. RESULTS Overall, participants found the decision aid acceptable and useful to facilitate decision-making. They expressed a need for individualised risk information, more detail about the potential risks of aspirin, and preferred risk information presented in pictograms when offered different options. Implementation pathways were discussed, including the possibility of involving different clinicians in the process such as GPs and/or community pharmacists. A range of potentially effective timepoints for sending out the decision aid were identified. CONCLUSION An acceptable and usable decision aid was developed to support decisions about aspirin use to prevent colorectal cancer.
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Affiliation(s)
- Lenira Semedo
- Division of Population Medicine, Cardiff University, Cardiff, UK
| | - Kate J Lifford
- Division of Population Medicine, Cardiff University, Cardiff, UK
| | - Adrian Edwards
- Division of Population Medicine, Cardiff University, Cardiff, UK
| | - Kathy Seddon
- Division of Population Medicine, Cardiff University, Cardiff, UK
| | - Kate Brain
- Division of Population Medicine, Cardiff University, Cardiff, UK
| | - Stephanie Smits
- Division of Population Medicine, Cardiff University, Cardiff, UK
| | - Sunil Dolwani
- Division of Population Medicine, Cardiff University, Cardiff, UK.
- Department of Gastroenterology, University Hospital Llandough, Penlan Road, Penarth, Cardiff, CF64 2XX, UK.
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Fang Z, Hang D, Wang K, Joshi A, Wu K, Chan AT, Ogino S, Giovannucci EL, Song M. Risk prediction models for colorectal cancer: Evaluating the discrimination due to added biomarkers. Int J Cancer 2021; 149:1021-1030. [PMID: 33948940 DOI: 10.1002/ijc.33621] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2021] [Revised: 04/07/2021] [Accepted: 04/20/2021] [Indexed: 02/05/2023]
Abstract
Most risk prediction models for colorectal cancer (CRC) are based on questionnaires and show a modest discriminatory ability. Therefore, we aim to develop risk prediction models incorporating plasma biomarkers for CRC to improve discrimination. We assessed the predictivity of 11 biomarkers in 736 men in the Health Professionals Follow-up Study and 639 women in the Nurses' Health Study. We used stepwise logistic regression to examine whether a set of biomarkers improved the predictivity on the basis of predictors in the National Cancer Institute's (NCI) Colorectal Cancer Risk Assessment Tool. Model discrimination was assessed using C-statistics. Bootstrap with 500 randomly sampled replicates was used for internal validation. The models containing each biomarker generated a C-statistic ranging from 0.50 to 0.59 in men and 0.50 to 0.54 in women. The NCI model demonstrated a C-statistic (95% CI) of 0.67 (0.62-0.71) in men and 0.58 (0.54-0.63) in women. Through stepwise selection of biomarkers, the C-statistic increased to 0.70 (0.66-0.74) in men after adding growth/differentiation factor 15, total adiponectin, sex hormone binding globulin and tumor necrosis factor receptor superfamily member 1B (P for difference = 0.008); and increased to 0.62 (0.57-0.66) in women after further including insulin-like growth factor 1 and insulin-like growth factor-binding protein 3 (P for difference = .06). The NCI + selected biomarkers model was internally validated with a C-statistic (95% CI) of 0.73 (0.70-0.77) in men and 0.66 (0.61-0.70) in women. Circulating plasma biomarkers may improve the performance of risk factor-based prediction model for CRC.
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Affiliation(s)
- Zhe Fang
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
| | - Dong Hang
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.,Department of Epidemiology and Biostatistics, Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Kai Wang
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
| | - Amit Joshi
- Clinical and Translational Epidemiology Unit, Mongan Institute, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Kana Wu
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
| | - Andrew T Chan
- Clinical and Translational Epidemiology Unit, Mongan Institute, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA.,Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA.,Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA.,Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
| | - Shuji Ogino
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.,Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.,Program in MPE Molecular Pathological Epidemiology, Department of Pathology, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Edward L Giovannucci
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.,Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.,Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Mingyang Song
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.,Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.,Clinical and Translational Epidemiology Unit, Mongan Institute, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA.,Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
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11
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Aleshin-Guendel S, Lange J, Goodman P, Weiss NS, Etzioni R. A Latent Disease Model to Reduce Detection Bias in Cancer Risk Prediction Studies. Eval Health Prof 2021; 44:42-49. [PMID: 33506704 PMCID: PMC8279086 DOI: 10.1177/0163278720984203] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
In studies of cancer risk, detection bias arises when risk factors are associated with screening patterns, affecting the likelihood and timing of diagnosis. To eliminate detection bias in a screened cohort, we propose modeling the latent onset of cancer and estimating the association between risk factors and onset rather than diagnosis. We apply this framework to estimate the increase in prostate cancer risk associated with black race and family history using data from the SELECT prostate cancer prevention trial, in which men were screened and biopsied according to community practices. A positive family history was associated with a hazard ratio (HR) of prostate cancer onset of 1.8, lower than the corresponding HR of prostate cancer diagnosis (HR = 2.2). This result comports with a finding that men in SELECT with a family history were more likely to be biopsied following a positive PSA test than men with no family history. For black race, the HRs for onset and diagnosis were similar, consistent with similar patterns of screening and biopsy by race. If individual screening and diagnosis histories are available, latent disease modeling can be used to decouple risk of disease from risk of disease diagnosis and reduce detection bias.
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Affiliation(s)
| | - Jane Lange
- Fred Hutchinson Cancer Research Center, Seattle, WA
| | | | - Noel S Weiss
- Fred Hutchinson Cancer Research Center, Seattle, WA
- University of Washington, Department of Epidemiology
| | - Ruth Etzioni
- University of Washington, Department of Biostatistics, Seattle, WA
- Fred Hutchinson Cancer Research Center, Seattle, WA
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12
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Aleksandrova K, Reichmann R, Kaaks R, Jenab M, Bueno-de-Mesquita HB, Dahm CC, Eriksen AK, Tjønneland A, Artaud F, Boutron-Ruault MC, Severi G, Hüsing A, Trichopoulou A, Karakatsani A, Peppa E, Panico S, Masala G, Grioni S, Sacerdote C, Tumino R, Elias SG, May AM, Borch KB, Sandanger TM, Skeie G, Sánchez MJ, Huerta JM, Sala N, Gurrea AB, Quirós JR, Amiano P, Berntsson J, Drake I, van Guelpen B, Harlid S, Key T, Weiderpass E, Aglago EK, Cross AJ, Tsilidis KK, Riboli E, Gunter MJ. Development and validation of a lifestyle-based model for colorectal cancer risk prediction: the LiFeCRC score. BMC Med 2021; 19:1. [PMID: 33390155 PMCID: PMC7780676 DOI: 10.1186/s12916-020-01826-0] [Citation(s) in RCA: 49] [Impact Index Per Article: 16.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/19/2020] [Accepted: 10/23/2020] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND Nutrition and lifestyle have been long established as risk factors for colorectal cancer (CRC). Modifiable lifestyle behaviours bear potential to minimize long-term CRC risk; however, translation of lifestyle information into individualized CRC risk assessment has not been implemented. Lifestyle-based risk models may aid the identification of high-risk individuals, guide referral to screening and motivate behaviour change. We therefore developed and validated a lifestyle-based CRC risk prediction algorithm in an asymptomatic European population. METHODS The model was based on data from 255,482 participants in the European Prospective Investigation into Cancer and Nutrition (EPIC) study aged 19 to 70 years who were free of cancer at study baseline (1992-2000) and were followed up to 31 September 2010. The model was validated in a sample comprising 74,403 participants selected among five EPIC centres. Over a median follow-up time of 15 years, there were 3645 and 981 colorectal cancer cases in the derivation and validation samples, respectively. Variable selection algorithms in Cox proportional hazard regression and random survival forest (RSF) were used to identify the best predictors among plausible predictor variables. Measures of discrimination and calibration were calculated in derivation and validation samples. To facilitate model communication, a nomogram and a web-based application were developed. RESULTS The final selection model included age, waist circumference, height, smoking, alcohol consumption, physical activity, vegetables, dairy products, processed meat, and sugar and confectionary. The risk score demonstrated good discrimination overall and in sex-specific models. Harrell's C-index was 0.710 in the derivation cohort and 0.714 in the validation cohort. The model was well calibrated and showed strong agreement between predicted and observed risk. Random survival forest analysis suggested high model robustness. Beyond age, lifestyle data led to improved model performance overall (continuous net reclassification improvement = 0.307 (95% CI 0.264-0.352)), and especially for young individuals below 45 years (continuous net reclassification improvement = 0.364 (95% CI 0.084-0.575)). CONCLUSIONS LiFeCRC score based on age and lifestyle data accurately identifies individuals at risk for incident colorectal cancer in European populations and could contribute to improved prevention through motivating lifestyle change at an individual level.
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Affiliation(s)
- Krasimira Aleksandrova
- Nutrition, Immunity and Metabolism Senior Scientist Group, Department of Nutrition and Gerontology, German Institute of Human Nutrition Potsdam-Rehbruecke (DIfE), Nuthetal, Germany.
- Institute of Nutritional Science, University of Potsdam, Potsdam, Germany.
- Department of Epidemiological Methods and Etiological Research, Leibniz Institute for Prevention Research and Epidemiology - BIPS, Bremen, Germany.
| | - Robin Reichmann
- Nutrition, Immunity and Metabolism Senior Scientist Group, Department of Nutrition and Gerontology, German Institute of Human Nutrition Potsdam-Rehbruecke (DIfE), Nuthetal, Germany
- Institute of Nutritional Science, University of Potsdam, Potsdam, Germany
| | - Rudolf Kaaks
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Mazda Jenab
- International Agency for Research on Cancer, World Health Organization, Lyon, France
| | - H Bas Bueno-de-Mesquita
- National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | | | | | | | - Fanny Artaud
- CESP, Faculté de Medicine, Université Paris-Saclay, Villejuif, France
- Institut Gustave Roussy, Villejuif, France
| | | | - Gianluca Severi
- CESP, Faculté de Medicine, Université Paris-Saclay, Villejuif, France
- Institut Gustave Roussy, Villejuif, France
- Dipartimento di Statistica, Informatica e Applicazioni "G. Parenti" (DISIA), University of Florence, Florence, Italy
| | - Anika Hüsing
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | | | - Anna Karakatsani
- Hellenic Health Foundation, Athens, Greece
- 2nd Pulmonary Medicine Department, School of Medicine, National and Kapodistrian University of Athens, "ATTIKON" University Hospital, Haidari, Greece
| | | | - Salvatore Panico
- EPIC Centre of Naples, Dipartimento di Medicina Clinica e Chirurgia, University of Naples Federico II, Naples, Italy
| | - Giovanna Masala
- Cancer Risk Factors and Lifestyle Epidemiology Unit, Institute for Cancer Research, Prevention and Clinical Network - ISPRO, Florence, Italy
| | - Sara Grioni
- Epidemiology and Prevention Unit, Fondazione IRCCS Istituto Nazionale dei Tumori di Milano, Milan, Italy
| | - Carlotta Sacerdote
- Unit of Cancer Epidemiology, Città della Salute e della Scienza University-Hospital and Center for Cancer Prevention (CPO), Turin, Italy
| | - Rosario Tumino
- Cancer Registry and Histopathology Department, Provincial Health Authority (ASP), Ragusa, Italy
| | - Sjoerd G Elias
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Anne M May
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Kristin B Borch
- Department of Community Medicine, Health Faculty, UiT-the Arctic university of Norway, Tromsø, Norway
| | - Torkjel M Sandanger
- Department of Community Medicine, Health Faculty, UiT-the Arctic university of Norway, Tromsø, Norway
| | - Guri Skeie
- Department of Community Medicine, Health Faculty, UiT-the Arctic university of Norway, Tromsø, Norway
| | - Maria-Jose Sánchez
- Escuela Andaluza de Salud Pública (EASP), Granada, Spain
- Instituto de Investigación Biosanitaria ibs. GRANADA, Granada, Spain
- Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
- Universidad de Granada, Granada, Spain
| | - José María Huerta
- Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
- Department of Epidemiology, Murcia Regional Health Council, IMIB-Arrixaca, Murcia, Spain
| | - Núria Sala
- Unit of Nutrition and Cancer, Cancer Epidemiology Research Program, Translational Research Laboratory, Catalan Institute of Oncology (ICO), Barcelona, Spain
- Bellvitge Biomedical Research Institute (IDIBELL), Barcelona, Spain
| | - Aurelio Barricarte Gurrea
- Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
- Navarra Public Health Institute, Pamplona, Spain
- Navarra Institute for Health Research (IdiSNA), Pamplona, Spain
| | | | - Pilar Amiano
- Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
- Ministry of Health of the Basque Government, Public Health Division of Gipuzkoa, Biodonostia Health Research Institute, Donostia-San Sebastian, Spain
| | - Jonna Berntsson
- Department of Clinical Sciences, Division of Oncology and Pathology, Lund University, Lund, Sweden
| | - Isabel Drake
- Department of Clinical Sciences in Malmö, Lund University, Lund, Sweden
| | - Bethany van Guelpen
- Department of Radiation Sciences, Oncology, Umeå University, Umeå, Sweden
- Wallenberg Centre for Molecular Medicine, Umeå University, Umeå, Sweden
| | - Sophia Harlid
- Department of Radiation Sciences, Oncology, Umeå University, Umeå, Sweden
| | - Tim Key
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Elisabete Weiderpass
- International Agency for Research on Cancer, World Health Organization, Lyon, France
| | - Elom K Aglago
- International Agency for Research on Cancer, World Health Organization, Lyon, France
| | - Amanda J Cross
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Konstantinos K Tsilidis
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina, Greece
| | - Elio Riboli
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Marc J Gunter
- International Agency for Research on Cancer, World Health Organization, Lyon, France
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13
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Juchli F, Zangger M, Schueck A, von Wolff M, Stute P. Chronic non-communicable disease risk calculators - An overview, part I. Maturitas 2020; 143:25-35. [PMID: 33308633 DOI: 10.1016/j.maturitas.2020.07.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2020] [Revised: 06/21/2020] [Accepted: 07/28/2020] [Indexed: 11/26/2022]
Abstract
This review identifies the different risk assessment tools that stratify the individual's risk of four of the eight leading causes of death in women: breast cancer, lung cancer, colorectal cancer and osteoporosis. It will be followed by the publication of a second paper that summarizes the risk assessment tools for the other four leading causes of death (myocardial infarction, stroke, diabetes mellitus type 2 and dementia). The different tools were compared by their use of different variables and validation criteria. To corroborate the validation process, validation study papers were considered for each risk assessment tool. Four tables, one for each illness, were designed. The tables provide an outline for each risk assessment tool, which includes its inventor/company, required variables, advantages, disadvantages and validity. These tables simplify the comparison of the different tools and enable the identification of the most suitable one for each patient.
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Affiliation(s)
- Fabienne Juchli
- Department of General Internal Medicine, Muri Hospital, Muri, Switzerland
| | - Martina Zangger
- Department of General Internal Medicine, Thun Hospital, Thun, Switzerland
| | - Andrea Schueck
- Department of Anesthesiology, Lachen Hospital, Lachen, Switzerland
| | - Michael von Wolff
- Department of Obstetrics and Gynecology, University Women's Hospital, Bern, Switzerland
| | - Petra Stute
- Department of Obstetrics and Gynecology, University Women's Hospital, Bern, Switzerland.
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14
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Chen Y, Chen X, Wang X, Liu Z, Zhou H, Xu S. Association of Cardiovascular Risk Assessment with Early Colorectal Neoplasia Detection in Asymptomatic Population: A Systematic Review and Meta-Analysis. Clin Epidemiol 2020; 12:865-873. [PMID: 32848475 PMCID: PMC7429103 DOI: 10.2147/clep.s262939] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2020] [Accepted: 07/19/2020] [Indexed: 12/24/2022] Open
Abstract
Previous studies have shown a strong coexistence of colorectal neoplasia (CRN) and cardiovascular diseases (CVD). This study was aimed to summarize the available evidence on association of CVD risk with early CRN detection in asymptomatic populations. PubMed, Web of Science, and Embase were systematically searched for eligible studies published until Dec 20, 2019. Studies exploring the associations of recommended CVD risk assessment methods (e.g., risk scores, carotid artery plaque, and coronary artery calcium score [CACS]) with risk of CRN were included. Meta-analyses were conducted to determine the overall association of CVD risk with the CRN. A total of 12 studies were finally included. The association of carotid artery plaque with the risk of colorectal adenoma (AD) was weakest (pooled odds ratio [OR)] 1.27, 95% confidence interval [CI), 1.12, 1.45]. Participants with CACS>100 had about 2-fold increased risk of AD than those with CACS=0. The pooled ORs were 3.36 (95% CI, 2.15, 5.27) and 2.30 (95% CI, 1.69, 3.13) for the risk of advanced colorectal neoplasia (AN) and AD, respectively, in participants with Framingham risk score (FRS)>20%, when compared to participants at low risk (FRS<10%). FRS might help identify subgroups at increased risk for AN, but further studies are needed.
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Affiliation(s)
- Yanwei Chen
- Infection Control Department of Shenzhen Hospital of University of Chinese Academy of Sciences, Shenzhen, People’s Republic of China
| | - Xuechen Chen
- Medical Faculty Heidelberg, University of Heidelberg, Heidelberg, Germany
| | - Xi Wang
- Medical Faculty Heidelberg, University of Heidelberg, Heidelberg, Germany
| | - Zhunzhun Liu
- Medical Faculty Heidelberg, University of Heidelberg, Heidelberg, Germany
| | - Haibo Zhou
- Institute of Pharmaceutical Analysis, College of Pharmacy, Jinan University, Guangzhou, People’s Republic of China
| | - Shu Xu
- Oncology Department of Shenzhen Hospital of University of Chinese Academy of Sciences, Shenzhen, People’s Republic of China
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15
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Tian T, Bi H, Liu Y, Li G, Zhang Y, Cao L, Hu F, Zhao Y, Yuan H. Copy number variation of ubiquitin- specific proteases genes in blood leukocytes and colorectal cancer. Cancer Biol Ther 2020; 21:637-646. [PMID: 32364424 PMCID: PMC7515516 DOI: 10.1080/15384047.2020.1750860] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2019] [Revised: 03/12/2020] [Accepted: 03/25/2020] [Indexed: 12/23/2022] Open
Abstract
Ubiquitin-specific proteases (USPs) play important roles in the regulation of many cancer-related biological processes. USPs copy number variation (CNVs) may affect the risk and prognosis of colorectal cancer (CRC). We detected CNVs of USPs genes in 468 matched CRC patients and controls, estimated the associations between the USPs genes CNVs and CRC risk and prognosis and their interactions with environmental factors on CRC risk. Finally, we generated five CRC risk predictive models with different CNVs patterns combining with environmental factors (EF). We identified significant association between CYLD deletion and CRC risk (ORadj = 4.18, 95% CI: 2.03-8.62), significant association between USP9X amplification and CRC risk (ORadj = 2.30, 95% CI: 1.48-3.57), and significant association between USP11 deletion and CRC risk (ORadj = 3.49, 95% CI: 1.49-8.64). There were significant gene-environment and gene-gene interactions on CRC risk. The area under the receiver operating characteristic curve (AUC) of EF + SIG (deletion of CYLD and USP11, amplification of USP9X) model was significantly larger than any other models (AUC = 0.75, 95% CI: 0.74-0.77). We did not identify significant associations between CNVs of the three genes and CRC prognosis. CNVs of CYLD, USP9X, and USP11 are significantly associated with the risk of CRC. Gene-gene and gene-environment interactions might also play an important role in the development of CRC.
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Affiliation(s)
- Tian Tian
- Department of Epidemiology, Public Health College of Harbin Medical University, Harbin, P.R. China
| | - Haoran Bi
- Department of Epidemiology, Public Health College of Harbin Medical University, Harbin, P.R. China
| | - Yupeng Liu
- Department of Epidemiology, Public Health College of Harbin Medical University, Harbin, P.R. China
| | - Guangxiao Li
- Department of Epidemiology, Public Health College of Harbin Medical University, Harbin, P.R. China
| | - Yiwei Zhang
- Department of Epidemiology, Public Health College of Harbin Medical University, Harbin, P.R. China
| | - Liming Cao
- Department of Epidemiology, Public Health College of Harbin Medical University, Harbin, P.R. China
| | - Fulan Hu
- Department of Epidemiology, Public Health College of Harbin Medical University, Harbin, P.R. China
| | - Yashuang Zhao
- Department of Epidemiology, Public Health College of Harbin Medical University, Harbin, P.R. China
| | - Huiping Yuan
- Department of Ophthalmology, The Second Affiliated Hospital of Harbin Medical University, Harbin, P.R. China
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16
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Saunders CL, Kilian B, Thompson DJ, McGeoch LJ, Griffin SJ, Antoniou AC, Emery JD, Walter FM, Dennis J, Yang X, Usher-Smith JA. External Validation of Risk Prediction Models Incorporating Common Genetic Variants for Incident Colorectal Cancer Using UK Biobank. Cancer Prev Res (Phila) 2020; 13:509-520. [PMID: 32071122 PMCID: PMC7610623 DOI: 10.1158/1940-6207.capr-19-0521] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2019] [Revised: 01/15/2020] [Accepted: 02/11/2020] [Indexed: 12/22/2022]
Abstract
The aim of this study was to compare and externally validate risk scores developed to predict incident colorectal cancer that include common genetic variants (SNPs), with or without established lifestyle/environmental (questionnaire-based/classical/phenotypic) risk factors. We externally validated 23 risk models from a previous systematic review in 443,888 participants ages 37 to 73 from the UK Biobank cohort who had 6-year prospective follow-up, no prior history of colorectal cancer, and data for incidence of colorectal cancer through linkage to national cancer registries. There were 2,679 (0.6%) cases of incident colorectal cancer. We assessed model discrimination using the area under the operating characteristic curve (AUC) and relative risk calibration. The AUC of models including only SNPs increased with the number of included SNPs and was similar in men and women: the model by Huyghe with 120 SNPs had the highest AUC of 0.62 [95% confidence interval (CI), 0.59-0.64] in women and 0.64 (95% CI, 0.61-0.66) in men. Adding phenotypic risk factors without age improved discrimination in men but not in women. Adding phenotypic risk factors and age increased discrimination in all cases (P < 0.05), with the best performing models including SNPs, phenotypic risk factors, and age having AUCs between 0.64 and 0.67 in women and 0.67 and 0.71 in men. Relative risk calibration varied substantially across the models. Among middle-aged people in the UK, existing polygenic risk scores discriminate moderately well between those who do and do not develop colorectal cancer over 6 years. Consideration should be given to exploring the feasibility of incorporating genetic and lifestyle/environmental information in any future stratified colorectal cancer screening program.
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Affiliation(s)
- Catherine L Saunders
- The Primary Care Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Britt Kilian
- The Primary Care Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Deborah J Thompson
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, Strangeways Research Laboratory, Wort's Causeway, Cambridge, United Kingdom
| | - Luke J McGeoch
- School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom
| | - Simon J Griffin
- The Primary Care Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Antonis C Antoniou
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, Strangeways Research Laboratory, Wort's Causeway, Cambridge, United Kingdom
| | - Jon D Emery
- Department of General Practice, Centre for Cancer Research, Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Victorian Comprehensive Cancer Centre, Melbourne, Victoria, Australia
| | - Fiona M Walter
- The Primary Care Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Joe Dennis
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, Strangeways Research Laboratory, Wort's Causeway, Cambridge, United Kingdom
| | - Xin Yang
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, Strangeways Research Laboratory, Wort's Causeway, Cambridge, United Kingdom
| | - Juliet A Usher-Smith
- The Primary Care Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom.
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17
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Hanford LC, Eckstrand K, Manelis A, Hafeman DM, Merranko J, Ladouceur CD, Graur S, McCaffrey A, Monk K, Bonar LK, Hickey MB, Goldstein TR, Goldstein BI, Axelson D, Bebko G, Bertocci MA, Gill MK, Birmaher B, Phillips ML. The impact of familial risk and early life adversity on emotion and reward processing networks in youth at-risk for bipolar disorder. PLoS One 2019; 14:e0226135. [PMID: 31830059 PMCID: PMC6907842 DOI: 10.1371/journal.pone.0226135] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2019] [Accepted: 11/20/2019] [Indexed: 12/11/2022] Open
Abstract
A recently developed risk calculator for bipolar disorder (BD) accounts for clinical and parental psychopathology. Yet, it is understood that both familial predisposition and early life adversity contribute to the development of BD. How the interplay between these two factors influence emotion and reward processing networks in youth at risk for BD remains unclear. In this exploratory analysis, offspring of BD parents performed emotion and reward processing tasks while undergoing a fMRI scan. Risk calculator score was used to assess risk for developing BD in the next 5 years. Environmental risk was tabulated using the Stressful Life Events Schedule (SLES). Emotion and reward processing networks were investigated for genetic and/or environment interactions. Interaction effects were found between risk calculator scores, negative SLES score and activity in right amygdala and bilateral fusiform gyri during the emotion processing task, as well as activity in the fronto-, striatal, and parietal regions during the reward processing task. Our findings are preliminary; however, they support the unique and interactive contributions of both familial and environmental risk factors on emotion and reward processing within OBP. They also identify potential neural targets to guide development of interventions for youth at greatest risk for psychiatric disorders.
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Affiliation(s)
- Lindsay C. Hanford
- Western Psychiatric Institute and Clinic, University of Pittsburgh Medical Center, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Kristen Eckstrand
- Western Psychiatric Institute and Clinic, University of Pittsburgh Medical Center, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Anna Manelis
- Western Psychiatric Institute and Clinic, University of Pittsburgh Medical Center, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Danella M. Hafeman
- Western Psychiatric Institute and Clinic, University of Pittsburgh Medical Center, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - John Merranko
- Western Psychiatric Institute and Clinic, University of Pittsburgh Medical Center, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Cecile D. Ladouceur
- Western Psychiatric Institute and Clinic, University of Pittsburgh Medical Center, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Simona Graur
- Western Psychiatric Institute and Clinic, University of Pittsburgh Medical Center, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Alicia McCaffrey
- Western Psychiatric Institute and Clinic, University of Pittsburgh Medical Center, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Kelly Monk
- Western Psychiatric Institute and Clinic, University of Pittsburgh Medical Center, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Lisa K. Bonar
- Western Psychiatric Institute and Clinic, University of Pittsburgh Medical Center, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Mary Beth Hickey
- Western Psychiatric Institute and Clinic, University of Pittsburgh Medical Center, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Tina R. Goldstein
- Western Psychiatric Institute and Clinic, University of Pittsburgh Medical Center, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Benjamin I. Goldstein
- Psychiatry, Sunnybrook Health Sciences Centre, Toronto, Canada
- Pharmacology and Toxicology, University of Toronto, Toronto, Canada
| | - David Axelson
- Nationwide Children’s Hospital and The Ohio State College of Medicine, Columbus, Ohio, United States of America
| | - Genna Bebko
- Western Psychiatric Institute and Clinic, University of Pittsburgh Medical Center, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Michele A. Bertocci
- Western Psychiatric Institute and Clinic, University of Pittsburgh Medical Center, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Mary Kay Gill
- Western Psychiatric Institute and Clinic, University of Pittsburgh Medical Center, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Boris Birmaher
- Western Psychiatric Institute and Clinic, University of Pittsburgh Medical Center, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Mary L. Phillips
- Western Psychiatric Institute and Clinic, University of Pittsburgh Medical Center, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
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18
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Riley KE, Hay JL, Waters EA, Biddle C, Schofield E, Li Y, Orom H, Kiviniemi MT. Lay beliefs about risk: relation to risk behaviors and to probabilistic risk perceptions. J Behav Med 2019; 42:1062-1072. [PMID: 31093806 PMCID: PMC7234841 DOI: 10.1007/s10865-019-00036-1] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2018] [Accepted: 03/23/2019] [Indexed: 01/29/2023]
Abstract
Lay illness risk beliefs are commonly held philosophies about how risk works. These include beliefs that one's personal illness risk is unknowable and beliefs that thinking about one's risk can actually increase that risk. Beliefs about risk may impact risk behaviors and thereby subsequent health status. However, limited research examines the relation between lay risk beliefs and health behavior. This paper explores this possible relation. A nationally representative sample of adults (N = 1005) recruited from an internet panel were surveyed about lay risk beliefs and risk perceptions regarding diabetes and colorectal cancer, psychosocial factors (i.e., health literacy, need for cognition, locus of control), demographics, and current health behaviors (i.e., cigarette smoking, red meat intake, physical activity). In separate sets of regressions controlling for either demographics, psychosocial factors, or risk perceptions, lay risk beliefs remained significantly related to health behaviors. It may be important to consider how to address lay risk beliefs in intervention content and targeting in order to increase adaptive health behaviors and thereby prevent chronic disease.
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Affiliation(s)
- Kristen E Riley
- Graduate School of Applied and Professional Psychology, 152 Frelinghuysen Rd, Piscataway, NJ, 08854, USA.
| | - Jennifer L Hay
- Department of Psychiatry and Behavioral Sciences, Memorial Sloan Kettering Cancer Center, 641 Lexington Ave, 7th Floor, New York, NY, 10022, USA.
| | - Erika A Waters
- Washington University in St. Louis, Saint Louis, MO, USA
| | - Caitlin Biddle
- Community Connections of New York, Inc., Buffalo, NY, USA
| | - Elizabeth Schofield
- Department of Psychiatry and Behavioral Sciences, Memorial Sloan Kettering Cancer Center, 641 Lexington Ave, 7th Floor, New York, NY, 10022, USA
| | - Yuelin Li
- Department of Psychiatry and Behavioral Sciences, Memorial Sloan Kettering Cancer Center, 641 Lexington Ave, 7th Floor, New York, NY, 10022, USA
| | - Heather Orom
- University of Buffalo- State University of New York, Buffalo, NY, USA
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19
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McGeoch L, Saunders CL, Griffin SJ, Emery JD, Walter FM, Thompson DJ, Antoniou AC, Usher-Smith JA. Risk Prediction Models for Colorectal Cancer Incorporating Common Genetic Variants: A Systematic Review. Cancer Epidemiol Biomarkers Prev 2019; 28:1580-1593. [PMID: 31292139 PMCID: PMC7610631 DOI: 10.1158/1055-9965.epi-19-0059] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2019] [Revised: 05/08/2019] [Accepted: 07/02/2019] [Indexed: 12/15/2022] Open
Abstract
Colorectal cancer screening reduces colorectal cancer incidence and mortality. Risk models based on phenotypic variables have relatively good discrimination in external validation and may improve efficiency of screening. Models incorporating genetic variables may perform better. In this review, we updated our previous review by searching Medline and EMBASE from the end date of that review (January 2014) to February 2019 to identify models incorporating at least one SNP and applicable to asymptomatic individuals in the general population. We identified 23 new models, giving a total of 29. Of those in which the SNP selection was on the basis of published genome-wide association studies, in external or split-sample validation the AUROC was 0.56 to 0.57 for models that included SNPs alone, 0.61 to 0.63 for SNPs in combination with other risk factors, and 0.56 to 0.70 when age was included. Calibration was only reported for four. The addition of SNPs to other risk factors increases discrimination by 0.01 to 0.06. Public health modeling studies suggest that, if determined by risk models, the range of starting ages for screening would be several years greater than using family history alone. Further validation and calibration studies are needed alongside modeling studies to assess the population-level impact of introducing genetic risk-based screening programs.
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Affiliation(s)
- Luke McGeoch
- School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom
| | - Catherine L Saunders
- The Primary Care Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Simon J Griffin
- The Primary Care Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Jon D Emery
- The Primary Care Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
- Department of General Practice and Centre for Cancer Research, Faculty of Medicine, Dentistry & Health Sciences, The University of Melbourne, Victorian Comprehensive Cancer Centre, Melbourne, Victoria, Australia
| | - Fiona M Walter
- The Primary Care Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
- Department of General Practice and Centre for Cancer Research, Faculty of Medicine, Dentistry & Health Sciences, The University of Melbourne, Victorian Comprehensive Cancer Centre, Melbourne, Victoria, Australia
| | - Deborah J Thompson
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, Strangeways Research Laboratory, University of Cambridge, Cambridge, United Kingdom
| | - Antonis C Antoniou
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, Strangeways Research Laboratory, University of Cambridge, Cambridge, United Kingdom
| | - Juliet A Usher-Smith
- The Primary Care Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom.
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20
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Mehraban Far P, Alshahrani A, Yaghoobi M. Quantitative risk of positive family history in developing colorectal cancer: A meta-analysis. World J Gastroenterol 2019; 25:4278-4291. [PMID: 31435179 PMCID: PMC6700697 DOI: 10.3748/wjg.v25.i30.4278] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/20/2019] [Revised: 07/06/2019] [Accepted: 07/19/2019] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND Positive family history is a risk factor for development of colorectal cancer. Despite numerous studies on the topic, the absolute risk in patients with a positive family history remains unclear and therefore studies are lacking to validate non-invasive screening methods in individuals with positive family history.
AIM To quantify the risk of colorectal cancer in individuals with a positive family history.
METHODS A comprehensive electronic literature search was performed using PubMed from January 1955 until November 2017, EMBASE from 1947 until 2018, and Cochrane Library without date restrictions. Two independent reviewers conducted study selection, data extraction and quality assessment. A meta-analysis of Mantel-Haenzel relative risks was performed using the random effects model. Newcastle-Ottawa scale was used to score the quality of selected papers. Funnel plot and Egger’s regression test was performed to detect publication bias. Subgroup analysis was performed comparing Asian and non-Asian studies. Sensitivity analyses were performed to rule out the effect of the timing of the study, overall quality, the main outcome and the effect of each individual study in overall result.
RESULTS Forty-six out of 3390 studies, including 906981 patients were included in the final analysis. 41 of the included studies were case-control and 5 were cohort. A positive family history of colorectal cancer in first-degree relatives was associated with significantly increased risk of colorectal cancer with a relative risk of 1.87 (95%CI: 1.68-2.09; P < 0.00001). Cochrane Q test was significant (P < 0.00001, I2 = 90%). Egger’s regression test showed asymmetry in the funnel plot and therefore the Trim and Fill method was used which confirmed the validity of the results. There was no difference between Asian versus non-Asian studies. Results remained robust in sensitivity analyses.
CONCLUSION Individuals with a positive family history of colorectal cancer are 1.87 times more likely to develop colorectal cancer. Screening guidelines should pay specific attention to individuals with positive family history and further studies need to be done on validating current screening methods or developing new modalities in this high-risk population.
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Affiliation(s)
| | | | - Mohammad Yaghoobi
- Division of Gastroenterology, McMaster University, Hamilton, ON L8S 4K1, Canada
- The Farncombe Family Digestive Health Research Institute, McMaster University, Hamilton, ON L8S 4K1, Canada
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21
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Gondal AB, Hsu CH, Zeeshan M, Hamidi M, Joseph B, Ghaderi I. A frailty index and the impact of frailty on postoperative outcomes in older patients after bariatric surgery. Surg Obes Relat Dis 2019; 15:1582-1588. [PMID: 31451386 DOI: 10.1016/j.soard.2019.06.028] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2019] [Accepted: 06/19/2019] [Indexed: 12/21/2022]
Abstract
BACKGROUND The prognostic value of frailty in the elderly surgical population has been well studied across surgical specialties. However, no studies have yet explored the effects of frailty across the full spectrum of adverse events after bariatric surgery. OBJECTIVES To study the impact of index-frailty on the full range of adverse short-term outcomes after bariatric surgery. METHODS Metabolic and Bariatric Surgery Accreditation and Quality Improvement Program data file for 2016 was used. Descriptive analyses, univariable, and multivariable regression models, assessed for discriminative and predictive capacities, were used to assess the effects of frailty on Clavien-Dindo categorized adverse outcomes within 30 days of bariatric surgery. Frailty index was modified from Canadian Study of Health and Aging Frailty Index. SETTING Data pooled from American Society for Bariatric Surgery-accredited bariatric surgery centers, United States. RESULTS A total of 21,426 patients aged ≥60 undergoing primary bariatric procedures were included. The prevalence of frailty as defined by the modified frailty index was 44.4%. Frail status was independently associated with higher odds of 30-day adverse events (Clavien-Dindo grades I, II, III, IV, and V). Frailty scores had weakly positive correlations with increasing age and increasing body mass index in the bariatric patients. CONCLUSION Frailty can be used as a risk stratification modality for patients before bariatric surgery. Further research should focus on exploring the relationship between obesity and frailty and the effects of weight loss on frailty status of bariatric patients.
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Affiliation(s)
- Amlish Bilal Gondal
- Banner-University Medical Centre, University of Arizona, Department of Surgery, Tucson, Arizona
| | - Chiu-Hsieh Hsu
- Banner-University Medical Centre, University of Arizona, Department of Surgery, Tucson, Arizona
| | - Muhammad Zeeshan
- Banner-University Medical Centre, University of Arizona, Department of Surgery, Tucson, Arizona
| | - Mohammad Hamidi
- Banner-University Medical Centre, University of Arizona, Department of Surgery, Tucson, Arizona
| | - Bellal Joseph
- Banner-University Medical Centre, University of Arizona, Department of Surgery, Tucson, Arizona
| | - Iman Ghaderi
- Banner-University Medical Centre, University of Arizona, Department of Surgery, Tucson, Arizona.
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22
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Mannucci A, Zuppardo RA, Rosati R, Leo MD, Perea J, Cavestro GM. Colorectal cancer screening from 45 years of age: Thesis, antithesis and synthesis. World J Gastroenterol 2019; 25:2565-2580. [PMID: 31210710 PMCID: PMC6558439 DOI: 10.3748/wjg.v25.i21.2565] [Citation(s) in RCA: 35] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/08/2019] [Revised: 04/15/2019] [Accepted: 04/20/2019] [Indexed: 02/06/2023] Open
Abstract
Colorectal cancer incidence and mortality in patients younger than 50 years are increasing, but screening before the age of 50 is not offered in Europe. Advanced-stage diagnosis and mortality from colorectal cancer before 50 years of age are increasing. This is not a detection-bias effect; it is a real issue affecting the entire population. Three independent computational models indicate that screening from 45 years of age would yield a better balance of benefits and risks than the current start at 50 years of age. Experimental data support these predictions in a sex- and race-independent manner. Earlier screening is seemingly affordable, with minimal impediments to providing younger adults with colonoscopy. Indeed, the American Cancer Society has already started to recommend screening from 45 years of age in the United States. Implementing early screening is a societal and public health problem. The three independent computational models that suggested earlier screening were criticized for assuming perfect compliance. Guidelines and recommendations should be derived from well-collected and reproducible data, and not from mathematical predictions. In the era of personalized medicine, screening decisions might not be based solely on age, and sophisticated prediction software may better guide screening. Moreover, early screening might divert resources away from older individuals with greater biological risks. Finally, it is still unknown whether early colorectal cancer is part of a continuum of disease or a biologically distinct disease and, as such, it might not benefit from screening at all. The increase in early-onset colorectal cancer incidence and mortality demonstrates an obligation to take actions. Earlier screening would save lives, and starting at the age of 45 years may be a robust screening option.
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Affiliation(s)
- Alessandro Mannucci
- Gastroenterology and Gastrointestinal Endoscopy Unit, Division of Experimental Oncology, Vita-Salute San Raffaele University, IRCCS San Raffaele Scientific Institute, Milan 20132, Italy
| | - Raffaella Alessia Zuppardo
- Gastroenterology and Gastrointestinal Endoscopy Unit, Division of Experimental Oncology, Vita-Salute San Raffaele University, IRCCS San Raffaele Scientific Institute, Milan 20132, Italy
| | - Riccardo Rosati
- Department of Surgery, Vita-Salute San Raffaele University, IRCCS San Raffaele Scientific Institute, Milan 20132, Italy
| | - Milena Di Leo
- Digestive Endoscopy Unit, Division of Gastroenterology, Humanitas Research Hospital, Department of Biomedical Science, Humanitas University, Milan 20090, Italy
| | - José Perea
- Surgery Department, “Fundación Jiménez Díaz” University Hospital, Madrid 28040, Spain
- Health Research Institute-Fundación Jiménez Díaz University Hospital, Madrid 28040, Spain
| | - Giulia Martina Cavestro
- Gastroenterology and Gastrointestinal Endoscopy Unit, Division of Experimental Oncology, Vita-Salute San Raffaele University, IRCCS San Raffaele Scientific Institute, Milan 20132, Italy
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23
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Smith T, Muller DC, Moons KGM, Cross AJ, Johansson M, Ferrari P, Fagherazzi G, Peeters PHM, Severi G, Hüsing A, Kaaks R, Tjonneland A, Olsen A, Overvad K, Bonet C, Rodriguez-Barranco M, Huerta JM, Barricarte Gurrea A, Bradbury KE, Trichopoulou A, Bamia C, Orfanos P, Palli D, Pala V, Vineis P, Bueno-de-Mesquita B, Ohlsson B, Harlid S, Van Guelpen B, Skeie G, Weiderpass E, Jenab M, Murphy N, Riboli E, Gunter MJ, Aleksandrova KJ, Tzoulaki I. Comparison of prognostic models to predict the occurrence of colorectal cancer in asymptomatic individuals: a systematic literature review and external validation in the EPIC and UK Biobank prospective cohort studies. Gut 2019; 68:672-683. [PMID: 29615487 PMCID: PMC6580880 DOI: 10.1136/gutjnl-2017-315730] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/21/2017] [Revised: 02/09/2018] [Accepted: 03/03/2018] [Indexed: 12/17/2022]
Abstract
OBJECTIVE To systematically identify and validate published colorectal cancer risk prediction models that do not require invasive testing in two large population-based prospective cohorts. DESIGN Models were identified through an update of a published systematic review and validated in the European Prospective Investigation into Cancer and Nutrition (EPIC) and the UK Biobank. The performance of the models to predict the occurrence of colorectal cancer within 5 or 10 years after study enrolment was assessed by discrimination (C-statistic) and calibration (plots of observed vs predicted probability). RESULTS The systematic review and its update identified 16 models from 8 publications (8 colorectal, 5 colon and 3 rectal). The number of participants included in each model validation ranged from 41 587 to 396 515, and the number of cases ranged from 115 to 1781. Eligible and ineligible participants across the models were largely comparable. Calibration of the models, where assessable, was very good and further improved by recalibration. The C-statistics of the models were largely similar between validation cohorts with the highest values achieved being 0.70 (95% CI 0.68 to 0.72) in the UK Biobank and 0.71 (95% CI 0.67 to 0.74) in EPIC. CONCLUSION Several of these non-invasive models exhibited good calibration and discrimination within both external validation populations and are therefore potentially suitable candidates for the facilitation of risk stratification in population-based colorectal screening programmes. Future work should both evaluate this potential, through modelling and impact studies, and ascertain if further enhancement in their performance can be obtained.
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Affiliation(s)
- Todd Smith
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - David C Muller
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Karel G M Moons
- Julius Center for Health Sciences and Primary Care, Umc Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Amanda J Cross
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Mattias Johansson
- International Agency for Research on Cancer (IARC), Genetic Epidemiology Group, Lyon, France
| | - Pietro Ferrari
- Nutritional Methodology and Biostatistics Group (NMB), International Agency for Research on Cancer, Lyon, France
| | - Guy Fagherazzi
- Inserm U1018, Gustave Roussy, Universite Paris-Sud, Villejuif, France
| | - Petra H M Peeters
- Department of Epidemiology, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Gianluca Severi
- Inserm U1018, Gustave Roussy, Universite Paris-Sud, Villejuif, France
| | - Anika Hüsing
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Rudolf Kaaks
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | | | - Anja Olsen
- Danish Cancer Society Research Center, Copenhagen, Denmark
| | - Kim Overvad
- Department of Public Health, Section for Epidemiology, Aarhus University, Aarhus, Denmark
| | - Catalina Bonet
- Catalan Institute of Oncology-IDIBELL, L’Hospitalet de Llobregat, Unit of Nutrition and Cancer, Cancer Epidemiology Research Program, Barcelona, Spain
| | | | - Jose Maria Huerta
- Murcia Regional Health Council, IMIB-Arrixaca, CIBER de Epidemiologia y Salud Publica (CIBERESP), Madrid, Spain
| | | | - Kathryn E Bradbury
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | | | | | - Philippos Orfanos
- Unit of Nutritional Epidemiology and Nutrition in Public Health, Department of Hygiene, Epidemiology and Medical Statistics, School of Medicine, WHO Collaborating Center for Nutrition and Health, National and Kapodistrian University of Athens, Athens, Greece
| | - Domenico Palli
- Cancer Risk Factors and Life-Style Epidemiology Unit, Cancer Research and Prevention Institute – ISPO, Florence, Italy
| | - Valeria Pala
- Epidemiology and Prevention Unit, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy
| | - Paolo Vineis
- Italian Institute for Genomic Medicine, Turin, Italy
| | - Bas Bueno-de-Mesquita
- Department for Determinants of Chronic Diseases (DCD), National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands
| | - Bodil Ohlsson
- Department of Internal Medicine, Lund University, Skane University Hospital, Malmo, Sweden
| | - Sophia Harlid
- Department of Radiation Sciences, Oncology, Umea University, Umea, Sweden
| | | | - Guri Skeie
- Department of Community Medicine, Faculty of Health Sciences, University of Tromso, The Arctic University of Norway, Tromso, Norway
| | - Elisabete Weiderpass
- Department of Research, Cancer Registry of Norway, Institute of Population-Based Cancer Research, Oslo, Norway
| | - Mazda Jenab
- Nutritional Epidemiology Group, International Agency for Research on Cancer, Lyon, France
| | - Neil Murphy
- Nutritional Epidemiology Group, International Agency for Research on Cancer, Lyon, France
| | - Elio Riboli
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Marc J Gunter
- Nutritional Epidemiology Group, International Agency for Research on Cancer, Lyon, France
| | - Krasimira Jekova Aleksandrova
- Nutrition, Immunity and Metabolism Start-up Lab, Department of Epidemiology, German Institute of Human Nutrition, Potsdam-Rehbrucke, Germany
| | - Ioanna Tzoulaki
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
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Liu J, Li C, Xu J, Wu H. A patient-oriented clinical decision support system for CRC risk assessment and preventative care. BMC Med Inform Decis Mak 2018; 18:118. [PMID: 30526596 PMCID: PMC6284274 DOI: 10.1186/s12911-018-0691-x] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022] Open
Abstract
Background Colorectal Cancer (CRC) is the third leading cause of cancer death among men and women in the United States. Research has shown that the risk of CRC associates with genetic and lifestyle factors. It is possible to prevent or minimize certain CRC risks by adopting a healthy lifestyle. Existing Clinical Decision Support Systems (CDSS) mainly targeted physicians as the CDSS users. As a result, the availability of patient-oriented CDSS is limited. Our project is to develop patient-oriented CDSS for active CRC management. Methods We implemented an online patient-oriented CRC CDSS for the public to learn about CRC, assess CRC risk levels, understand personalized CRC risk factors, and seek professional advices for people with CRC concerns. The system is implemented based on the Django Model-View-Controller (MVC) framework with an extensible background MySQL database. A CRC absolute risk prediction model is applied to calculate the personalized CRC risk score with a user-friendly web survey. An interactive dashboard using advanced data visualization technics will display and interpret the risk scores and factors. Based on the risk assessment, a structured decision tree algorithm will provide the recommendations on customized CRC screening methods. The CDSS also provides a search function for preferred providers and hospitals based on geographical information and patient preferences. Results A prototype of the patient-oriented CRC CDSS has been developed. It provides an open assessment of potential CRC risks via an online survey. The CRC risk predictive model has been implemented. The prediction outcomes of risk levels and factors are presented to the users through a personalized interactive visualization interface, to guide the public on how to reduce the CRC risks by changing their living styles (such as smoking and drinking) and diet characteristics (such as consumptions of red meat and milk). The CDSS will also provide customized recommendations on screening methods based on the corresponding risk factors. For users seeking professional clinicians, the CDSS also provides a convenient tool for searching nearby hospitals and available doctors based on the location preferences and providers characteristics (such as gender, language, and specialty). Conclusions This CRC CDSS prototype provides a patient-friendly interface for CRC risk assessment and gives a personalized interpretation on important CRC risk factors. It is a useful tool to educate the public on CRC, to provide guidance on minimizing CRC risks, and to promote early CRC screening that reduces the CRC occurrences. Electronic supplementary material The online version of this article (10.1186/s12911-018-0691-x) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Jiannan Liu
- Department of BioHealth Informatics, School of Informatics and Computing, Indiana University Purdue University Indianapolis (IUPUI), Indianapolis, IN, USA
| | - Chenyang Li
- Department of BioHealth Informatics, School of Informatics and Computing, Indiana University Purdue University Indianapolis (IUPUI), Indianapolis, IN, USA
| | - Jing Xu
- Department of BioHealth Informatics, School of Informatics and Computing, Indiana University Purdue University Indianapolis (IUPUI), Indianapolis, IN, USA
| | - Huanmei Wu
- Department of BioHealth Informatics, School of Informatics and Computing, Indiana University Purdue University Indianapolis (IUPUI), Indianapolis, IN, USA.
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25
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Peng L, Weigl K, Boakye D, Brenner H. Risk Scores for Predicting Advanced Colorectal Neoplasia in the Average-risk Population: A Systematic Review and Meta-analysis. Am J Gastroenterol 2018; 113:1788-1800. [PMID: 30315282 PMCID: PMC6768585 DOI: 10.1038/s41395-018-0209-2] [Citation(s) in RCA: 68] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/27/2017] [Accepted: 06/29/2018] [Indexed: 02/07/2023]
Abstract
OBJECTIVES A systematic review and meta-analysis was performed to summarize the available evidence on risk scores for predicting advanced colorectal neoplasia (advanced adenomas and cancer) in average-risk and asymptomatic populations undergoing screening colonoscopy. METHODS PubMed, EMBASE, and Web of Science databases were searched up to 28 March 2018. Studies that developed or validated a risk score to predict the risk of advanced colorectal neoplasia were included. Two reviewers independently extracted study characteristics including diagnostic performance indicators and assessed risk of bias and applicability in the included studies. Meta-analyses were conducted to determine the overall discrimination of risk scores evaluated by more than 1 study. RESULTS A total of 22 studies including 17 original risk scores were identified. Risk scores included a median number of 5 risk factors. Factors most commonly included were age, sex, family history in first-degree relatives, body mass index and smoking. The area under the receiver operating characteristic curve of risk scores ranged from 0.62 to 0.77 in the individual studies and from 0.61 to 0.70 in the meta-analyses. CONCLUSIONS Although the majority of available risk scores had relatively weak discriminatory power, they may be of some use for risk stratification in CRC screening. Rather than developing more risk scores based on environmental risk factors, future research should focus on exploring possibilities of enhancing predictive power by combining risk factor data with novel laboratory matters, such as polygenetic risk scores.
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Affiliation(s)
- Le Peng
- 1Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany.,2Medical Faculty Heidelberg, Heidelberg University, Heidelberg, Germany
| | - Korbinian Weigl
- 1Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany.,2Medical Faculty Heidelberg, Heidelberg University, Heidelberg, Germany.,3German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Daniel Boakye
- 1Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany.,2Medical Faculty Heidelberg, Heidelberg University, Heidelberg, Germany
| | - Hermann Brenner
- 1Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany.,3German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany.,4Division of Preventive Oncology, National Center for Tumor Diseases (NCT), German Cancer Research Center (DKFZ), Heidelberg, Germany
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26
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Birmaher B, Merranko JA, Goldstein TR, Gill MK, Goldstein BI, Hower H, Yen S, Hafeman D, Strober M, Diler RS, Axelson D, Ryan ND, Keller MB. A Risk Calculator to Predict the Individual Risk of Conversion From Subthreshold Bipolar Symptoms to Bipolar Disorder I or II in Youth. J Am Acad Child Adolesc Psychiatry 2018; 57:755-763.e4. [PMID: 30274650 PMCID: PMC6293466 DOI: 10.1016/j.jaac.2018.05.023] [Citation(s) in RCA: 50] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/14/2018] [Revised: 04/18/2018] [Accepted: 06/21/2018] [Indexed: 11/28/2022]
Abstract
OBJECTIVE Youth with subthreshold mania are at increased risk of conversion to bipolar disorder (BP) I/II. Predictors for conversion have been published for the group as a whole. However, risk factors are heterogeneous, indicating the need for personalized risk assessment. METHOD One hundred forty youth with BP not otherwise specified (BP-NOS; 6-17 years old) followed through the Course and Outcome of Bipolar Youth (COBY) study with at least 1 follow-up assessment before conversion to BP-I/II were included. Youths were assessed on average every 7 months (median 11.5 years) using standard instruments. Risk predictors reported in the literature were used to build a 5-year risk calculator. Discrimination was measured using the time-dependent area under the curve after 1,000 bootstrap resamples. Calibration was evaluated by comparing observed with predicted probability of conversion. External validation was performed using an independent sample of 58 youths with BP-NOS recruited from the Pittsburgh Bipolar Offspring Study. RESULTS Seventy-five (53.6%) COBY youths with BP-NOS converted to BP-I/II, of which 57 (76.0%) converted within 5 years. Earlier-onset BP-NOS, familial hypomania/mania, and high mania, anxiety, and mood lability symptoms were important predictors of conversion. The calculator showed excellent consistency between the predicted and observed risks of conversion, good discrimination between converters and non-converters (area under the curve 0.71, CI 0.67-0.74), and a proportionally increasing rate of converters at each successive risk class. Discrimination in the external validation sample was good (area under the curve 0.75). CONCLUSION If replicated, the risk calculator would provide a useful tool to predict personalized risk of conversion from subsyndromal mania to BP-I/II and inform individualized interventions and research.
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Affiliation(s)
| | | | | | | | - Benjamin I Goldstein
- Sunnybrook Health Sciences Centre, University of Toronto Faculty of Medicine, Ontario, Canada
| | - Heather Hower
- Warren Alpert Medical School of Brown University, Butler Hospital, Providence, RI
| | - Shirley Yen
- Warren Alpert Medical School of Brown University, Butler Hospital, Providence, RI
| | | | - Michael Strober
- David Geffen School of Medicine at the University of California, Los Angeles
| | | | - David Axelson
- Nationwide Children's Hospital and The Ohio State College of Medicine, Columbus
| | - Neal D Ryan
- University of Pittsburgh School of Medicine, PA
| | - Martin B Keller
- Warren Alpert Medical School of Brown University, Butler Hospital, Providence, RI
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27
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Smith T, Gunter MJ, Tzoulaki I, Muller DC. The added value of genetic information in colorectal cancer risk prediction models: development and evaluation in the UK Biobank prospective cohort study. Br J Cancer 2018; 119:1036-1039. [PMID: 30323197 PMCID: PMC6203780 DOI: 10.1038/s41416-018-0282-8] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2018] [Revised: 08/21/2018] [Accepted: 09/11/2018] [Indexed: 12/24/2022] Open
Abstract
Colorectal cancer (CRC) risk prediction models could be used to risk-stratify the population to provide individually tailored screening provision. Using participants from the UK Biobank prospective cohort study, we evaluated whether the addition of a genetic risk score (GRS) could improve the performance of two previously validated models. Inclusion of the GRS did not appreciably improve discrimination of either model, and led to substantial miscalibration. Following recalibration the discrimination did not change, but good calibration for models incorporating the GRS was recovered. Comparing predictions between models with and without the GRS, 5% of participants or fewer changed their absolute risk by ±0.3% or more in either model. In summary, addition of a GRS did not meaningfully improve the performance of validated CRC-risk prediction models. At present, provision of genetic information is not useful for risk stratification for CRC.
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Affiliation(s)
- Todd Smith
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, W2 1PG, UK
- MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, W2 1PG, UK
| | - Marc J Gunter
- Section of Nutrition and Metabolism, International Agency for Research on Cancer, Lyon, France
| | - Ioanna Tzoulaki
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, W2 1PG, UK.
- MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, W2 1PG, UK.
- Department of Hygiene and Epidemiology, University of Ioannina Medical School, Ioannina, Greece.
| | - David C Muller
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, W2 1PG, UK.
- MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, W2 1PG, UK.
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Usher-Smith JA, Harshfield A, Saunders CL, Sharp SJ, Emery J, Walter FM, Muir K, Griffin SJ. External validation of risk prediction models for incident colorectal cancer using UK Biobank. Br J Cancer 2018; 118:750-759. [PMID: 29381683 PMCID: PMC5846069 DOI: 10.1038/bjc.2017.463] [Citation(s) in RCA: 40] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2017] [Revised: 11/23/2017] [Accepted: 11/24/2017] [Indexed: 12/18/2022] Open
Abstract
BACKGROUND This study aimed to compare and externally validate risk scores developed to predict incident colorectal cancer (CRC) that include variables routinely available or easily obtainable via self-completed questionnaire. METHODS External validation of fourteen risk models from a previous systematic review in 373 112 men and women within the UK Biobank cohort with 5-year follow-up, no prior history of CRC and data for incidence of CRC through linkage to national cancer registries. RESULTS There were 1719 (0.46%) cases of incident CRC. The performance of the risk models varied substantially. In men, the QCancer10 model and models by Tao, Driver and Ma all had an area under the receiver operating characteristic curve (AUC) between 0.67 and 0.70. Discrimination was lower in women: the QCancer10, Wells, Tao, Guesmi and Ma models were the best performing with AUCs between 0.63 and 0.66. Assessment of calibration was possible for six models in men and women. All would require country-specific recalibration if estimates of absolute risks were to be given to individuals. CONCLUSIONS Several risk models based on easily obtainable data have relatively good discrimination in a UK population. Modelling studies are now required to estimate the potential health benefits and cost-effectiveness of implementing stratified risk-based CRC screening.
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Affiliation(s)
- J A Usher-Smith
- The Primary Care Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB2 0SR, UK
| | - A Harshfield
- The Primary Care Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB2 0SR, UK
| | - C L Saunders
- The Primary Care Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB2 0SR, UK
| | - S J Sharp
- MRC Epidemiology Unit, University of Cambridge, Institute of Metabolic Science, Cambridge CB2 0QQ, UK
| | - J Emery
- Department of General Practice, Centre for Cancer Research, Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Victorian Comprehensive Cancer Centre, Melbourne, VIC 3010, Australia
| | - F M Walter
- The Primary Care Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB2 0SR, UK
| | - K Muir
- Institute of Population Health, University of Manchester, Manchester M13 9PL, UK
| | - S J Griffin
- The Primary Care Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB2 0SR, UK
- MRC Epidemiology Unit, University of Cambridge, Institute of Metabolic Science, Cambridge CB2 0QQ, UK
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Hafeman DM, Merranko J, Goldstein TR, Axelson D, Goldstein BI, Monk K, Hickey MB, Sakolsky D, Diler R, Iyengar S, Brent DA, Kupfer DJ, Kattan MW, Birmaher B. Assessment of a Person-Level Risk Calculator to Predict New-Onset Bipolar Spectrum Disorder in Youth at Familial Risk. JAMA Psychiatry 2017; 74:841-847. [PMID: 28678992 PMCID: PMC5710639 DOI: 10.1001/jamapsychiatry.2017.1763] [Citation(s) in RCA: 97] [Impact Index Per Article: 13.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Abstract
IMPORTANCE Early identification of individuals at high risk for the onset of bipolar spectrum disorder (BPSD) is key from both a clinical and research perspective. While previous work has identified the presence of a bipolar prodrome, the predictive implications for the individual have not been assessed, to date. OBJECTIVE To build a risk calculator to predict the 5-year onset of BPSD in youth at familial risk for BPSD. DESIGN, SETTING, AND PARTICIPANTS The Pittsburgh Bipolar Offspring Study is an ongoing community-based longitudinal cohort investigation of offspring of parents with bipolar I or II (and community controls), recruited between November 2001 and July 2007, with a median follow-up period of more than 9 years. Recruitment has ended, but follow-up is ongoing. The present analysis included offspring of parents with bipolar I or II (aged 6-17 years) who had not yet developed BPSD at baseline. MAIN OUTCOMES AND MEASURES This study tested the degree to which a time-to-event model, including measures of mood and anxiety, general psychosocial functioning, age at mood disorder onset in the bipolar parent, and age at each visit, predicted new-onset BPSD. To fully use longitudinal data, the study assessed each visit separately, clustering within individuals. Discrimination was measured using the time-dependent area under the curve (AUC), predicting 5-year risk; internal validation was performed using 1000 bootstrapped resamples. Calibration was assessed by comparing observed vs predicted probability of new-onset BPSD. RESULTS There were 412 at-risk offspring (202 [49.0%] female), with a mean (SD) visit age of 12.0 (3.5) years and a mean (SD) age at new-onset BPSD of 14.2 (4.5) years. Among them, 54 (13.1%) developed BPSD during follow-up (18 with BD I or II); these participants contributed a total of 1058 visits, 67 (6.3%) of which preceded new-onset BPSD within the next 5 years. Using internal validation to account for overfitting, the model provided good discrimination between converting vs nonconverting visits (AUC, 0.76; bootstrapped 95% CI, 0.71-0.82). Important univariate predictors of outcome (AUC range, 0.66-0.70) were dimensional measures of mania, depression, anxiety, and mood lability; psychosocial functioning; and parental age at mood disorder. CONCLUSIONS AND RELEVANCE This risk calculator provides a practical tool for assessing the probability that a youth at familial risk for BPSD will develop new-onset BPSD within the next 5 years. Such a tool may be used by clinicians to inform frequency of monitoring and treatment options and for research studies to better identify potential participants at ultra high risk of conversion.
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Affiliation(s)
- Danella M. Hafeman
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - John Merranko
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Tina R. Goldstein
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - David Axelson
- Department of Psychiatry, Ohio State University, Columbus
| | | | - Kelly Monk
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Mary Beth Hickey
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Dara Sakolsky
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Rasim Diler
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Satish Iyengar
- Department of Statistics, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - David A. Brent
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - David J. Kupfer
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Michael W. Kattan
- Department of Quantitative Health Sciences, Cleveland Clinic, Cleveland, Ohio
| | - Boris Birmaher
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania
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30
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Iwasaki M, Tanaka-Mizuno S, Kuchiba A, Yamaji T, Sawada N, Goto A, Shimazu T, Sasazuki S, Wang H, Marchand LL, Tsugane S. Inclusion of a Genetic Risk Score into a Validated Risk Prediction Model for Colorectal Cancer in Japanese Men Improves Performance. Cancer Prev Res (Phila) 2017; 10:535-541. [PMID: 28729251 DOI: 10.1158/1940-6207.capr-17-0141] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2017] [Revised: 06/22/2017] [Accepted: 07/11/2017] [Indexed: 11/16/2022]
Abstract
We previously developed and validated a risk prediction model for colorectal cancer in Japanese men using modifiable risk factors. To further improve risk prediction, we evaluated the degree of improvement obtained by adding a genetic risk score (GRS) using genome-wide association study (GWAS)-identified risk variants to our validated model. We examined the association between 36 risk variants identified by GWAS and colorectal cancer risk using a weighted Cox proportional hazards model in a nested case-control study within the Japan Public Health Center-based Prospective Study. GRS was constructed using six variants associated with risk in this study of the 36 tested. We assessed three models: a nongenetic model that included the same variables used in our previously validated model; a genetic model that used GRS; and an inclusive model, which included both. The c-statistic, integrated discrimination improvement (IDI), and net reclassification improvement (NRI) were calculated by the 5-fold cross-validation method. We estimated 10-year absolute risks for developing colorectal cancer. A statistically significant association was observed between the weighted GRS and colorectal cancer risk. The mean c-statistic for the inclusive model (0.66) was slightly greater than that for the nongenetic model (0.60). Similarly, the mean IDI and NRI showed improvement when comparing the nongenetic and inclusive models. These models for colorectal cancer were well calibrated. The addition of GRS using GWAS-identified risk variants to our validated model for Japanese men improved the prediction of colorectal cancer risk. Cancer Prev Res; 10(9); 535-41. ©2017 AACR.
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Affiliation(s)
- Motoki Iwasaki
- Epidemiology and Prevention Group, Center for Public Health Sciences, National Cancer Center, Tokyo, Japan.
| | - Sachiko Tanaka-Mizuno
- Division of Medical Statistics, Shiga University of Medical Science, Tsukinowa Seta-cho, Ohtsu, Shiga, Japan
| | - Aya Kuchiba
- Division of Biostatistical Research, Center for Public Health Sciences, National Cancer Center, Tokyo, Japan
| | - Taiki Yamaji
- Epidemiology and Prevention Group, Center for Public Health Sciences, National Cancer Center, Tokyo, Japan
| | - Norie Sawada
- Epidemiology and Prevention Group, Center for Public Health Sciences, National Cancer Center, Tokyo, Japan
| | - Atsushi Goto
- Epidemiology and Prevention Group, Center for Public Health Sciences, National Cancer Center, Tokyo, Japan
| | - Taichi Shimazu
- Epidemiology and Prevention Group, Center for Public Health Sciences, National Cancer Center, Tokyo, Japan
| | - Shizuka Sasazuki
- Epidemiology and Prevention Group, Center for Public Health Sciences, National Cancer Center, Tokyo, Japan
| | - Hansong Wang
- Epidemiology Program, University of Hawaii Cancer Center, Honolulu, Hawaii
| | - Loïc Le Marchand
- Epidemiology Program, University of Hawaii Cancer Center, Honolulu, Hawaii
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Liu Y, Wang Y, Hu F, Sun H, Zhang Z, Wang X, Luo X, Zhu L, Huang R, Li Y, Li G, Li X, Lin S, Wang F, Liu Y, Rong J, Yuan H, Zhao Y. Multiple gene-specific DNA methylation in blood leukocytes and colorectal cancer risk: a case-control study in China. Oncotarget 2017; 8:61239-61252. [PMID: 28977860 PMCID: PMC5617420 DOI: 10.18632/oncotarget.18054] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2017] [Accepted: 04/07/2017] [Indexed: 12/17/2022] Open
Abstract
The relationship between gene-specific DNA methylation in peripheral blood leukocytes and colorectal cancer (CRC) susceptibility is unclear. In this case-control study, the methylation status of a panel of 10 CRC-related genes in 428 CRC cases and 428 cancer-free controls were detected with methylation-sensitive high-resolution melting analysis. We calculated a weighted methylation risk score (MRS) that comprehensively combined the methylation status of the panel of 10 genes and found that the MRS_10 was significantly associated with CRC risk. Compared with MRS-Low group, MRS-High group and MRS-Medium group exhibited a 6.51-fold (95% CI, 3.77-11.27) and 3.85-fold (95% CI, 2.72-5.45) increased risk of CRC, respectively. Moreover, the CRC risk increased with increasing MRS_10 (Ptrend < 0.0001). Stratified analyses demonstrated that the significant association retained in both men and women, younger and older, and normal weight or underweight and overweight or obese subjects. The area under the receiver operating characteristic curves for the MRS_10 model was 69.04% (95% CI, 65.57-72.66%) and the combined EF and MRS_10 model yielded an AUC of 79.12% (95% CI, 76.22-82.15%). Together, the panel of 10 gene-specific DNA methylation in leukocytes was strongly associated with the risk of CRC and might be a useful marker of susceptibility for CRC.
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Affiliation(s)
- Yupeng Liu
- Department of Epidemiology, Public Health College, Harbin Medical University, Harbin 150081, Heilongjiang Province, The People's Republic of China
| | - Yibaina Wang
- Department of Epidemiology, Public Health College, Harbin Medical University, Harbin 150081, Heilongjiang Province, The People's Republic of China
| | - Fulan Hu
- Department of Epidemiology, Public Health College, Harbin Medical University, Harbin 150081, Heilongjiang Province, The People's Republic of China
| | - Hongru Sun
- Department of Epidemiology, Public Health College, Harbin Medical University, Harbin 150081, Heilongjiang Province, The People's Republic of China
| | - Zuoming Zhang
- Department of Epidemiology, Public Health College, Harbin Medical University, Harbin 150081, Heilongjiang Province, The People's Republic of China
| | - Xuan Wang
- Department of Epidemiology, Public Health College, Harbin Medical University, Harbin 150081, Heilongjiang Province, The People's Republic of China
| | - Xiang Luo
- Department of Epidemiology, Public Health College, Harbin Medical University, Harbin 150081, Heilongjiang Province, The People's Republic of China
| | - Lin Zhu
- Department of Epidemiology, Public Health College, Harbin Medical University, Harbin 150081, Heilongjiang Province, The People's Republic of China
| | - Rong Huang
- Department of Epidemiology, Public Health College, Harbin Medical University, Harbin 150081, Heilongjiang Province, The People's Republic of China
| | - Yan Li
- Department of Epidemiology, Public Health College, Harbin Medical University, Harbin 150081, Heilongjiang Province, The People's Republic of China
| | - Guangxiao Li
- Department of Epidemiology, Public Health College, Harbin Medical University, Harbin 150081, Heilongjiang Province, The People's Republic of China
| | - Xia Li
- Department of Epidemiology, Public Health College, Harbin Medical University, Harbin 150081, Heilongjiang Province, The People's Republic of China
| | - Shangqun Lin
- Department of Epidemiology, Public Health College, Harbin Medical University, Harbin 150081, Heilongjiang Province, The People's Republic of China
| | - Fan Wang
- Department of Epidemiology, Public Health College, Harbin Medical University, Harbin 150081, Heilongjiang Province, The People's Republic of China
| | - Yanhong Liu
- Department of Clinical Laboratory, The Second Affiliated Hospital of Harbin Medical University, Harbin 150081, Heilongjiang Province, The People's Republic of China
| | - Jiesheng Rong
- Department of Orthopedics Surgery, The Second Affiliated Hospital of Harbin Medical University, Harbin 150081, Heilongjiang Province, The People's Republic of China
| | - Huiping Yuan
- Key Laboratory of Ophthalmology, Department of Ophthalmology, The Second Affiliated Hospital of Harbin Medical University, Harbin 150081, Heilongjiang Province, The People's Republic of China
| | - Yashuang Zhao
- Department of Epidemiology, Public Health College, Harbin Medical University, Harbin 150081, Heilongjiang Province, The People's Republic of China
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Raina A, Humbert M. Risk assessment in pulmonary arterial hypertension. Eur Respir Rev 2017; 25:390-398. [PMID: 27903661 PMCID: PMC9487550 DOI: 10.1183/16000617.0077-2016] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2016] [Accepted: 10/13/2016] [Indexed: 11/23/2022] Open
Abstract
Regular patient assessment is essential for the management of chronic diseases, such as pulmonary arterial hypertension (PAH). Comprehensive patient assessment and risk stratification in PAH are important to guide treatment decisions and to monitor disease progression as well as patients' response to treatment. Approaches for assessing risk in PAH patients include the use of risk variables, as recommended in the 2015 European Society of Cardiology (ESC)/European Respiratory Society (ERS) pulmonary hypertension (PH) guidelines, and the application of risk equations and scores, such as the French registry risk equation and the REVEAL registry risk score. Risk stratification and risk scores are both useful predictors of survival on a population basis, and provide an estimate for individual patients' risk. The 2015 ESC/ERS PH guidelines recommend regular assessment of multiple variables at an expert centre. The respective merits and limitations of different risk assessment methods in PAH are discussed in this article, as well as some considerations that can be taken into account in the future development of risk assessment tools. Regular risk assessment with multiple parameters evaluates PAH disease progression and treatment responsehttp://ow.ly/Nq0I305kgpU
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Affiliation(s)
- Amresh Raina
- Cardiovascular Institute, Allegheny General Hospital, Pittsburgh, PN, USA
| | - Marc Humbert
- Université Paris-Sud, Faculté de Médecine, Université Paris-Saclay, Le Kremlin-Bicêtre, France.,AP-HP, Service de Pneumologie, Hôpital Bicêtre, Le Kremlin-Bicêtre, France.,Inserm UMR_S 999, Hôpital Marie Lannelongue, Le Plessis Robinson, France
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33
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Personalized medicine for prevention: can risk stratified screening decrease colorectal cancer mortality at an acceptable cost? Cancer Causes Control 2017; 28:299-308. [DOI: 10.1007/s10552-017-0864-4] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2016] [Accepted: 02/01/2017] [Indexed: 12/15/2022]
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34
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Carrión RE, Cornblatt BA, Burton CZ, Tso IF, Auther A, Adelsheim S, Calkins R, Carter CS, Niendam T, Taylor SF, McFarlane WR, McFarlane WR. Personalized Prediction of Psychosis: External Validation of the NAPLS-2 Psychosis Risk Calculator With the EDIPPP Project. Am J Psychiatry 2016; 173:989-996. [PMID: 27363511 PMCID: PMC5048503 DOI: 10.1176/appi.ajp.2016.15121565] [Citation(s) in RCA: 127] [Impact Index Per Article: 15.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/02/2023]
Abstract
OBJECTIVE As part of the second phase of the North American Prodrome Longitudinal Study (NAPLS-2), Cannon and colleagues report, concurrently with the present article, on a risk calculator for the individualized prediction of a psychotic disorder in a 2-year period. The present study represents an external validation of the NAPLS-2 psychosis risk calculator using an independent sample of patients at clinical high risk for psychosis collected as part of the Early Detection, Intervention, and Prevention of Psychosis Program (EDIPPP). METHOD Of the total EDIPPP sample of 210 subjects rated as being at clinical high risk based on the Structured Interview for Prodromal Syndromes, 176 had at least one follow-up assessment and were included in the construction of a new prediction model with six predictor variables in the NAPLS-2 psychosis risk calculator (unusual thoughts and suspiciousness, symbol coding test performance, verbal learning test performance, decline in social functioning, baseline age, and family history). Discrimination performance was assessed with the area under the receiver operating characteristic curve (AUC). The NAPLS-2 risk calculator was then used to generate a psychosis risk estimate for each case in the external validation sample. RESULTS The external validation model showed good discrimination, with an AUC of 0.790 (95% CI=0.644-0.937). In addition, the personalized risk generated by the risk calculator provided a solid estimation of the actual conversion outcome in the validation sample. CONCLUSIONS Two independent samples of clinical high-risk patients converge to validate the NAPLS-2 psychosis risk calculator. This prediction calculator represents a meaningful step toward early intervention and the personalized treatment of psychotic disorders.
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Affiliation(s)
- Ricardo E. Carrión
- Division of Psychiatry Research, The Zucker Hillside Hospital, North Shore – Long Island Jewish Health System (NS-LIJHS), Glen Oaks, NY, USA,Center for Psychiatric Neuroscience, The Feinstein Institute for Medical Research, North Shore – Long Island Jewish Health System, Manhasset, New York, 11030, USA,Department of Psychiatry, Hofstra North Shore-LIJ School of Medicine, Hempstead, NY, USA
| | - Barbara A. Cornblatt
- Division of Psychiatry Research, The Zucker Hillside Hospital, North Shore – Long Island Jewish Health System (NS-LIJHS), Glen Oaks, NY, USA,Center for Psychiatric Neuroscience, The Feinstein Institute for Medical Research, North Shore – Long Island Jewish Health System, Manhasset, New York, 11030, USA,Department of Psychiatry, Hofstra North Shore-LIJ School of Medicine, Hempstead, NY, USA,Department of Molecular Medicine, Hofstra North Shore-LIJ School of Medicine, Hempstead, NY
| | - Cynthia Z. Burton
- Department of Psychiatry, University of Michigan, Ann Arbor, Michigan, USA
| | - Ivy F Tso
- Department of Psychiatry, University of Michigan, Ann Arbor, Michigan, USA
| | - Andrea Auther
- Division of Psychiatry Research, The Zucker Hillside Hospital, North Shore – Long Island Jewish Health System (NS-LIJHS), Glen Oaks, NY, USA,Department of Psychiatry, Hofstra North Shore-LIJ School of Medicine, Hempstead, NY, USA
| | - Steven Adelsheim
- Department of Psychiatry, Stanford University, Palo Alto, California, USA
| | - Roderick Calkins
- Mid-Valley Behavioral Care Network, Marion County Health Department, Salem, Oregon, USA
| | - Cameron S. Carter
- Imaging Research Center, University of California Davis, Sacramento, California, USA
| | - Tara Niendam
- Imaging Research Center, University of California Davis, Sacramento, California, USA
| | - Stephan F. Taylor
- Department of Psychiatry, University of Michigan, Ann Arbor, Michigan, USA
| | - William R. McFarlane
- Tufts University School of Medicine, Boston, MA,Maine Medical Center Research Institute, Portland, ME
| | - William R McFarlane
- From the Division of Psychiatry Research, Zucker Hillside Hospital, Northwell Health, Glen Oaks, N.Y.; the Center for Psychiatric Neuroscience, Feinstein Institute for Medical Research, Northwell Health, Manhasset, N.Y.; the Departments of Psychiatry and Molecular Medicine, Hofstra Northwell School of Medicine, Hempstead, N.Y.; the Department of Psychiatry, University of Michigan, Ann Arbor; the Department of Psychiatry, Stanford University, Palo Alto, Calif.; the Imaging Research Center and the Center for Neuroscience, University of California Davis, Sacramento, Calif.; Portland State University Regional Research Institute, Portland, Ore.; the Mid-Valley Behavioral Care Network, Marion County Health Department, Salem, Ore.; Tufts University School of Medicine, Boston; and Maine Medical Center Research Institute, Portland
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35
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Ladabaum U, Patel A, Mannalithara A, Sundaram V, Mitani A, Desai M. Predicting advanced neoplasia at colonoscopy in a diverse population with the National Cancer Institute colorectal cancer risk-assessment tool. Cancer 2016; 122:2663-70. [PMID: 27219715 DOI: 10.1002/cncr.30096] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2016] [Revised: 04/07/2016] [Accepted: 04/22/2016] [Indexed: 12/12/2022]
Abstract
BACKGROUND Tailoring screening to colorectal cancer (CRC) risk could improve screening effectiveness. Most CRCs arise from advanced neoplasia (AN) that dwells for years. To date, no available colorectal neoplasia risk score has been validated externally in a diverse population. The authors explored whether the National Cancer Institute (NCI) CRC risk-assessment tool, which was developed to predict future CRC risk, could predict current AN prevalence in a diverse population, thereby allowing its use in risk stratification for screening. METHODS This was a prospective examination of the relation between predicted 10-year CRC risk and the prevalence of AN, defined as advanced or multiple (≥3 adenomatous, ≥5 serrated) adenomatous or sessile serrated polyps, in individuals undergoing screening colonoscopy. RESULTS Among 509 screenees (50% women; median age, 58 years; 61% white, 5% black, 10% Hispanic, and 24% Asian), 58 (11%) had AN. The prevalence of AN increased progressively from 6% in the lowest risk-score quintile to 17% in the highest risk-score quintile (P = .002). Risk-score distributions in individuals with versus without AN differed significantly (median, 1.38 [0.90-1.87] vs 1.02 [0.62-1.57], respectively; P = .003), with substantial overlap. The discriminatory accuracy of the tool was modest, with areas under the curve of 0.61 (95% confidence interval [CI], 0.54-0.69) overall, 0.59 (95% CI, 0.49-0.70) for women, and 0.63 (95% CI, 0.53-0.73) for men. The results did not change substantively when the analysis was restricted to adenomatous lesions or to screening procedures without any additional incidental indication. CONCLUSIONS The NCI CRC risk-assessment tool displays modest discriminatory accuracy in predicting AN at screening colonoscopy in a diverse population. This tool may aid shared decision-making in clinical practice. Cancer 2016. © 2016 American Cancer Society. Cancer 2016;122:2663-2670. © 2016 American Cancer Society.
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Affiliation(s)
- Uri Ladabaum
- Division of Gastroenterology and Hepatology, Stanford University School of Medicine, Stanford, California.,Department of Medicine, Stanford University School of Medicine, Stanford, California
| | - Ashley Patel
- Division of Gastroenterology and Hepatology, Stanford University School of Medicine, Stanford, California.,Department of Medicine, Stanford University School of Medicine, Stanford, California
| | - Ajitha Mannalithara
- Division of Gastroenterology and Hepatology, Stanford University School of Medicine, Stanford, California.,Department of Medicine, Stanford University School of Medicine, Stanford, California
| | - Vandana Sundaram
- Department of Medicine, Stanford University School of Medicine, Stanford, California.,Quantitative Sciences Unit, Stanford University School of Medicine, Stanford, California
| | - Aya Mitani
- Department of Medicine, Stanford University School of Medicine, Stanford, California.,Quantitative Sciences Unit, Stanford University School of Medicine, Stanford, California
| | - Manisha Desai
- Department of Medicine, Stanford University School of Medicine, Stanford, California.,Quantitative Sciences Unit, Stanford University School of Medicine, Stanford, California
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36
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Affiliation(s)
- Ethan Bortniker
- Division of Gastroenterology and Hepatology, University of Connecticut School of Medicine, Farmington, CT, 06030, USA
| | - Joseph C Anderson
- Department of Veterans Affairs Medical Center, White River Junction, VT, USA. .,The Geisel School of Medicine at Dartmouth, Hanover, NH, USA. .,Division of Gastroenterology and Hepatology, University of Connecticut School of Medicine, Farmington, CT, 06030, USA.
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37
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Locke PA, Weil MM. Personalized Cancer Risk Assessments for Space Radiation Exposures. Front Oncol 2016; 6:38. [PMID: 26942127 PMCID: PMC4762001 DOI: 10.3389/fonc.2016.00038] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2015] [Accepted: 02/05/2016] [Indexed: 11/13/2022] Open
Abstract
Individuals differ in their susceptibility to radiogenic cancers, and there is evidence that this inter-individual susceptibility extends to HZE ion-induced carcinogenesis. Three components of individual risk: sex, age at exposure, and prior tobacco use, are already incorporated into the NASA cancer risk model used to determine safe days in space for US astronauts. Here, we examine other risk factors that could potentially be included in risk calculations. These include personal and family medical history, the presence of pre-malignant cells that could undergo malignant transformation as a consequence of radiation exposure, the results from phenotypic assays of radiosensitivity, heritable genetic polymorphisms associated with radiosensitivity, and postflight monitoring. Inclusion of these additional risk or risk reduction factors has the potential to personalize risk estimates for individual astronauts and could influence the determination of safe days in space. We consider how this type of assessment could be used and explore how the provisions of the federal Genetic Information Non-discrimination Act could impact the collection, dissemination and use of this information by NASA.
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Affiliation(s)
- Paul A Locke
- Department of Environmental Health Sciences, Johns Hopkins Bloomberg School of Public Health , Baltimore, MD , USA
| | - Michael M Weil
- Department of Environmental and Radiological Health Sciences, Colorado State University , Fort Collins, CO , USA
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Which Aspirin Dose and Preparation Is Best for the Long-Term Prevention of Cardiovascular Disease and Cancer? Evidence From a Systematic Review and Network Meta-Analysis. Prog Cardiovasc Dis 2016; 58:495-504. [PMID: 26851562 DOI: 10.1016/j.pcad.2016.02.001] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/01/2016] [Accepted: 02/01/2016] [Indexed: 02/05/2023]
Abstract
The evidence base on aspirin in primary prevention suggests that it can reduce significantly the risk of cardiovascular disease (CVD) events and cancer, especially colorectal, albeit increasing bleeding. There is, however, uncertainty on the optimal aspirin dose and preparation for primary prevention. We thus aimed to review main sources of evidence informing on daily dosage and preparation of aspirin for primary prevention of CVD and cancer. We collected and elaborated aspirin effectiveness and safety data from U.S. Preventive Services Task Force reports on aspirin in primary prevention, distinguishing average daily dose in <100mg, 100mg, and >100mg. The following preparations were also systematically compared: enteric coated, controlled release, non-coated, or otherwise unspecified. Fixed-effect pairwise and network meta-analytic models were run in a frequentist framework. Eleven randomized trials were shortlisted, enrolling 104,101 subjects, followed for a median of 60months. At pairwise analysis, aspirin was associated with significant reductions in death and CVD events, non-significant reductions in cancer death or incidence, and significant increases in the risk of intracranial and gastrointestinal (GI) bleeding. An average daily dose of 100mg had the highest probability of reducing death, cancer death, and cancer incidence, whereas higher doses seemed superior for reducing CVD events, and 100mg or less daily proved better tolerated. Coated preparations appeared more beneficial for death, cancer death, cancer incidence, and GI bleeding, whereas controlled release preparations appeared better for CVD events and non-coated ones for intracranial bleeding. In conclusion, an average daily dose of 100mg of coated aspirin seems more likely to confer favorable preventive effects on death and cancer, with higher doses more appealing for CVD prevention and lower doses better tolerated.
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Comment on: "Development of a sleeve gastrectomy risk calculator". Surg Obes Relat Dis 2015; 12:1766. [PMID: 26656878 DOI: 10.1016/j.soard.2015.10.082] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2015] [Accepted: 10/27/2015] [Indexed: 11/23/2022]
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Ruco A, Stock D, Hilsden RJ, McGregor SE, Paszat LF, Saskin R, Rabeneck L. Evaluation of a clinical risk index for advanced colorectal neoplasia among a North American population of screening age. BMC Gastroenterol 2015; 15:162. [PMID: 26585867 PMCID: PMC4653881 DOI: 10.1186/s12876-015-0395-y] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/19/2015] [Accepted: 11/12/2015] [Indexed: 12/14/2022] Open
Abstract
Background A clinical risk index employing age, sex, family history of colorectal cancer (CRC), smoking history and body mass index (BMI) may be useful for prioritizing screening with colonoscopy. The aim of this study was to conduct an external evaluation of a previously published risk index for advanced neoplasia (AN) in a large, well-characterized cohort. Methods Five thousand one hundred thirty-seven asymptomatic persons aged 50 to 74 (54.9 % women) with a mean age (SD) of 58.3 (6.2) years were recruited for the study from a teaching hospital and colorectal cancer screening centre between 2003 and 2011. All participants underwent a complete screening colonoscopy and removal of all polyps. AN was defined as cancer or a tubular adenoma, traditional serrated adenoma (TSA), or sessile serrated adenoma (SSA) with villous characteristics (≥25% villous component), and/or high-grade dysplasia and/or diameter ≥10 mm. Risk scores for each participant were summed to derive an overall score (0–8). The c-statistic was used to measure discriminating ability of the risk index. Results The prevalence of AN in the study cohort was 6.8 %. The likelihood of detecting AN increased from 3.6 to 13.1 % for those with a risk score of 1 to 6 respectively. The c-statistic for the multivariable logistic model in our cohort was 0.64 (95 % CI = 0.61–067) indicating modest overlap between risk scores. Conclusions The risk index for AN using age, sex, family history, smoking history and BMI was found to be of limited discriminating ability upon external validation. The index requires further refinement to better predict AN in average risk persons of screening age.
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Affiliation(s)
- Arlinda Ruco
- Sunnybrook Health Sciences Centre, Toronto, ON, Canada.
| | - David Stock
- Sunnybrook Health Sciences Centre, Toronto, ON, Canada.
| | - Robert J Hilsden
- Department of Medicine, University of Calgary, Calgary, AB, Canada.
| | - S Elizabeth McGregor
- Alberta Health Services - Population, Public & Aboriginal Health, Calgary, AB, Canada.
| | - Lawrence F Paszat
- Sunnybrook Health Sciences Centre, Toronto, ON, Canada. .,Institute for Clinical Evaluative Sciences, Toronto, ON, Canada. .,Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada. .,Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada.
| | - Refik Saskin
- Institute for Clinical Evaluative Sciences, Toronto, ON, Canada.
| | - Linda Rabeneck
- Institute for Clinical Evaluative Sciences, Toronto, ON, Canada. .,Prevention and Cancer Control, Cancer Care Ontario, 620 University Avenue, Toronto, M5G 2L7, ON, Canada. .,Department of Medicine, University of Toronto, Toronto, ON, Canada. .,Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada. .,Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada.
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Kawai K, Sunami E, Yamaguchi H, Ishihara S, Kazama S, Nozawa H, Hata K, Kiyomatsu T, Tanaka J, Tanaka T, Nishikawa T, Kitayama J, Watanabe T. Nomograms for colorectal cancer: A systematic review. World J Gastroenterol 2015; 21:11877-86. [PMID: 26557011 PMCID: PMC4631985 DOI: 10.3748/wjg.v21.i41.11877] [Citation(s) in RCA: 41] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/26/2015] [Revised: 05/28/2015] [Accepted: 09/30/2015] [Indexed: 02/06/2023] Open
Abstract
AIM To assist in the selection of suitable nomograms for obtaining desired predictions in daily clinical practice. METHODS We conducted electronic searches for journal articles on colorectal cancer (CRC)-associated nomograms using the search terms colon/rectal/colorectal/nomogram. Of 174 articles initially found, we retrieved 28 studies in which a nomogram for CRC was developed. RESULTS We discuss the currently available CRC-associated nomograms, including those that predict the oncological prognosis, the short-term outcome of treatments, such as surgery or neoadjuvant chemoradiotherapy, and the future development of CRC. Developing nomograms always presents a dilemma. On the one hand, the desire to cover as wide a patient range as possible tends to produce nomograms that are too complex and yet have C-indexes that are not sufficiently high. Conversely, confining the target patients might impair the clinical applicability of constructed nomograms. CONCLUSION The information provided in this review should be of use in selecting a nomogram suitable for obtaining desired predictions in daily clinical practice.
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Usher-Smith JA, Walter FM, Emery JD, Win AK, Griffin SJ. Risk Prediction Models for Colorectal Cancer: A Systematic Review. Cancer Prev Res (Phila) 2015; 9:13-26. [PMID: 26464100 DOI: 10.1158/1940-6207.capr-15-0274] [Citation(s) in RCA: 114] [Impact Index Per Article: 12.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2015] [Accepted: 09/15/2015] [Indexed: 12/12/2022]
Abstract
Colorectal cancer is the second leading cause of cancer-related death in Europe and the United States. Survival is strongly related to stage at diagnosis and population-based screening reduces colorectal cancer incidence and mortality. Stratifying the population by risk offers the potential to improve the efficiency of screening. In this systematic review we searched Medline, EMBASE, and the Cochrane Library for primary research studies reporting or validating models to predict future risk of primary colorectal cancer for asymptomatic individuals. A total of 12,808 papers were identified from the literature search and nine through citation searching. Fifty-two risk models were included. Where reported (n = 37), half the models had acceptable-to-good discrimination (the area under the receiver operating characteristic curve, AUROC >0.7) in the derivation sample. Calibration was less commonly assessed (n = 21), but overall acceptable. In external validation studies, 10 models showed acceptable discrimination (AUROC 0.71-0.78). These include two with only three variables (age, gender, and BMI; age, gender, and family history of colorectal cancer). A small number of prediction models developed from case-control studies of genetic biomarkers also show some promise but require further external validation using population-based samples. Further research should focus on the feasibility and impact of incorporating such models into stratified screening programmes.
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Affiliation(s)
- Juliet A Usher-Smith
- The Primary Care Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom.
| | - Fiona M Walter
- The Primary Care Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom. Department of General Practice, Melbourne Medical School Faculty of Medicine, Dentistry & Health Sciences The University of Melbourne, Carlton, Victoria, Australia
| | - Jon D Emery
- The Primary Care Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom. Department of General Practice, Melbourne Medical School Faculty of Medicine, Dentistry & Health Sciences The University of Melbourne, Carlton, Victoria, Australia
| | - Aung K Win
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, Level 4, The University of Melbourne, Victoria, Australia
| | - Simon J Griffin
- The Primary Care Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
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Schroy PC, Wong JB, O’Brien MJ, Chen CA, Griffith JL. A Risk Prediction Index for Advanced Colorectal Neoplasia at Screening Colonoscopy. Am J Gastroenterol 2015; 110:1062-71. [PMID: 26010311 PMCID: PMC4705553 DOI: 10.1038/ajg.2015.146] [Citation(s) in RCA: 34] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/01/2014] [Accepted: 04/03/2015] [Indexed: 12/11/2022]
Abstract
OBJECTIVES Eliciting patient preferences within the context of shared decision making has been advocated for colorectal cancer screening. Risk stratification for advanced colorectal neoplasia (ACN) might facilitate more effective shared decision making when selecting an appropriate screening option. Our objective was to develop and validate a clinical index for estimating the probability of ACN at screening colonoscopy. METHODS We conducted a cross-sectional analysis of 3,543 asymptomatic, mostly average-risk patients 50-79 years of age undergoing screening colonoscopy at two urban safety net hospitals. Predictors of ACN were identified using multiple logistic regression. Model performance was internally validated using bootstrapping methods. RESULTS The final index consisted of five independent predictors of risk (age, smoking, alcohol intake, height, and a combined sex/race/ethnicity variable). Smoking was the strongest predictor (net reclassification improvement (NRI), 8.4%) and height the weakest (NRI, 1.5%). Using a simplified weighted scoring system based on 0.5 increments of the adjusted odds ratio, the risk of ACN ranged from 3.2% (95% confidence interval (CI), 2.6-3.9) for the low-risk group (score ≤2) to 8.6% (95% CI, 7.4-9.7) for the intermediate/high-risk group (score 3-11). The model had moderate to good overall discrimination (C-statistic, 0.69; 95% CI, 0.66-0.72) and good calibration (P=0.73-0.93). CONCLUSIONS A simple 5-item risk index based on readily available clinical data accurately stratifies average-risk patients into low- and intermediate/high-risk categories for ACN at screening colonoscopy. Uptake into clinical practice could facilitate more effective shared decision-making for CRC screening, particularly in situations where patient and provider test preferences differ.
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Affiliation(s)
- Paul C. Schroy
- Department of Medicine, Boston University School of Medicine, Boston, MA
| | - John B. Wong
- Department of Medicine, Tufts Medical Center, Boston, MA
| | - Michael J. O’Brien
- Department of Pathology, Boston University School of Medicine, Boston, MA
| | - Clara A. Chen
- Data Coordinating Center, Boston University School of Public Health, Boston, MA
| | - John L. Griffith
- Department of Health Sciences, Bouve College of Health Sciences, Northeastern University, Boston, MA
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Battistoni A, Mastromarino V, Volpe M. Reducing Cardiovascular and Cancer Risk: How to Address Global Primary Prevention in Clinical Practice. Clin Cardiol 2015; 38:387-94. [PMID: 25873555 DOI: 10.1002/clc.22394] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/19/2014] [Revised: 01/15/2015] [Accepted: 01/20/2015] [Indexed: 12/11/2022] Open
Abstract
Emerging evidence suggesting the possibility that interventions able to prevent cardiovascular disease (CVD) may also be effective in the prevention of cancer have recently stimulated great interest in the medical community. In particular, data from both experimental and observational studies have demonstrated that aspirin may play a role in preventing different types of cancer. Although the use of aspirin in the secondary prevention of CVD is well established, aspirin in primary prevention is not systematically recommended because the absolute cardiovascular event reduction is similar to the absolute excess in major bleedings. By adding to its cardiovascular prevention benefits, the potential beneficial effect of aspirin in reducing the incidence of mortality and cancer could tip the balance between risks and benefits of aspirin therapy in primary prevention in favor of the latter and broaden the indication for treatment with aspirin in populations at average risk. Prospective and randomized studies are currently investigating the effect of aspirin in prevention of both cancer and CVD; however, clinical efforts at the individual level to promote the use of aspirin in global (or total) primary prevention already could be made on the basis of a balanced evaluation of the benefit/risk ratio.
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Affiliation(s)
- Allegra Battistoni
- Cardiology Department, Clinical and Molecular Medicine Department, Sapienza University of Rome, Rome, Italy
| | - Vittoria Mastromarino
- Cardiology Department, Clinical and Molecular Medicine Department, Sapienza University of Rome, Rome, Italy
| | - Massimo Volpe
- Cardiology Department, Clinical and Molecular Medicine Department, Sapienza University of Rome, Rome, Italy.,IRCCS Neuromed (Volpe), Pozzilli, Italy
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Bortniker E, Anderson JC. Do recent epidemiologic observations impact who and how we should screen for CRC? Dig Dis Sci 2015; 60:781-94. [PMID: 25492505 DOI: 10.1007/s10620-014-3467-x] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/30/2014] [Accepted: 11/26/2014] [Indexed: 12/18/2022]
Abstract
Colorectal cancer (CRC) screening is recommended to begin at age 50 for those patients with no significant family history of CRC. However, even within this group of average-risk patients, there is data to suggest that there may be variation in CRC risk. These observations suggest that perhaps CRC screening should be tailored to target those patients at higher risk for earlier or more invasive screening as compared to those individuals at lower risk. The strategy of how to identify those higher-risk patients may not be straightforward. One method might be to use single risk factors such as smoking or elevated BMI as has been suggested in the recent American College of Gastroenterology CRC screening guidelines. Another paradigm involves the use of models which incorporate several risk factors to stratify patients by risk. This article will highlight recent large studies that examine recognized CRC risk factors as well as review recently developed CRC risk models. There will also be a discussion of the application of these factors and models in an effort to make CRC screening more efficient.
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Affiliation(s)
- Ethan Bortniker
- Division of Gastroenterology and Hepatology, University of Connecticut School of Medicine, Farmington, CT, 06030, USA
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Benamouzig R. Prediction of Colorectal Cancer or Colonic Neoplasia Risk: From Symptoms to Scores. CURRENT COLORECTAL CANCER REPORTS 2015. [DOI: 10.1007/s11888-014-0254-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
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Aminian A, Brethauer SA, Sharafkhah M, Schauer PR. Development of a sleeve gastrectomy risk calculator. Surg Obes Relat Dis 2014; 11:758-64. [PMID: 26117166 DOI: 10.1016/j.soard.2014.12.012] [Citation(s) in RCA: 64] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2014] [Revised: 12/10/2014] [Accepted: 12/12/2014] [Indexed: 12/14/2022]
Abstract
BACKGROUND Laparoscopic sleeve gastrectomy (LSG) is rapidly gaining popularity. Estimating the risk of postoperative adverse events can improve surgical decision-making and informed patient consent. The objective of this study was to develop and validate a risk prediction model for early postoperative morbidity and mortality after LSG. METHODS Cases of primary LSG in the American College of Surgeons-National Surgical Quality Improvement Program (ACS-NSQIP) data set at year 2012 (n = 5871) and 2011 (n = 3130) were identified to develop and examine the validity of model. The composite primary outcome was defined as presence of any of 14 serious adverse events within the 30-days after LSG. Multiple logistic regression analysis was performed and a risk calculator was created to predict the primary outcome. RESULTS Thirty-day postoperative mortality and composite adverse events rates of 5871 LSG cases were .05% and 2.4%, respectively. Of the 52 examined baseline variables, the final model contained history of congestive heart failure (odds ratio [OR] 6.23; 95% CI 1.25-31.07), chronic steroid use (OR 5.00; 95% CI 2.06-12.15), male sex (OR 1.68; 95% CI 1.03-2.72), diabetes (OR 1.62; 95% CI 1.07-2.48), preoperative serum total bilirubin level (OR 1.57; 95% CI 1.11-2.22), body mass index (OR 1.03; 95% CI 1.01-1.05), and preoperative hematocrit level (OR .95; 95% CI .89-1.00). The risk model was then validated with the 2011 data set and was used to create an online risk calculator with a relatively good accuracy (c-statistic .682). CONCLUSIONS This risk assessment scoring system, which specifically estimates serious adverse events after LSG, can contribute to surgical decision-making, informed patient consent, and prediction of surgical risk for patients and referring physicians.
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Affiliation(s)
- Ali Aminian
- Bariatric and Metabolic Institute, Cleveland Clinic, Cleveland, Ohio
| | - Stacy A Brethauer
- Bariatric and Metabolic Institute, Cleveland Clinic, Cleveland, Ohio
| | - Maryam Sharafkhah
- Bariatric and Metabolic Institute, Cleveland Clinic, Cleveland, Ohio
| | - Philip R Schauer
- Bariatric and Metabolic Institute, Cleveland Clinic, Cleveland, Ohio.
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Yu TY, Li HY, Jiang YD, Chang TJ, Wei JN, Lin CM, Chu CC, Chuang LM. Serum vascular adhesion protein-1 level predicts risk of incident cancers in subjects with type II diabetes. Cancer Epidemiol Biomarkers Prev 2014; 23:1366-73. [PMID: 24781952 DOI: 10.1158/1055-9965.epi-14-0023] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
BACKGROUND Serum vascular adhesion protein-1 (VAP-1) predicts cancer-related mortality in diabetic subjects. However, whether serum VAP-1 predicts cancer incidence or cancer progression remains unclear. We conducted a cohort study to investigate whether serum VAP-1 and related clinical variables predict incident cancers in type II diabetic subjects. METHODS From 1996 to 2003, we enrolled 568 type II diabetic subjects who were free of cancer at baseline. Serum VAP-1 at enrollment was measured by time-resolved immunofluorometric assay. Chronic kidney disease (CKD) was defined as estimated glomerular filtration rate <60 mL/min per 1.73 m(2). The subjects were followed until first occurrence of cancer or until December 31, 2011. RESULTS During a mean follow-up of 11.3 years, 71 subjects developed incident cancers. The HRs for incident cancers in subjects with highest tertile of serum VAP-1 and in subjects with CKD were 2.95 [95% confidence interval (CI), 1.31-6.63; P = 0.009] and 2.29 (95% CI, 1.18-4.44; P = 0.015), respectively, after multivariate adjustment. There was an interaction between serum VAP-1 and CKD on the risk of incident cancers (P = 0.01 for log-transformed VAP-1 × CKD). The relationship among serum VAP-1, CKD, and incident cancers was similar if death was considered in the competing risk models or if subjects with shorter follow-up period were excluded. CONCLUSIONS Higher serum VAP-1 and CKD can independently predict future development of cancers in type II diabetic subjects. IMPACT Physicians should be aware of the early signs of cancer in diabetic individuals with elevated VAP-1 or renal dysfunction. More aggressive treatment strategies might be considered.
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Affiliation(s)
- Tse-Ya Yu
- Authors' Affiliations: Department of Internal Medicine, En Chu Kong Hospital, New Taipei City
| | - Hung-Yuan Li
- Department of Internal Medicine, National Taiwan University Hospital, Taipei; and
| | - Yi-Der Jiang
- Department of Internal Medicine, National Taiwan University Hospital, Taipei; and
| | - Tien-Jyun Chang
- Department of Internal Medicine, National Taiwan University Hospital, Taipei; and
| | - Jung-Nan Wei
- Chia Nan University of Pharmacy and Science, Tainan, Taiwan
| | - Chi-Ming Lin
- Authors' Affiliations: Department of Internal Medicine, En Chu Kong Hospital, New Taipei City
| | - Ching-Chi Chu
- Authors' Affiliations: Department of Internal Medicine, En Chu Kong Hospital, New Taipei City
| | - Lee-Ming Chuang
- Graduate Institute of Clinical Medicine, Medical College and Graduate Institute of Preventive Medicine, National Taiwan University School of Public Health, National Taiwan University; Department of Internal Medicine, National Taiwan University Hospital, Taipei; and
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