Prognosis research strategy (PROGRESS) 4: stratified medicine research

Development of a core descriptor set for Crohn's anal fistula

AIM

Crohn's anal fistula (CAF) is a complex condition, with no agreement on which patient characteristics should be routinely reported in studies. The aim of this study was to develop a core descriptor set of key patient characteristics for reporting in all CAF research.

METHOD

Candidate descriptors were generated from published literature and stakeholder suggestions. Colorectal surgeons, gastroenterologists and specialist nurses in inflammatory bowel disease took part in three rounds of an international modified Delphi process using nine-point Likert scales to rank the importance of descriptors. Feedback was provided between rounds to allow refinement of the next ratings. Patterns in descriptor voting were assessed using principal component analysis (PCA). Resulting PCA groups were used to organize items in rounds two and three. Consensus descriptors were submitted to a patient panel for feedback. Items meeting predetermined thresholds were included in the final set and ratified at the consensus meeting.

RESULTS

One hundred and thirty three respondents from 22 countries completed round one, of whom 67.0% completed round three. Ninety seven descriptors were rated across three rounds in 11 PCA-based groups. Forty descriptors were shortlisted. The consensus meeting ratified a core descriptor set of 37 descriptors within six domains: fistula anatomy, current disease activity and phenotype, risk factors, medical interventions for CAF, surgical interventions for CAF, and patient symptoms and impact on quality of life.

CONCLUSION

The core descriptor set proposed for all future CAF research reflects characteristics important to gastroenterologists and surgeons. This might aid transparent reporting in future studies.

Service evaluation of telehealth in a physiotherapy musculoskeletal setting: Patient outcomes and results from risk stratification

INTRODUCTION

Due to COVID-19 the ability to see all patients face-to-face (FTF) was removed. Services implemented telehealth to cater for patients requiring musculoskeletal care. A service evaluation was undertaken to assess the effectiveness of a mixed telehealth/FTF approach and identify if stratifying patients could help tailor intervention.

METHODS

Retrospective analysis of data collected from patients who were assessed by Musculoskeletal Physiotherapists in one Scottish health board was undertaken. Patients were divided into low, medium and high risk sub-groups through the Keele STarT MSK tool. Outcome measures for pain and musculoskeletal health were taken at baseline/discharge along with satisfaction/preference. Descriptive and Inferential statistical analysis was conducted to establish whether changes in the outcome measures within and between risk sub-groups were statistically significant.

RESULTS

Pain level difference from baseline to discharge demonstrated clinically and statistically significant improvements across all risk groups (N = 89). Musculoskeletal health demonstrated clinically significant improvements across all risk groups and statistically significant improvements in the medium/high risk groups but not the low risk. Patients with knee osteoarthritis and low back pain in the medium risk group had fewest appointments while patients with chronic shoulder pain had the most. The majority of patients were satisfied with all mediums but preferred FTF or an option between telehealth/FTF in the future.

CONCLUSION

Telehealth is a promising model of care when utilised in combination with FTF for patients with musculoskeletal conditions. Through stratification, identifying specific conditions and shared decision making it may be possible to treat certain patient groups via telehealth.

Predictive model for long COVID in children 3 months after a SARS-CoV-2 PCR test

BACKGROUND

To update and internally validate a model to predict children and young people (CYP) most likely to experience long COVID (i.e. at least one impairing symptom) 3 months after SARS-CoV-2 PCR testing and to determine whether the impact of predictors differed by SARS-CoV-2 status.

METHODS

Data from a nationally matched cohort of SARS-CoV-2 test-positive and test-negative CYP aged 11-17 years was used. The main outcome measure, long COVID, was defined as one or more impairing symptoms 3 months after PCR testing. Potential pre-specified predictors included SARS-CoV-2 status, sex, age, ethnicity, deprivation, quality of life/functioning (five EQ-5D-Y items), physical and mental health and loneliness (prior to testing) and number of symptoms at testing. The model was developed using logistic regression; performance was assessed using calibration and discrimination measures; internal validation was performed via bootstrapping and the final model was adjusted for overfitting.

RESULTS

A total of 7139 (3246 test-positives, 3893 test-negatives) completing a questionnaire 3 months post-test were included. 25.2% (817/3246) of SARS-CoV-2 PCR-positives and 18.5% (719/3893) of SARS-CoV-2 PCR-negatives had one or more impairing symptoms 3 months post-test. The final model contained SARS-CoV-2 status, number of symptoms at testing, sex, age, ethnicity, physical and mental health, loneliness and four EQ-5D-Y items before testing. Internal validation showed minimal overfitting with excellent calibration and discrimination measures (optimism-adjusted calibration slope: 0.96575; C-statistic: 0.83130).

CONCLUSIONS

We updated a risk prediction equation to identify those most at risk of long COVID 3 months after a SARS-CoV-2 PCR test which could serve as a useful triage and management tool for CYP during the ongoing pandemic. External validation is required before large-scale implementation.

Management and Clinical Outcome of Aortic Graft Infections: A Single-Center Retrospective Study

BACKGROUND

This study aimed to evaluate the outcome of various treatment options for aortic graft infection (AGI) patients and identify factors affecting their prognosis.

METHODS

The data of AGI patients from January 2008 to December 2019 were retrospectively collected and analyzed. The primary endpoints were 30-day mortality and perioperative complication-related morbidity; the secondary endpoints were re-infection (RI) rates, primary and secondary graft patency, overall mortality, duration of antibiotic therapy, and the number of antibiotic types used in treatment.

RESULTS

There was no significant difference in the 30-day mortality and perioperative-related complications between the conservative treatment, in-situ reconstruction (ISR), and extra-anatomic reconstruction (EAR) groups. The ISR group had lower re-infection rates and better overall survival rates than the EAR and conservative treatment groups. Different bypass graft conduits had no significant influence on the RI rate or primary and secondary graft patency. AGI patients infected with high-virulence pathogens had higher RI and overall mortality rates than those infected with low virulence pathogens, but this was not statistically significant. Initial procedures prior to the AGI also had no influence on the prognosis of AGI patients. Patients undergoing ISR or EAR surgery received antibiotic therapy for a longer duration than patients undergoing conservative treatment. Patients without RI received more types of antibiotics than patients with RI.

CONCLUSIONS

ISR had lower RI rates and better overall survival rates than EAR and conservative treatment and may be a better choice for patients with AGI. Several factors were found to have no influence on patients' prognosis however, further studies are required.

Walk the Talk: Current Evidence for Walking Recovery After Stroke, Future Pathways and a Mission for Research and Clinical Practice

Achieving safe, independent, and efficient walking is a top priority for stroke survivors to enable quality of life and future health. This narrative review explores the state of the science in walking recovery after stroke and potential for development. The importance of targeting walking capacity and performance is explored in relation to individual stroke survivor gait recovery, applying a common language, measurement, classification, prediction, current and future intervention development, and health care delivery. Findings are summarized in a model of current and future stroke walking recovery research and a mission statement is set for researchers and clinicians to drive the field forward to improve the lives of stroke survivors and their carers.

The power of integrating data: advancing pain research using meta-analysis

Publications related to pain research have increased significantly in recent years. The abundance of new evidence creates challenges staying up to date with the latest information. A comprehensive understanding of the literature is important for both clinicians and investigators involved in pain research. One commonly used method to combine and analyse data in health care research is meta-analysis. The primary aim of a meta-analysis is to quantitatively synthesise the results of multiple studies focused on the same research question. Meta-analysis is a powerful tool that can be used to advance pain research. However, there are inherent challenges when combining data from multiple sources. There are also numerous models and statistical considerations when undertaking a meta-analysis. This review aims to discuss the planning and preparation for completing a meta-analysis, review commonly used meta-analysis models, and evaluate the clinical implications of meta-analysis in pain research.

Anti-Müllerian hormone in guiding the selection of a freeze-all versus a fresh embryo transfer strategy: a cohort study

PURPOSE

To explore an interaction effect between serum anti-Müllerian hormone (AMH) levels and the relative treatment effect of a freeze-all versus a fresh embryo transfer strategy on live birth.

METHODS

This was a retrospective cohort study investigating couples with infertility and eligible for both freeze-all and fresh embryo transfer between 2017 and 2019. Women with an absolute indication for a freeze-all strategy were excluded. Multivariable fractional polynomial interaction analysis within a logistic regression model was used to evaluate whether the treatment effect of a freeze-all versus a fresh transfer strategy varied at different AMH levels. Non-linear interactions were also considered. The primary outcome was the live birth after the first transfer.

RESULTS

A total of 13,503 women underwent a fresh embryo transfer and 2247 women underwent a freeze-all strategy. Live birth rates were slightly higher in the freeze-all group compared to those in the fresh embryo transfer group (35% vs 33%). There was a non-linear interaction between baseline serum AMH levels and the relative treatment effect of a freeze-all strategy versus a fresh transfer strategy on live birth (P = 0.0161). The benefit on live birth from a freeze-all embryo transfer strategy was greatest in women with a high serum level (> 7 ng/ml). The interaction remained valid when different imputation methods were used.

CONCLUSION

As serum AMH level increased, there was a nonlinear increase in relative treatment effect of a freeze-only transfer versus a fresh transfer strategy on live birth, and such an effect reaches its maximum in women with high AMH levels.

Frailty and hearing loss: From association to causation

Background

Observational studies suggest that frailty is associated with hearing loss (HL) but with inconsistent results. This study aims to examine such association and to assess its causality.

Materials and methods

The cross-sectional data from the National Health and Nutrition Examination Survey (NHANES). Multivariate logistic regression models were used to assess the association between HL and frailty index (FI). Genetic variants associated with the FI and HL were obtained from a large genome-wide association study (GWAS) meta-analysis and UK Biobank GWAS. The inverse variance weighting (IVW) method was used to estimate causal effects. Sensitivity analyses were performed to further validate the robustness of results.

Results

In this cross-sectional analysis, results support the possibility that frailty may be associated with a higher risk of developing HL, with self-reported [odds ratio (OR) = 2.813; 95% CI, 2.386, 3.317; p < 0.001], speech frequency HL (OR = 1.975; 95% CI, 1.679–2.323; p < 0.001), and high frequency HL (OR = 1.748; 95% CI, 1.459–2.094; p < 0.001). In the adjusted model, frail participants remained at high risk of HL. Mendelian randomization (MR) studies showed a bidirectional causal association between genetically predicted FI and risk of HL (FI for exposure: OR = 1.051; 95% CI, 1.020–1.083; p = 0.001; HL for exposure: OR = 1.527; 95% CI, 1.227–1.901; p < 0.001).

Conclusion

Our observational study found that inter-individual differences in frailty were associated with the risk of developing HL. Genetic evidence suggests a potential bidirectional causal association between FI and HL. Furthermore, the potential mechanisms of this association require investigation.

Prognostic biomarkers of cutaneous melanoma

BACKGROUND/PURPOSE

Melanomas account for only approximately 4% of diagnosed skin cancers in the United States but are responsible for the majority of deaths caused by skin cancer. Both genetic factors and ultraviolet (UV) radiation exposure play a role in the development of melanoma. Although melanomas have a strong propensity to metastasize when diagnosed late, melanomas that are diagnosed and treated early pose a low mortality risk. In particular, the identification of patients with increased metastatic risk, who may benefit from early adjuvant therapies, is crucial, especially given the advent of new melanoma treatments. However, the accuracy of classic clinical and histological variables, including the Breslow thickness, presence of ulceration, and lymph node status, might not be sufficient to identify such individuals. Thus, there is a need for the development of additional prognostic melanoma biomarkers that can improve early attempts to stratify melanoma patients and reliably identify high-risk subgroups with the aim of providing effective personalized therapies.

METHODS

In our current work, we discuss and assess emerging primary melanoma tumor biomarkers and prognostic circulating biomarkers.

RESULTS

Several promising biomarkers show prognostic value (eg, exosomal MIA (ie, melanoma inhibitory activity), serum S100B, AMLo signatures, and mRNA signatures); however, the scarcity of reliable data precludes the use of these biomarkers in current clinical applications.

CONCLUSION

Further research is needed on several promising biomarkers for melanoma. Large-scale studies are warranted to facilitate the clinical translation of prognostic biomarker applications for melanoma in personalized medicine.

Risk-based stratified primary care for common musculoskeletal pain presentations (STarT MSK): a cluster-randomised, controlled trial

BACKGROUND

Risk-based stratified care shows clinical effectiveness and cost-effectiveness versus usual primary care for non-specific low back pain but is untested for other common musculoskeletal disorders. We aimed to test the clinical effectiveness and cost-effectiveness of point-of-care risk stratification (using Keele's STarT MSK Tool and risk-matched treatments) versus usual care for the five most common musculoskeletal presentations (back, neck, knee, shoulder, and multi-site pain).

METHODS

In this cluster-randomised, controlled trial in UK primary care with embedded qualitative and health economic studies we recruited patients from 24 general practices in the West Midlands region of England. Eligible patients were those aged 18 years or older whose general practitioner (GP) confirmed a consultation for a musculoskeletal presentation. General practices that consented to participate via a representative of the cluster were randomly assigned (1:1) to intervention or usual care, using stratified block randomisation. Researchers involved in data collection, outcome data entry, and statistical analysis were masked at both the cluster and individual participant level. Participating patients were told the study was examining GP treatment of common aches and pains and were not aware they were in a randomised trial. GPs in practices allocated to the intervention group were supported to deliver risk-based stratified care using a bespoke computer-based template, including the risk-stratification tool, and risk-matched treatment options for patients at low, medium, or high risk of poor disability or pain outcomes. There were 15 risk-matched treatment options. In the usual care group, patients with musculoskeletal pain consulting their GP received treatment as usual, typically including advice and education, medication, referral for investigations or tests, or referral to other services. The primary outcome was time-averaged pain intensity over 6 months. All analyses were done by intention to treat. The trial is registered with ISRCTN, ISRCTN15366334.

RESULTS

Between May 1, 2018, and April 30, 2019, 104 GPs from 24 practices (12 per study group) identified 2494 patients with musculoskeletal pain. 1211 (49%) participants consented to questionnaires (534 in the intervention group and 677 in the usual care group), with 1070 (88%) completing the follow-up questionnaire at 6 months. We found no significant difference in time-averaged pain intensity (mean(SD) mean 4·4 [SD 2·3] in the intervention group vs 4·6 [2·5] in the control group; adjusted mean difference -0·16, 95% CI -0·65 to 0·34) or in standardised function score (mean -0·06 [SD 0·94] in the intervention group vs 0·05 [1·04]; adjusted mean difference -0·07, 95% CI -0·22 to 0·08). No serious adverse events or adverse events were reported. Risk stratification received positive patient and clinician feedback.

INTERPRETATION

Risk stratification for patients in primary care with common musculoskeletal presentations did not lead to significant improvements in pain or function, although some aspects of GP decision making were affected, and GP and patients had positive experiences. The costs of risk-based stratified care were similar to usual care, and such a strategy only offers marginal changes in cost-effectiveness outcomes. The clinical implications from this trial are largely inconclusive.

FUNDING

National Institute for Health Research.

Preventing unscheduled hospitalisations from asthma: a retrospective cohort study using routine primary and secondary care data in the UK (The PUSH-Asthma Study)-protocol paper

INTRODUCTION

Asthma is the most common chronic respiratory disease in children and adults. Asthma results in significant disease-related morbidity, healthcare costs and, in some cases, death. Despite efforts through implementation of national guidelines to improve asthma care, the UK has one of the highest asthma-related morbidity and mortality rates in the western world. New approaches are necessary to prevent asthma attacks in children and adults. The objectives of this study are to assess the association between demographic and clinical factors and asthma-related hospital admissions in children and adults, describe the epidemiology of asthma phenotypes among hospital attenders, and externally validate existing asthma risk prediction models.

METHODS AND ANALYSIS

This is a retrospective cohort study of children and adults with asthma. Data will be extracted from the Clinical Practice Research Datalink (CPRD) Aurum database, which holds anonymised primary care data for over 13 million actively registered patients and covers approximately 19% of the UK population. The primary outcome will be asthma-related hospital admissions. The secondary outcomes will be prescriptions of short courses of oral corticosteroids (as a surrogate measure for asthma exacerbations), a composite outcome measure including hospital admissions and prescriptions of short courses of oral corticosteroids and delivery of asthma care management following hospital discharge. The primary analysis will use a Poisson regression model to assess the association between demographic and clinical risk factors and the primary and secondary outcomes. Latent class analysis will be used to identify distinct subgroups, which will further our knowledge on potential phenotypes of asthma among patients at high risk of asthma-related hospital admissions. A Concordance statistic (C-statistic) and logistic regression model will also be used to externally validate existing risk prediction models for asthma-related hospitalisations to allow for the optimal model to be identified and evaluated provide evidence for potential use of the optimal performing risk prediction model in primary care.

ETHICS AND DISSEMINATION

This study was approved by the CPRD Independent Scientific Advisory Committee (reference number: 21_000512). Findings from this study will be published in a peer-reviewed journal and disseminated at national and international conferences.

Black Box Prediction Methods in Sports Medicine Deserve a Red Card for Reckless Practice: A Change of Tactics is Needed to Advance Athlete Care

There is growing interest in the role of predictive analytics in sport, where such extensive data collection provides an exciting opportunity for the development and utilisation of prediction models for medical and performance purposes. Clinical prediction models have traditionally been developed using regression-based approaches, although newer machine learning methods are becoming increasingly popular. Machine learning models are considered 'black box'. In parallel with the increase in machine learning, there is also an emergence of proprietary prediction models that have been developed by researchers with the aim of becoming commercially available. Consequently, because of the profitable nature of proprietary systems, developers are often reluctant to transparently report (or make freely available) the development and validation of their prediction algorithms; the term 'black box' also applies to these systems. The lack of transparency and unavailability of algorithms to allow implementation by others of 'black box' approaches is concerning as it prevents independent evaluation of model performance, interpretability, utility, and generalisability prior to implementation within a sports medicine and performance environment. Therefore, in this Current Opinion article, we: (1) critically examine the use of black box prediction methodology and discuss its limited applicability in sport, and (2) argue that black box methods may pose a threat to delivery and development of effective athlete care and, instead, highlight why transparency and collaboration in prediction research and product development are essential to improve the integration of prediction models into sports medicine and performance.

The disease severity index for inflammatory bowel disease is associated with psychological symptoms and quality of life, and predicts a more complicated disease course

BACKGROUND

The Disease Severity Index (DSI) is a novel tool to predict disease severity in inflammatory bowel disease (IBD). However, its ability to predict disease complications and the presence of psychosocial comorbidity is unclear.

AIMS

To assess prospectively associations between the DSI and psychological symptoms, quality-of-life (QoL) and disease outcomes in an IBD cohort.

METHODS

Patients with IBD undergoing ileocolonoscopy were followed prospectively for 12 months. DSI, psychological symptoms (perceived stress (PSS-10), depression (PHQ-9), anxiety (GAD-7)) and QoL (IBDQ-32) scores were assessed at baseline. Logistic regression identified variables predicting a complicated IBD course at 12 months (composite outcome of need for escalation of biological/immunomodulator for disease relapse, recurrent corticosteroid use, IBD-related hospitalisation and surgery). Receiver operating characteristics (ROC) analysis identified optimal DSI thresholds predicting a complicated disease course and multivariable logistic regression assessed the risk of reaching this outcome.

RESULTS

One hundred and seventy-two patients were recruited (100 Crohn's disease, 91 female). Median DSI was 21 (IQR 11-32) and 97 patients had endoscopically active disease at baseline. The DSI was significantly higher in patients with symptoms of moderate-severe stress (PSS-10 > 14, p < 0.01), depression (PHQ-9 ≥ 10, p < 0.01), anxiety (GAD-7 ≥ 10, p < 0.05) and impaired quality-of-life (IBDQ-32 < 168, p < 0.01). Only the baseline DSI (OR 1.05, p < 0.01) and endoscopically active disease (OR 6.12, p < 0.01) were associated with a complicated IBD course. A DSI > 23 was strongly predictive of a complicated IBD course (OR 8.31, p < 0.001).

CONCLUSIONS

The DSI is associated with psychological distress, impaired QoL and predicts a more complicated disease course in patients with IBD.

Comparing "people-like-me" and linear mixed model predictions of functional recovery following knee arthroplasty

OBJECTIVE

Prediction models can be useful tools for monitoring patient status and personalizing treatment in health care. The goal of this study was to compare the relative strengths and weaknesses of 2 different approaches for predicting functional recovery after knee arthroplasty: a neighbors-based "people-like-me" (PLM) approach and a linear mixed model (LMM) approach.

MATERIALS AND METHODS

We used 2 distinct datasets to train and then test PLM and LMM prediction approaches for functional recovery following knee arthroplasty. We used the Timed Up and Go (TUG)-a common test of mobility-to operationalize physical function. Both approaches used patient characteristics and baseline postoperative TUG values to predict TUG recovery from days 1-425 following surgery. We then compared the accuracy and precision of PLM and LMM predictions.

RESULTS

A total of 317 patient records with 1379 TUG observations were used to train PLM and LMM approaches, and 456 patient records with 1244 TUG observations were used to test the predictions. The approaches performed similarly in terms of mean squared error and bias, but the PLM approach provided more accurate and precise estimates of prediction uncertainty.

DISCUSSION AND CONCLUSION

Overall, the PLM approach more accurately and precisely predicted TUG recovery following knee arthroplasty. These results suggest PLM predictions may be more clinically useful for monitoring recovery and personalizing care following knee arthroplasty. However, clinicians and organizations seeking to use predictions in practice should consider additional factors (eg, resource requirements) when selecting a prediction approach.

Validation of the German version of the STarT-MSK-Tool: A cohort study with patients from physiotherapy clinics

BACKGROUND

The STarT-MSK-Tool is an adaptation of the well established STarT-Back-Tool, used to risk-stratify patients with a wider range of musculoskeletal presentations.

OBJECTIVE

To formally translate and cross-culturally adapt the Keele STarT-MSK risk stratification tool into German (STarT-MSKG) and to establish its reliability and validity.

METHODS

A formal, multi-step, forward and backward translation approach was used. To assess validity patients aged ≥18 years, with acute, subacute or chronic musculoskeletal presentations in the lumbar spine, hip, knee, shoulder, or neck were included. The prospective cohort was used with initial data collected electronically at the point-of-consultation. Retest and 6-month follow-up questionnaires were sent by email. Test-retest reliability, construct validity, discriminative ability, predictive ability and floor or ceiling effects were analysed using intraclass correlation coefficient, and comparisons with a reference standard (Orebro-Musculoskeletal-Pain-Questionnaire: OMPQ) using correlations, ROC-curves and regression models.

RESULTS

The participants' (n = 287) mean age was 47 (SD = 15.8) years, 51% were female, with 48.8% at low, 43.6% at medium, and 7.7% at high risk. With ICC = 0.75 (95% CI 0.69; 0.81) test-retest-reliability was good. Construct validity was good with correlations for the STarT-MSKG-Tool against the OMPQ-Tool of rs = 0.74 (95% CI 0.68, 0.79). The ability of the tool [comparison OMPQ] to predict 6-month pain and disability was acceptable with AUC = 0.77 (95% CI 0.71, 0.83) [OMPQ = 0.74] and 0.76 (95% CI 0.69, 0.82) [OMPQ = 0.72] respectively. However, the explained variance (linear/logistic regression) for predicting 6-month pain (21% [OMPQ = 17%]/logistic = 29%) and disability (linear = 20%:[OMPQ = 19%]/logistic = 26%), whilst being comparable to the existing OMPQ reference standard, fell short of the a priori target of ≥30%.

CONCLUSIONS

The German version of the STarT-MSK-Tool is a valid instrument for use across multiple musculoskeletal conditions and is availabe for use in clinical practice. Comparison with the OMPQ suggests it is a good alternative.

The association between person and fracture characteristics with patient reported outcome after ankle fractures in adults: A systematic review

BACKGROUND

The incidence of ankle fractures is increasing and the clinical outcome is highly variable.

QUESTION

What person and fracture characteristics are associated with patient reported outcomes after surgically or conservatively managed ankle fractures in adults?

DATA SOURCES

Medline, EMBASE, and Allied and Complimentary Health Medical Database (AMED) databases were searched from the earliest available date until 16th July 2020.

STUDY SELECTION

Prognostic factors studies recruiting adults of age 18 years or older with a radiologically confirmed ankle fracture, and evaluating function, symptoms and quality of life by patient reported outcome measures, were included.

STUDY APPRAISAL/SYNTHESIS METHODS

Risk of bias of individual studies was assessed by the Quality in Prognostic Factors Studies tool. Correlation coefficients were calculated and data were analysed using narrative synthesis.

RESULTS

Fifty-one phase 1 explanatory studies with 6177 participants met the inclusion criteria. Thirty-one studies were rated as high risk of bias using the Quality in Prognostic Factors Studies tool. There was low quality evidence that age, body mass index, American Society of Anesthesiologists classification and pre-injury mobility were associated with function, and low to moderate quality evidence that age, smoking and American Society of Anesthesiologists classification were associated with quality of life. No person characteristics were associated with symptoms and no fracture characteristics were associated with any outcomes.

CONCLUSION

There was low to moderate quality evidence that person characteristics may be associated with patient reported function and quality of life following ankle fracture.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO registration number CRD42020184830.

Development and content validity of a rating scale for the pain and disability drivers management model

Background

Establishing the biopsychosocial profile of patients with low back pain (LBP) is essential to personalized care. The Pain and Disability Drivers Management model (PDDM) has been suggested as a useful framework to help clinicians establish this biopsychosocial profile. Yet, there is no tool to facilitate its integration into clinical practice. Thus, the aim of this study is to develop a rating scale and validate its content, to rapidly establish the patient’s biopsychosocial profile, based on the five domains of the PDDM.

Methods

The tool was developed in accordance with the principles of the COSMIN methodology. We conducted three steps: 1) item generation from a comprehensive review, 2) refinement of the scale with clinicians’ feedback, and 3) statistical analyses to assess content validity.

To validate the item assessing with Likert scales, we performed Item level-Content Validity Index (I-CVI) analyses on three criteria (clarity, presentation and clinical applicability) with an a priori threshold of > 0.78. We conducted Average-Content Validity Index (Ave-CVI) analyses to validate the overall scale with a threshold of > 0.9.

Results

In accordance with the PDDM, we developed a 5-item rating scale (1 per domain) with 4 score options. We selected clinical instruments to screen for the presence or absence of problematic issues within each category of the 5 domains. Forty-two participants provided feedback to refine the scale’s clarity, presentation, and clinical applicability. The statistical analysis of the latest version presented I-CVI above the threshold for each item (I-CVI ranged between 0.94 and 1). Analysis of the overall scale supported its validation (Ave-CVI = 0.96 [0.93;0.98]).

Conclusion

From the 51 biopsychosocial elements contained within the 5 domains of the PDDM, we developed a rating scale that allows to rapidly screen for problematic issues within each category of the PDDM’s 5 domains. Involving clinicians in the process allowed us to validate the content of the first scale to establish the patient’s biopsychosocial profile for people with low back pain. Future steps will be necessary to continue the psychometric properties analysis of this rating scale.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40945-022-00137-2.

Prognostic factors associated with development of infected necrosis in patients with acute necrotizing or severe pancreatitis-A systematic review and meta-analysis

PURPOSE

Acute pancreatitis is a potentially life-threatening condition with a wide spectrum of clinical presentation and illness severity. An infection of pancreatic necrosis (IPN) results in a more than twofold increase in mortality risk as compared with patients with sterile necrosis. We sought to identify prognostic factors for the development of IPN among adult patients with severe or necrotizing pancreatitis.

METHODS

We conducted this prognostic review in accordance with systematic review methodology guidelines. We searched six databases from inception through March 21, 2021. We included English language studies describing prognostic factors associated with the development of IPN. We pooled unadjusted odds ratio (uOR) and adjusted odds ratios (aOR) for prognostic factors using a random-effects model. We assessed risk of bias using the Quality in Prognosis Studies tool and certainty of evidence using the GRADE approach.

RESULTS

We included 31 observational studies involving 5,210 patients. Factors with moderate or higher certainty of association with increased IPN risk include older age (uOR, 2.19; 95% confidence interval [CI], 1.39-3.45, moderate certainty), gallstone etiology (aOR, 2.35; 95% CI, 1.36-4.04, high certainty), greater than 50% necrosis of the pancreas (aOR, 3.61; 95% CI, 2.15-6.04, high certainty), delayed enteral nutrition (aOR, 2.09; 95% CI, 1.26-3.47, moderate certainty), multiple or persistent organ failure (aOR, 11.71; 95% CI, 4.97-27.56, high certainty), and invasive mechanical ventilation (uOR, 12.24; 95% CI, 2.28-65.67, high certainty).

CONCLUSION

This meta-analysis confirms the association between several clinical early prognostic factors and the risk of IPN development among patients with severe or necrotizing pancreatitis. These findings provide the foundation for the development of an IPN risk stratification tool to guide more targeted clinical trials for prevention or early intervention strategies.

LEVEL OF EVIDENCE

Systematic review and meta-analysis, Level IV.

Mindfulness-based programmes for mental health promotion in adults in non-clinical settings: protocol of an individual participant data meta-analysis of randomised controlled trials

INTRODUCTION

With mental ill health listed as a top cause of global disease burden, there is an urgent need to prioritise mental health promotion programmes. Mindfulness-based programmes (MBPs) are being widely implemented to reduce stress in non-clinical settings. In a recent aggregate-level meta-analysis we found that, compared with no intervention, these MBPs reduce average psychological distress. However, heterogeneity between studies impedes generalisation of effects across every setting. Study-level effect modifiers were insufficient to reduce heterogeneity; studying individual-level effect modifiers is warranted. This requires individual participant data (IPD) and larger samples than those found in existing individual trials.

METHODS AND ANALYSIS

We propose an IPD meta-analysis. Our primary aim is to see if, and how, baseline psychological distress, gender, age, education and dispositional mindfulness moderate the effect of MBPs on distress. We will search 13 databases for good-quality randomised controlled trials comparing in-person, expert-defined MBPs in non-clinical settings with passive controls. Two researchers will independently select, extract and appraise trials using the revised Cochrane risk-of-bias tool. Anonymised IPD of eligible trials will be sought from authors, who will be invited to collaborate.The primary outcome will be psychological distress measured using psychometrically validated questionnaires at 1-6 months after programme completion. Pairwise random-effects two-stage IPD meta-analyses will be conducted. Moderator analyses will follow a 'deft' approach. We will estimate subgroup-specific intervention effects. Secondary outcomes and sensitivity analyses are prespecified. Multiple imputation strategies will be applied to missing data.

ETHICS AND DISSEMINATION

The findings will refine our knowledge on the effectiveness of MBPs and help improve the targeting of MBPs in non-clinical settings. They will be shared in accessible formats with a range of stakeholders. Public and professional stakeholders are being involved in the planning, conduct and dissemination of this project.

PROSPERO REGISTRATION NUMBER

CRD42020200117.

Development and evaluation of a search filter to identify prognostic factor studies in Ovid MEDLINE

Background

Systematic reviews (SRs) are valuable resources as they address specific clinical questions by summarizing all existing relevant studies. However, finding all information to include in systematic reviews can be challenging. Methodological search filters have been developed to find articles related to specific clinical questions. To our knowledge, no filter exists for finding studies on the role of prognostic factor (PF). We aimed to develop and evaluate a search filter to identify PF studies in Ovid MEDLINE that has maximum sensitivity.

Methods

We followed current recommendations for the development of a search filter by first identifying a reference set of PF studies included in relevant systematic reviews on the topic, and by selecting search terms using a word frequency analysis complemented with an expert panel discussion. We evaluated filter performance using the relative recall methodology.

Results

We constructed a reference set of 73 studies included in six systematic reviews from a larger sample. After completing a word frequency analysis using the reference set studies, we compiled a list of 80 of the frequent methodological terms. This list of terms was evaluated by the Delphi panel for inclusion in the filter, resulting in a final set of 8 appropriate terms. The consecutive connection of these terms with the Boolean operator OR produced the filter. We then evaluated the filter using the relative recall method against the reference set, comparing the references included in the SRs with our new search using the filter. The overall sensitivity of the filter was calculated to be 95%, while the overall specificity was 41%. The precision of the filter varied considerably, ranging from 0.36 to 17%. The NNR (number needed to read) value varied largely from 6 to 278. The time saved by using the filter ranged from 13–70%.

Conclusions

We developed a search filter for OVID-Medline with acceptable performance that could be used in systematic reviews of PF studies. Using this filter could save as much as 40% of the title and abstract screening task. The specificity of the filter could be improved by defining additional terms to be included, although it is important to evaluate any modification to guarantee the filter is still highly sensitive.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12874-022-01595-9.

Study protocol for the development and internal validation of Schizophrenia Prediction of Resistance to Treatment (SPIRIT): a clinical tool for predicting risk of treatment resistance to antipsychotics in first-episode schizophrenia

INTRODUCTION

Treatment-resistant schizophrenia (TRS) is associated with significant impairment of functioning and high treatment costs. Identification of patients at high risk of TRS at the time of their initial diagnosis may significantly improve clinical outcomes and minimise social and functional disability. We aim to develop a prognostic model for predicting the risk of developing TRS in patients with first-episode schizophrenia and to examine its potential utility and acceptability as a clinical decision tool.

METHODS AND ANALYSIS

We will use two well-characterised longitudinal UK-based first-episode psychosis cohorts: Aetiology and Ethnicity in Schizophrenia and Other Psychoses and Genetics and Psychosis for which data have been collected on sociodemographic and clinical characteristics. We will identify candidate predictors for the model based on current literature and stakeholder consultation. Model development will use all data, with the number of candidate predictors restricted according to available sample size and event rate. A model for predicting risk of TRS will be developed based on penalised regression, with missing data handled using multiple imputation. Internal validation will be undertaken via bootstrapping, obtaining optimism-adjusted estimates of the model's performance. The clinical utility of the model in terms of clinically relevant risk thresholds will be evaluated using net benefit and decision curves (comparative to competing strategies). Consultation with patients and clinical stakeholders will determine potential thresholds of risk for treatment decision-making. The acceptability of embedding the model as a clinical tool will be explored using qualitative focus groups with up to 20 clinicians in total from early intervention services. Clinicians will be recruited from services in Stafford and London with the focus groups being held via an online platform.

ETHICS AND DISSEMINATION

The development of the prognostic model will be based on anonymised data from existing cohorts, for which ethical approval is in place. Ethical approval has been obtained from Keele University for the qualitative focus groups within early intervention in psychosis services (ref: MH-210174). Suitable processes are in place to obtain informed consent for National Health Service staff taking part in interviews or focus groups. A study information sheet with cover letter and consent form have been prepared and approved by the local Research Ethics Committee. Findings will be shared through peer-reviewed publications, conference presentations and social media. A lay summary will be published on collaborator websites.

Investigating treatment-effect modification by a continuous covariate in IPD meta-analysis: an approach using fractional polynomials

BACKGROUND

In clinical trials, there is considerable interest in investigating whether a treatment effect is similar in all patients, or that one or more prognostic variables indicate a differential response to treatment. To examine this, a continuous predictor is usually categorised into groups according to one or more cutpoints. Several weaknesses of categorization are well known. To avoid the disadvantages of cutpoints and to retain full information, it is preferable to keep continuous variables continuous in the analysis. To handle this issue, the Subpopulation Treatment Effect Pattern Plot (STEPP) was proposed about two decades ago, followed by the multivariable fractional polynomial interaction (MFPI) approach. Provided individual patient data (IPD) from several studies are available, it is possible to investigate for treatment heterogeneity with meta-analysis techniques. Meta-STEPP was recently proposed and in patients with primary breast cancer an interaction of estrogen receptors with chemotherapy was investigated in eight randomized controlled trials (RCTs).

METHODS

We use data from eight randomized controlled trials in breast cancer to illustrate issues from two main tasks. The first task is to derive a treatment effect function (TEF), that is, a measure of the treatment effect on the continuous scale of the covariate in the individual studies. The second is to conduct a meta-analysis of the continuous TEFs from the eight studies by applying pointwise averaging to obtain a mean function. We denote the method metaTEF. To improve reporting of available data and all steps of the analysis we introduce a three-part profile called MethProf-MA.

RESULTS

Although there are considerable differences between the studies (populations with large differences in prognosis, sample size, effective sample size, length of follow up, proportion of patients with very low estrogen receptor values) our results provide clear evidence of an interaction, irrespective of the choice of the FP function and random or fixed effect models.

CONCLUSIONS

In contrast to cutpoint-based analyses, metaTEF retains the full information from continuous covariates and avoids several critical issues when performing IPD meta-analyses of continuous effect modifiers in randomised trials. Early experience suggests it is a promising approach.

TRIAL REGISTRATION

Not applicable.

How Do We Predict a Patient's Disease Course and Whether They Will Respond to Specific Treatments?

Gastroenterologists will be all too familiar with the difficult decisions that managing inflammatory bowel disease often presents. How aggressively should I treat this patient? Do I expect them to have a mild or aggressive form of disease? Do they need a biologic? If so, which one? And when should I start it? The reality is that the answers that would be right for one patient might be disastrous for another. The growing therapeutic armamentarium will only make these decisions more difficult, and yet, we have seen how other specialties have begun to use the molecular heterogeneity in their diseases to provide some answers. Here, we review the progress that has been made in predicting the future for any given patient with inflammatory bowel disease-whether that is the course of disease that they will experience or whether or not they will respond to, or indeed tolerate, a particular therapy.

New horizons in evidence-based care for older people: individual participant data meta-analysis

Evidence-based decisions on clinical and cost-effectiveness of interventions are ideally informed by meta-analyses of intervention trial data. However, when undertaken, such meta-analyses in ageing research have typically been conducted using standard methods whereby summary (aggregate) data are extracted from published trial reports. Although meta-analysis of aggregate data can provide useful insights into the average effect of interventions within a selected trial population, it has limitations regarding robust conclusions on which subgroups of people stand to gain the greatest benefit from an intervention or are at risk of experiencing harm. Future evidence synthesis using individual participant data from ageing research trials for meta-analysis could transform understanding of the effectiveness of interventions for older people, supporting evidence-based and sustainable commissioning. A major advantage of individual participant data meta-analysis (IPDMA) is that it enables examination of characteristics that predict treatment effects, such as frailty, disability, cognitive impairment, ethnicity, gender and other wider determinants of health. Key challenges of IPDMA relate to the complexity and resources needed for obtaining, managing and preparing datasets, requiring a meticulous approach involving experienced researchers, frequently with expertise in designing and analysing clinical trials. In anticipation of future IPDMA work in ageing research, we are establishing an international Ageing Research Trialists collective, to bring together trialists with a common focus on transforming care for older people as a shared ambition across nations.

Do recommended interventions widen or narrow inequalities in musculoskeletal health? An equity-focussed systematic review of differential effectiveness

Background

It is unclear whether seven interventions recommended by Public Health England for preventing and managing common musculoskeletal conditions reduce or widen health inequalities in adults with musculoskeletal conditions.

Methods

We used citation searches of Web of Science (date of ‘parent publication’ for each intervention to April 2021) to identify original research articles reporting subgroup or moderator analyses of intervention effects by social stratifiers defined using the PROGRESS-Plus frameworks. Randomized controlled trials, controlled before-after studies, interrupted time series, systematic reviews presenting subgroup/stratified analyses or meta-regressions, individual participant data meta-analyses and modelling studies were eligible. Two reviewers independently assessed the credibility of effect moderation claims using Instrument to assess the Credibility of Effect Moderation Analyses. A narrative approach to synthesis was used (PROSPERO registration number: CRD42019140018).

Results

Of 1480 potentially relevant studies, seven eligible analyses of single trials and five meta-analyses were included. Among these, we found eight claims of potential differential effectiveness according to social characteristics, but none that were judged to have high credibility.

Conclusions

In the absence of highly credible evidence of differential effectiveness in different social groups, and given ongoing national implementation, equity concerns may be best served by investing in monitoring and action aimed at ensuring fair access to these interventions.

Protocol for the implementation of a stepped-care model to address fear of cancer recurrence in patients previously diagnosed with early-stage (0-II) melanoma

INTRODUCTION

Fear of cancer recurrence (FCR) is commonly reported by patients diagnosed with early-stage (0-II) melanoma and can have a significant impact on daily functioning. This study will pilot the implementation of the Melanoma Care Program, an evidence-based, psychological intervention to reduce FCR, into routine practice, using a stepped-care model.

METHODS AND ANALYSIS

Intervention effectiveness and level of implementation will be investigated using a hybrid type I design. Between 4 weeks before and 1 week after their next dermatological appointment, patients with melanoma will be invited to complete the Fear of Cancer Recurrence Inventory Short-Form, measuring self-reported FCR severity. Using a stepped-care model, clinical cut-off points will guide the level of support offered to patients. This includes: (1) usual care, (2) Melanoma: Questions and Answers psychoeducational booklet, and (3) three or five psychotherapeutic telehealth sessions. This longitudinal, mixed-methods pilot implementation study aims to recruit 108 patients previously diagnosed with stage 0-II melanoma. The primary effectiveness outcome is change in FCR severity over time. Secondary effectiveness outcomes include change in anxiety, depression, stress, health-related quality of life and melanoma-related knowledge over time. All outcomes are measured at baseline, within 1 week of the final telehealth session, and 6 and 12 months post-intervention. Implementation stakeholders at each study site and interested patients will provide feedback on intervention acceptability and appropriateness. Implementation stakeholders will also provide feedback on intervention cost, feasibility, fidelity and sustainability. These outcomes will be measured throughout implementation, using questionnaires and semistructured interviews/expert group discussions. Descriptive statistics, linear mixed-effects regression and thematic analysis will be used to analyse study data.

ETHICS AND DISSEMINATION

Ethics approval was granted by the Sydney Local Health District-Royal Prince Alfred Zone (2020/ETH02518), protocol number: X20-0495. Results will be disseminated through peer-reviewed journals, conference presentations, social media and result summaries distributed to interested participants. TRIAL REGISTRATION DETAILS: (ACTRN12621000145808).

Scoring systems for the management of oncological hepato-pancreato-biliary patients

Oncological scoring systems in surgery are used as evidence-based decision aids to best support management through assessing prognosis, effectiveness and recurrence. Currently, the use of scoring systems in the hepato-pancreato-biliary (HPB) field is limited as concerns over precision and applicability prevent their widespread clinical implementation. The aim of this review was to discuss clinically useful oncological scoring systems for surgical management of HPB patients. A narrative review was conducted to appraise oncological HPB scoring systems. Original research articles of established and novel scoring systems were searched using Google Scholar, PubMed, Cochrane, and Ovid Medline. Selected models were determined by authors. This review discusses nine scoring systems in cancers of the liver (CLIP, BCLC, ALBI Grade, RETREAT, Fong's score), pancreas (Genç's score, mGPS), and biliary tract (TMHSS, MEGNA). Eight models used exclusively objective measurements to compute their scores while one used a mixture of both subjective and objective inputs. Seven models evaluated their scoring performance in external populations, with reported discriminatory c-statistic ranging from 0.58 to 0.82. Selection of model variables was most frequently determined using a combination of univariate and multivariate analysis. Calibration, another determinant of model accuracy, was poorly reported amongst nine scoring systems. A diverse range of HPB surgical scoring systems may facilitate evidence-based decisions on patient management and treatment. Future scoring systems need to be developed using heterogenous patient cohorts with improved stratification, with future trends integrating machine learning and genetics to improve outcome prediction.

REDACS: Regional emergency-driven adaptive cluster sampling for effective COVID-19 management

As COVID-19 is spreading, national agencies need to monitor and track several metrics. Since we do not have perfect testing programs on the hand, one needs to develop an advanced sampling strategies for prevalence study, control and management. Here we introduce REDACS: Regional emergency-driven adaptive cluster sampling for effective COVID-19 management and control and justify its usage for COVID-19. We show its advantages over classical massive individual testing sampling plans. We also point out how regional and spatial heterogeneity underlines proper sampling. Fundamental importance of adaptive control parameters from emergency health stations and medical frontline is outlined. Since the Northern hemisphere entered Autumn and Winter season (this paper was originally submitted in November 2020), practical illustration from spatial heterogeneity of Chile (Southern hemisphere, which already experienced COVID-19 winter outbreak peak) is underlying the importance of proper regional heterogeneity of sampling plan. We explain the regional heterogeneity by microbiological backgrounds and link it to behavior of Lyapunov exponents. We also discuss screening by antigen tests from the perspective of "on the fly" biomarker validation, i.e., during the screening.

Mastering Prognostic Tools: An Opportunity to Enhance Personalized Care and to Optimize Clinical Outcomes in Physical Therapy

In health care, clinical decision making is typically based on diagnostic findings. Rehabilitation clinicians commonly rely on pathoanatomical diagnoses to guide treatment and define prognosis. Targeting prognostic factors is a promising way for rehabilitation clinicians to enhance treatment decision-making processes, personalize rehabilitation approaches, and ultimately improve patient outcomes. This can be achieved by using prognostic tools that provide accurate estimates of the probability of future outcomes for a patient in clinical practice. Most literature reviews of prognostic tools in rehabilitation have focused on prescriptive clinical prediction rules. These studies highlight notable methodological issues and conclude that these tools are neither valid nor useful for clinical practice. This has raised the need to open the scope of research to understand what makes a quality prognostic tool that can be used in clinical practice. Methodological guidance in prognosis research has emerged in the last decade, encompassing exploratory studies on the development of prognosis and prognostic models. Methodological rigor is essential to develop prognostic tools, because only prognostic models developed and validated through a rigorous methodological process should guide clinical decision making. This Perspective argues that rehabilitation clinicians need to master the identification and use of prognostic tools to enhance their capacity to provide personalized rehabilitation. It is time for prognosis research to look for prognostic models that were developed and validated following a comprehensive process before being simplified into suitable tools for clinical practice. New models, or rigorous validation of current models, are needed. The approach discussed in this Perspective offers a promising way to overcome the limitations of most models and provide clinicians with quality tools for personalized rehabilitation approaches.

IMPACT

Prognostic research can be applied to clinical rehabilitation; this Perspective proposes solutions to develop high-quality prognostic models to optimize patient outcomes.

Development and comparison of 1-year survival models in patients with primary bone sarcomas: External validation of a Bayesian belief network model and creation and external validation of a new gradient boosting machine model

Background:

Bone sarcomas often present late with advanced stage at diagnosis and an according, varying short-term survival. In 2016, Nandra et al. generated a Bayesian belief network model for 1-year survival in patients with bone sarcomas. The purpose of this study is: (1) to externally validate the prior 1-year Bayesian belief network prediction model for survival in patients with bone sarcomas and (2) to develop a gradient boosting machine model using Nandra et al.’s cohort and evaluate whether the gradient boosting machine model outperforms the Bayesian belief network model when externally validated in an independent Danish population cohort.

Material and Methods:

The training cohort comprised 3493 patients newly diagnosed with bone sarcoma from the institutional prospectively maintained database at the Royal Orthopaedic Hospital, Birmingham, UK. The validation cohort comprised 771 patients with newly diagnosed bone sarcoma included from the Danish Sarcoma Registry during January 1, 2000–June 22, 2016. We performed area under receiver operator characteristic curve analysis, Brier score and decision curve analysis to evaluate the predictive performance of the models.

Results:

External validation of the Bayesian belief network 1-year prediction model demonstrated an area under receiver operator characteristic curve of 68% (95% confidence interval, 62%-73%). Area under receiver operator characteristic curve of the gradient boosting machine model demonstrated: 75% (95% confidence interval: 70%-80%), overall model performance by the Brier score was 0.09 (95% confidence interval: 0.077–0.11) and decision curve analysis demonstrated a positive net benefit for threshold probabilities above 0.5. External validation of the developed gradient boosting machine model demonstrated an area under receiver operator characteristic curve of 63% (95% confidence interval: 57%-68%), and the Brier score was 0.14 (95% confidence interval: 0.12–0.16).

Conclusion:

External validation of the 1-year Bayesian belief network survival model yielded a poor outcome based on a Danish population cohort validation. We successfully developed a gradient boosting machine 1-year survival model. The gradient boosting machine did not outperform the Bayesian belief network model based on external validation in a Danish population-based cohort.

Case Reporting in Homeopathy-An Overview of Guidelines and Scientific Tools

Case reports have been of central importance to the development of homeopathy over the past 200 years. With a special focus on homeopathy, we give an overview on guidelines and tools that may help to improve the quality of case reports. Reporting guidelines such as CARE (Case Report), HOM-CASE (Homeopathic Clinical Case Reports), and the WissHom Documentation Standard help to improve the quality of reporting and strengthen the scientific value of a case report. Additional scientific tools such as prospective outcome assessment, prognostic factor research, cognition-based medicine, and the Modified Naranjo Criteria for Homeopathy (MONARCH) score may be helpful in improving case documentation and evaluation.

Radiomics Nomogram for Predicting Locoregional Failure in Locally Advanced Non-small Cell Lung Cancer Treated with Definitive Chemoradiotherapy

RATIONALE AND OBJECTIVES

To develop and validate a computed tomography (CT)-based radiomics nomogram for predicting locoregional failure (LRF) in patients with locally advanced non-small cell lung cancer (NSCLC) treated with definitive chemoradiotherapy (CRT).

MATERIALS AND METHODS

A total of 141 patients with locally advanced NSCLC treated with definitive CRT from January 2014 to December 2017 were included and divided into testing cohort (n = 100) and validation (n = 41) cohort. Radiomics features were extracted from pretreatment contrast enhanced CT. The least absolute shrinkage and selection operator logistic regression was processed to select predictive features from the testing cohort and constructed a radiomics signature. Clinical characteristics and the radiomics signature were analyzed using univariable and multivariate Cox regression. The radiomics nomogram was established with the radiomics signature and independent clinical factors. Harrell's C-index, calibration curves and decision curves were used to assess the performance of the radiomics nomogram.

RESULTS

The radiomics signature, which consisted of eight selected features, was an independent factor of LRF. The clinical predictors of LRF were the histologic type and clinical stage. The radiomics nomogram combined with the radiomics signature and clinical prognostic factors showed good performance with C-indexes of 0.796 (95% confidence interval [CI]: 0.709-0.883) and 0.756 (95% CI: 0.674-0.838) in the testing and validation cohorts respectively. Additionally, the combined nomogram resulted in better performance (p < 0.001) for the estimation of LRF than the nomograms with the radiomics signature (C-index: 0.776; 95% CI: 0.686-0.866) or clinical predictors (C-index: 0.641; 95% CI: 0.542-0.740) alone.

CONCLUSION

The radiomics nomogram provided the best performance for LRF prediction in patients with locally advanced NSCLC, which may help optimize individual treatments.

Stratified Care vs Stepped Care for Depression: A Cluster Randomized Clinical Trial

IMPORTANCE

Depression is a major cause of disability worldwide. Although empirically supported treatments are available, there is scarce evidence on how to effectively personalize psychological treatment selection.

OBJECTIVE

To compare the clinical effectiveness and cost-effectiveness of 2 treatment selection strategies: stepped care and stratified care.

DESIGN, SETTING, AND PARTICIPANTS

This multisite, cluster randomized clinical trial recruited participants from the English National Health Service from July 5, 2018, to February 1, 2019. Thirty clinicians working across 4 psychological therapy services were randomly assigned to provide stratified (n = 15) or stepped (n = 15) care. In stepped care, patients sequentially access low-intensity guided self-help followed by high-intensity psychotherapy. In stratified care, patients are matched with either low- or high-intensity treatments at initial assessment. Data were analyzed from May 18, 2020, to October 13, 2021, using intention-to-treat principles.

INTERVENTIONS

All clinicians used the same interview schedule to conduct initial assessments with patients seeking psychological treatment for common mental disorders, but those in the stratified care group received a personalized treatment recommendation for each patient generated by a machine learning algorithm. Eligible patients received either stratified or stepped care (ie, treatment as usual).

MAIN OUTCOMES AND MEASURES

The preregistered outcome was posttreatment reliable and clinically significant improvement (RCSI) of depression symptoms (measured using the 9-item Patient Health Questionnaire). The RCSI outcome was compared between groups using logistic regression adjusted for baseline severity. Cost-effectiveness analyses compared incremental costs and health outcomes of the 2 treatment pathways.

RESULTS

A total of 951 patients were included (618 women among 950 with data available [65.1%]; mean [SD] age, 38.27 [14.53] years). The proportion of cases of RCSI was significantly higher in the stratified care arm compared with the stepped care arm (264 of 505 [52.3%] vs 134 of 297 [45.1%]; odds ratio, 1.40 [95% CI, 1.04-1.87]; P = .03). Stratified care was associated with a higher mean additional cost per patient (£104.5 [95% CI, £67.5-£141.6] [$139.83 (95% CI, $90.32-$189.48)]; P < .001) because more patients accessed high-intensity treatments (332 of 583 [56.9%] vs 107 of 368 [29.1%]; χ2 = 70.51; P < .001), but this additional cost resulted in an approximately 7% increase in the probability of RCSI.

CONCLUSIONS AND RELEVANCE

In this cluster randomized clinical trial of adults with common mental disorders, stratified care was efficacious and cost-effective for the treatment of depression symptoms compared with stepped care. Stratified care can improve depression treatment outcomes at a modest additional cost.

TRIAL REGISTRATION

isrctn.org Identifier: ISRCTN11106183.

Development of a clinical prediction model to inform clinical decision making for classification of patients with sciatica, based on their clinical characteristics, in the Greek health system: protocol for a prospective predictive exploratory study

INTRODUCTION

Sciatica is one of the most common reasons for seeking healthcare for musculoskeletal pain. Sciatica is primarily considered as neuropathic in nature when neural tissue in the low back is compromised, but sometimes other non-neural structures may be involved. Appropriate assessment and management are important for patients with sciatica. Therapists use several outcome measures to assess patients to inform selection of the most suitable treatment. There is limited evidence for the best treatment of sciatica, and this is likely contributed to by having no reliable algorithm to categorise patients based on their clinical characteristics to inform physiotherapy treatment. The purpose of this study is to develop a clinical prediction model to categorise patients with sciatica, in terms of early clinical outcome, based on their initial clinical characteristics.

METHODS AND ANALYSIS

A prospective observational multicentre design will recruit consecutive patients (n=467) with sciatica referred for physiotherapy. Each patient will be evaluated to determine whether or not they will be accepted into the study by answering some questions that will confirm the study's eligibility criteria. Patients' basic characteristics, patient-reported outcome measures and performance-based measures will be collected at baseline from multiple sites in the Greek territory using this same protocol, prior to commencement of treatment. The main researcher of this study will be responsible for data collection in all sites. On completion of the standard referred physiotherapy treatment after 3 weeks' time, participants will be asked by telephone to evaluate their outcome using the Global Perceived Effect Scale. For the descriptive statistical analysis, the continuous variables will be expressed in the form of 'mean' and 'SD'. In order to assess the prognostic value of each predictor, in terms of the level of improvement or worsening of the symptoms, multiple variable regression analysis will be used.

ETHICS AND DISSEMINATION

Τhis study is approved from the Ethics and Deontology Committee of the University of West Attica, Athens, Greece, protocol number: 38313-09/06/2020, 10226-10/02/2021. The study's findings will be published in a peer-reviewed journal and disseminated at national and international conferences and through social media.

PROSPERO REGISTRATION NUMBER

CRD42020168467.

Analyzing Data of a Multilab Replication Project With Individual Participant Data Meta-Analysis

Abstract. Multilab replication projects such as Registered Replication Reports (RRR) and Many Labs projects are used to replicate an effect in different labs. Data of these projects are usually analyzed using conventional meta-analysis methods. This is certainly not the best approach because it does not make optimal use of the available data as a summary rather than participant data are analyzed. I propose to analyze data of multilab replication projects with individual participant data (IPD) meta-analysis where the participant data are analyzed directly. The prominent advantages of IPD meta-analysis are that it generally has larger statistical power to detect moderator effects and allows drawing conclusions at the participant and lab level. However, a disadvantage is that IPD meta-analysis is more complex than conventional meta-analysis. In this tutorial, I illustrate IPD meta-analysis using the RRR by McCarthy and colleagues, and I provide R code and recommendations to facilitate researchers to apply these methods.

Prognostic factors for work disability in patients with chronic widespread pain and fibromyalgia: protocol for a cohort study

INTRODUCTION

The association between chronic widespread pain (CWP) and disability is well established. Although research support large interindividual differences in functional outcomes, limited studies are available on the socio-economic consequences of offering stratified treatment based on prognostic factors. Identification of predictors of long-term functional outcomes such as work disability as a critical consequence, could assist early and targeted personalised interventions. The primary objective of this cohort study is to identify prognostic factors for the primary endpoint work status (employed and working vs not working) in patients with CWP assessed 3 years from baseline, that is, at referral for specialist care.

METHODS AND ANALYSES

Data are collected at the diagnostic unit at Department of Rheumatology, Frederiksberg Hospital. The first 1000 patients ≥18 years of age registered in a clinical research database (DANFIB registry) with CWP either 'employed and working' or 'not working' will be enrolled. Participants must meet the American College of Rheumatology 1990 definition of CWP, that is, pain in all four body quadrants and axially for more than 3 months and are additionally screened for fulfilment of criteria for fibromyalgia. Clinical data and patient-reported outcomes are collected at referral (baseline) through clinical assessment and electronic questionnaires. Data on the primary endpoint work status at baseline and 3 years from baseline will be extracted from the Integrated Labour Market Database, Statistics Denmark and the nationwide Danish DREAM database. Prognostic factor analysis will be based on multivariable logistic regression modelling with the dichotomous work status as dependent variable.

ETHICS AND DISSEMINATION

Sensitive personal data will be anonymised according to regulations by the Danish Data Protection Agency, and informed consent are obtained from all participants. Understanding and improving the prognosis of a health condition like CWP should be a priority in clinical research and practice. Results will be published in international peer-reviewed journals.

TRIAL REGISTRATION NUMBER

NCT04862520.

Knowledge translation of prediction rules: methods to help health professionals understand their trade-offs

Clinical prediction models are developed with the ultimate aim of improving patient outcomes, and are often turned into prediction rules (e.g. classifying people as low/high risk using cut-points of predicted risk) at some point during the development stage. Prediction rules often have reasonable ability to either rule-in or rule-out disease (or another event), but rarely both. When a prediction model is intended to be used as a prediction rule, conveying its performance using the C-statistic, the most commonly reported model performance measure, does not provide information on the magnitude of the trade-offs. Yet, it is important that these trade-offs are clear, for example, to health professionals who might implement the prediction rule. This can be viewed as a form of knowledge translation. When communicating information on trade-offs to patients and the public there is a large body of evidence that indicates natural frequencies are most easily understood, and one particularly well-received way of depicting the natural frequency information is to use population diagrams. There is also evidence that health professionals benefit from information presented in this way.Here we illustrate how the implications of the trade-offs associated with prediction rules can be more readily appreciated when using natural frequencies. We recommend that the reporting of the performance of prediction rules should (1) present information using natural frequencies across a range of cut-points to inform the choice of plausible cut-points and (2) when the prediction rule is recommended for clinical use at a particular cut-point the implications of the trade-offs are communicated using population diagrams. Using two existing prediction rules, we illustrate how these methods offer a means of effectively and transparently communicating essential information about trade-offs associated with prediction rules.

Appraisal of multivariable prognostic models for post-operative liver decompensation following partial hepatectomy: a systematic review

BACKGROUND

Few reports have evaluated prognostic modelling studies of tools used for surgical decision-making. This systematic review aimed to describe and critically appraise studies that have developed or validated multivariable prognostic models for post-operative liver decompensation following partial hepatectomy.

METHODS

This study was designed using the CHARMS checklist. Following a comprehensive literature search, two reviewers independently screened candidate references for inclusion and abstracted relevant study details. Qualitative assessment was performed using the PROBAST tool.

RESULTS

We identified 36 prognostic modelling studies; 25 focused on development only, 3 developed and validated models, and 8 validated pre-existing models. None compared routine use of a prognostic model against standard clinical practice. Most studies used single-institution, retrospective cohort designs, conducted in Eastern populations. In total, 15 different outcome definitions for post-operative liver decompensation events were used. Statistical concerns surrounding model overfitting, performance assessment, and internal validation led to high risk of bias for all studies.

CONCLUSIONS

Current prognostic models for post-operative liver decompensation following partial hepatectomy may not be valid for routine clinical use due to design and methodologic concerns. Landmark resources and reporting guidelines such as the TRIPOD statement may assist researchers, and additionally, model impact assessment studies represent opportunities for future research.

Predictors of the outcome of physiotherapy following a meniscus tear: A systematic review

BACKGROUND

Physiotherapy is indicated for treatment of a painful degenerative knee meniscus tear. Predicting the outcome remains uncertain.

OBJECTIVE

The purpose of this systematic review was to identify which predictive factors are associated with the outcome of physiotherapy for degenerative knee meniscus tear.

METHODS

A systematic electronic literature search was undertaken of PubMed, CINAHL, Medline with AMED and EMBASE via Ovid from inception to July 2021. Studies of adults receiving physiotherapy which presented data on the association of baseline variables and the treatment outcome were included. Study quality was assessed using CASP (Critical Appraisal Skills Programme) tools. Data were narratively analysed.

RESULTS

1051 titles were retrieved and screened for eligibility. Fifteen studies met the inclusion criteria. Nine studies investigated just degenerative tears. The evidence-base was of low/moderate quality. Across all studies, seven and five studies (100%) reported no association between mechanical symptoms or gender respectively (p > 0.05). There was no association with osteoarthritis in 80%, age in 71%, or body mass index in 60% of studies (p > 0.05). Four studies (80%) reported that higher baseline pain was associated with cross-over to surgery, greater improvement with surgery or less improvement in pain score (p > 0.05).

CONCLUSION

Patient demographic characteristics provide minimal association with outcome following physiotherapy for degenerative meniscus tear. The evidence-base is limited in size and quality. A large adequately powered prospective cohort study investigating a broad range of predictive factors is warranted to develop a predictive model to better stratify those most likely to benefit from physiotherapy.

Development and Validation of Prognostic Models for Oral Squamous Cell Carcinoma: A Systematic Review and Appraisal of the Literature

(1) Background: An accurate prediction of cancer survival is very important for counseling, treatment planning, follow-up, and postoperative risk assessment in patients with Oral Squamous Cell Carcinoma (OSCC). There has been an increased interest in the development of clinical prognostic models and nomograms which are their graphic representation. The study aimed to revise the prognostic performance of clinical-pathological prognostic models with internal validation for OSCC. (2) Methods: This systematic review was performed according to the Cochrane Handbook for Diagnostic Test Accuracy Reviews chapter on searching, the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) guidelines, and the Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies (CHARMS). (3) Results: Six studies evaluating overall survival in patients with OSCC were identified. All studies performed internal validation, while only four models were externally validated. (4) Conclusions: Based on the results of this systematic review, it is possible to state that it is necessary to carry out internal validation and shrinkage to correct overfitting and provide an adequate performance for optimism. Moreover, calibration, discrimination and nonlinearity of continuous predictors should always be examined. To reduce the risk of bias the study design used should be prospective and imputation techniques should always be applied to handle missing data. In addition, the complete equation of the prognostic model must be reported to allow updating, external validation in a new context and the subsequent evaluation of the impact on health outcomes and on the cost-effectiveness of care.

Moderator effects in a randomized controlled trial of the Common Elements Treatment Approach (CETA) for intimate partner violence and hazardous alcohol use in Zambia

BACKGROUND

Intimate partner violence (IPV) and hazardous alcohol use are prevalent and co-occurring problems in low- and middle-income countries (LMICs). While limited evidence suggests that cognitive behavioral therapy (CBT) interventions can help address these problems, few randomized trials in LMICs have investigated moderators of treatment effectiveness. This study explores moderating factors impacting responsiveness to a CBT-based intervention for IPV and hazardous alcohol use among couples in Zambia.

METHODS

Data were obtained from a completed randomized trial of a CBT-based intervention, the Common Elements Treatment Approach (CETA), among 248 couples in Lusaka. Female experiences of IPV and male alcohol use were measured at baseline and 12 months post-baseline. Mixed effects regression models were used to evaluate each moderator: age, educational attainment, employment status, marital status, physical disability, HIV status, trauma exposure, depression, post-traumatic stress disorder, alcohol use disorder, and substance use.

RESULTS

Treatment effectiveness for male alcohol use was moderated by female substance use, with greater reductions among men whose partners reported using non-alcohol substances (e.g., cannabis) (p < 0.01). Other marginally significant moderators (p < 0.15) of change in male alcohol use included female education and male depression, substance use, and moderate-to-severe alcohol use at baseline. Female HIV status and depression were marginally significant moderators of change in IPV.

CONCLUSIONS

This study suggests that CETA may be especially effective for highly symptomatic individuals with comorbid mental and behavioral health problems, a promising finding given that such comorbidity is widespread in LMICs. Psychotherapeutic treatments that can flexibly and simultaneously address co-occurring problems are needed.

Detecting Heterogeneity of Intervention Effects Using Analysis and Meta-analysis of Differences in Variance Between Trial Arms

BACKGROUND

Randomized controlled trials (RCTs) with continuous outcomes usually only examine mean differences in response between trial arms. If the intervention has heterogeneous effects, then outcome variances will also differ between arms. Power of an individual trial to assess heterogeneity is lower than the power to detect the same size of main effect.

METHODS

We describe several methods for assessing differences in variance in trial arms and apply them to a single trial with individual patient data and to meta-analyses using summary data. Where individual data are available, we use regression-based methods to examine the effects of covariates on variation. We present an additional method to meta-analyze differences in variances with summary data.

RESULTS

In the single trial, there was agreement between methods, and the difference in variance was largely due to differences in prevalence of depression at baseline. In two meta-analyses, most individual trials did not show strong evidence of a difference in variance between arms, with wide confidence intervals. However, both meta-analyses showed evidence of greater variance in the control arm, and in one example, this was perhaps because mean outcome in the control arm was higher.

CONCLUSIONS

Using meta-analysis, we overcame low power of individual trials to examine differences in variance using meta-analysis. Evidence of differences in variance should be followed up to identify potential effect modifiers and explore other possible causes such as varying compliance.

Mammographic density, endocrine therapy and breast cancer risk: a prognostic and predictive biomarker review

BACKGROUND

Endocrine therapy is effective at preventing or treating breast cancer. Some forms of endocrine therapy have been shown to reduce mammographic density. Reduced mammographic density for women receiving endocrine therapy could be used to estimate the chance of breast cancer returning or developing breast cancer in the first instance (a prognostic biomarker). In addition, changes in mammographic density might be able to predict how well a woman responds to endocrine therapy (a predictive biomarker). The role of breast density as a prognostic or predictive biomarker could help improve the management of breast cancer.

OBJECTIVES

To assess the evidence that a reduction in mammographic density following endocrine therapy for breast cancer prevention in women without previous breast cancer, or for treatment in women with early-stage hormone receptor-positive breast cancer, is a prognostic or predictive biomarker.

SEARCH METHODS

We searched the Cochrane Breast Cancer Group Specialised Register, CENTRAL, MEDLINE, Embase, and two trials registers on 3 August 2020 along with reference checking, bibliographic searching, and contact with study authors to obtain further data.

SELECTION CRITERIA

We included randomised, cohort and case-control studies of adult women with or without breast cancer receiving endocrine therapy. Endocrine therapy agents included were selective oestrogen receptor modulators and aromatase inhibitors. We required breast density before start of endocrine therapy and at follow-up. We included studies published in English.

DATA COLLECTION AND ANALYSIS

We used standard methodological procedures expected by Cochrane. Two review authors independently extracted data and assessed risk of bias using adapted Quality in Prognostic Studies (QUIPS) and Risk Of Bias In Non-randomised Studies - of Interventions (ROBINS-I) tools. We used the GRADE approach to evaluate the certainty of the evidence. We did not perform a quantitative meta-analysis due to substantial heterogeneity across studies.

MAIN RESULTS

Eight studies met our inclusion criteria, of which seven provided data on outcomes listed in the protocol (5786 women). There was substantial heterogeneity across studies in design, sample size (349 to 1066 women), participant characteristics, follow-up (5 to 14 years), and endocrine therapy agent. There were five breast density measures and six density change definitions. All studies had at least one domain as at moderate or high risk of bias. Common concerns were whether the study sample reflected the review target population, and likely post hoc definitions of breast density change. Most studies on prognosis for women receiving endocrine therapy reported a reduced risk associated with breast density reduction. Across endpoints, settings, and agents, risk ratio point estimates (most likely value) were between 0.1 and 1.5, but with substantial uncertainty. There was greatest consistency in the direction and magnitude of the effect for tamoxifen (across endpoints and settings, risk ratio point estimates were between 0.3 and 0.7). The findings are summarised as follows. Prognostic biomarker findings: Treatment Breast cancer mortality Two studies of 823 women on tamoxifen (172 breast cancer deaths) reported risk ratio point estimates of ~0.4 and ~0.5 associated with a density reduction. The certainty of the evidence was low. Recurrence Two studies of 1956 women on tamoxifen reported risk ratio point estimates of ~0.4 and ~0.7 associated with a density reduction. There was risk of bias in methodology for design and analysis of the studies and considerable uncertainty over the size of the effect. One study of 175 women receiving an aromatase inhibitor reported a risk ratio point estimate of ~0.1 associated with a density reduction. There was considerable uncertainty about the effect size and a moderate or high risk of bias in all domains. One study of 284 women receiving exemestane or tamoxifen as part of a randomised controlled trial reported risk ratio point estimates of ~1.5 (loco-regional recurrence) and ~1.3 (distance recurrence) associated with a density reduction. There was risk of bias in reporting and study confounding, and uncertainty over the size of the effects. The certainty of the evidence for all recurrence endpoints was very low. Incidence of a secondary primary breast cancer Two studies of 451 women on exemestane, tamoxifen, or unknown endocrine therapy reported risk ratio point estimates of ~0.5 and ~0.6 associated with a density reduction. There was risk of bias in reporting and study confounding, and uncertainty over the effect size. The certainty of the evidence was very low. We were unable to find data regarding the remaining nine outcomes prespecified in the review protocol. Prevention Incidence of invasive breast cancer and ductal carcinoma in situ (DCIS) One study of 507 women without breast cancer who were receiving preventive tamoxifen as part of a randomised controlled trial (51 subsequent breast cancers) reported a risk ratio point estimate of ~0.3 associated with a density reduction. The certainty of the evidence was low. Predictive biomarker findings: One study of a subset of 1065 women from a randomised controlled trial assessed how much the effect of endocrine therapy could be explained by breast density declines in those receiving endocrine therapy. This study evaluated the prevention of invasive breast cancer and DCIS. We found some evidence to support the hypothesis, with a risk ratio interaction point estimate ~0.5. However, the 95% confidence interval included unity, and data were based on 51 women with subsequent breast cancer in the tamoxifen group. The certainty of the evidence was low.

AUTHORS' CONCLUSIONS

There is low-/very low-certainty evidence to support the hypothesis that breast density change following endocrine therapy is a prognostic biomarker for treatment or prevention. Studies suggested a potentially large effect size with tamoxifen, but the evidence was limited. There was less evidence that breast density change following tamoxifen preventive therapy is a predictive biomarker than prognostic biomarker. Evidence for breast density change as a prognostic treatment biomarker was stronger for tamoxifen than aromatase inhibitors. There were no studies reporting mammographic density change following endocrine therapy as a predictive biomarker in the treatment setting, nor aromatase inhibitor therapy as a prognostic or predictive biomarker in the preventive setting. Further research is warranted to assess mammographic density as a biomarker for all classes of endocrine therapy and review endpoints.