Competing and Noncompeting Risk Models for Predicting Kidney Allograft Failure.

BACKGROUND: Prognostic models are becoming increasingly relevant in clinical trials as potential surrogate endpoints, and for patient management as clinical decision support tools. However, the impact of competing risks on model performance remains poorly investigated. We aimed to carefully assess the performance of competing risk and noncompeting risk models in the context of kidney transplantation, where allograft failure and death with a functioning graft are two competing outcomes. METHODS: We included 11,046 kidney transplant recipients enrolled in 10 countries. We developed prediction models for long-term kidney graft failure prediction, without accounting (i.e., censoring) and accounting for the competing risk of death with a functioning graft, using Cox, Fine-Gray, and cause-specific Cox regression models. To this aim, we followed a detailed and transparent analytical framework for competing and noncompeting risk modelling, and carefully assessed the models' development, stability, discrimination, calibration, overall fit, clinical utility, and generalizability in external validation cohorts and subpopulations. More than 15 metrics were used to provide an exhaustive assessment of model performance. RESULTS: Among 11,046 recipients in the derivation and validation cohorts, 1,497 (14%) lost their graft and 1,003 (9%) died with a functioning graft after a median follow-up post-risk evaluation of 4.7 years (IQR 2.7-7.0). The cumulative incidence of graft loss was similarly estimated by Kaplan-Meier and Aalen-Johansen methods (17% versus 16% in the derivation cohort). Cox and competing risk models showed similar and stable risk estimates for predicting long-term graft failure (average mean absolute prediction error of 0.0140, 0.0138 and 0.0135 for Cox, Fine-Gray, and cause-specific Cox models, respectively). Discrimination and overall fit were comparable in the validation cohorts, with concordance index ranging from 0.76 to 0.87. Across various subpopulations and clinical scenarios, the models performed well and similarly, although in some high-risk groups (such as donors over 65 years old), the findings suggest a trend towards moderately improved calibration when using a competing risk approach. CONCLUSIONS: Competing and noncompeting risk models performed similarly in predicting long-term kidney graft failure.

Limitations of Separating Athletes into High or Low-Risk Groups based on a Cut-Off. A Clinical Commentary.

Background: Athlete injury risk assessment and management is an important, yet challenging task for sport and exercise medicine professionals. A common approach to injury risk screening is to stratify athletes into risk groups based on their performance on a test relative to a cut-off threshold. However, one potential reason for ineffective injury prevention efforts is the over-reliance on identifying these 'at-risk' groups using arbitrary cut-offs for these tests and measures. The purpose of this commentary is to discuss the conceptual and technical issues related to the use of a cut-off in both research and clinical practice. Clinical Question: How can we better assess and interpret clinical tests or measures to enable a more effective injury risk assessment in athletes? Key Results: Cut-offs typically lack strong biologic plausibility to support them; and are typically derived in a data-driven manner and thus not generalizable to other samples. When a cut-off is used in analyses, information is lost, leading to potentially misleading results and less accurate injury risk prediction. Dichotomizing a continuous variable using a cut-off should be avoided. Using continuous variables on its original scale is advantageous because information is not discarded, outcome prediction accuracy is not lost, and personalized medicine can be facilitated. Clinical Application: Researchers and clinicians are encouraged to analyze and interpret the results of tests and measures using continuous variables and avoid relying on singular cut-offs to guide decisions. Injury risk can be predicted more accurately when using continuous variables in their natural form. A more accurate risk prediction will facilitate personalized approaches to injury risk mitigation and may lead to a decline in injury rates. Level of Evidence: 5.

The TRIPOD-LLM Statement: A Targeted Guideline For Reporting Large Language Models Use.

Large Language Models (LLMs) are rapidly being adopted in healthcare, necessitating standardized reporting guidelines. We present TRIPOD-LLM, an extension of the TRIPOD+AI statement, addressing the unique challenges of LLMs in biomedical applications. TRIPOD-LLM provides a comprehensive checklist of 19 main items and 50 subitems, covering key aspects from title to discussion. The guidelines introduce a modular format accommodating various LLM research designs and tasks, with 14 main items and 32 subitems applicable across all categories. Developed through an expedited Delphi process and expert consensus, TRIPOD-LLM emphasizes transparency, human oversight, and task-specific performance reporting. We also introduce an interactive website ( https://tripod-llm.vercel.app/ ) facilitating easy guideline completion and PDF generation for submission. As a living document, TRIPOD-LLM will evolve with the field, aiming to enhance the quality, reproducibility, and clinical applicability of LLM research in healthcare through comprehensive reporting. COI: DSB: Editorial, unrelated to this work: Associate Editor of Radiation Oncology, HemOnc.org (no financial compensation); Research funding, unrelated to this work: American Association for Cancer Research; Advisory and consulting, unrelated to this work: MercurialAI. DDF: Editorial, unrelated to this work: Associate Editor of JAMIA, Editorial Board of Scientific Data, Nature; Funding, unrelated to this work: the intramural research program at the U.S. National Library of Medicine, National Institutes of Health. JWG: Editorial, unrelated to this work: Editorial Board of Radiology: Artificial Intelligence, British Journal of Radiology AI journal and NEJM AI. All other authors declare no conflicts of interest.

External validation of models to estimate gestational age in the second and third trimester using ultrasound: A prospective multicentre observational study.

OBJECTIVES: Accurate assessment of gestational age (GA) is important at both individual and population levels. The most accurate way to estimate GA in women who book late in pregnancy is unknown. The aim of this study was to externally validate the accuracy of equations for GA estimation in late pregnancy and to identify the best equation for estimating GA in women who do not receive an ultrasound scan until the second or third trimester. DESIGN: This was a prospective, observational cross-sectional study. SETTING: 57 prenatal care centres, France. PARTICIPANTS: Women with a singleton pregnancy and a previous 11-14-week dating scan that gave the observed GA were recruited over an 8-week period. They underwent a standardised ultrasound examination at one time point during the pregnancy (15-43 weeks), measuring 12 foetal biometric parameters that have previously been identified as useful for GA estimation. MAIN OUTCOME MEASURES: A total of 189 equations that estimate GA based on foetal biometry were examined and compared with GA estimation based on foetal CRL. Comparisons between the observed GA and the estimated GA were made using R2, calibration slope and intercept. RMSE, mean difference and 95% range of error were also calculated. RESULTS: A total of 2741 pregnant women were examined. After exclusions, 2339 participants were included. In the 20 best performing equations, the intercept ranged from -0.22 to 0.30, the calibration slope from 0.96 to 1.03 and the RSME from 0.67 to 0.87. Overall, multiparameter models outperformed single-parameter models. Both the 95% range of error and mean difference increased with gestation. Commonly used models based on measurement of the head circumference alone were not amongst the best performing models and were associated with higher 95% error and mean difference. CONCLUSIONS: We provide strong evidence that GA-specific equations based on multiparameter models should be used to estimate GA in late pregnancy. However, as all methods of GA assessment in late pregnancy are associated with large prediction intervals, efforts to improve access to early antenatal ultrasound must remain a priority. TRIAL REGISTRATION: The proposal for this study and the corresponding methodological review was registered on PROSPERO international register of systematic reviews (registration number: CRD4201913776).

Risk of serious adverse events after primary shoulder replacement: development and external validation of a prediction model using linked national data from England and Denmark.

BACKGROUND: Despite a rising rate of serious medical complications after shoulder replacement surgery, there are no prediction models in widespread use to guide surgeons in identifying patients at high risk and to provide patients with personalised risk estimates to support shared decision making. Our aim was to develop and externally validate a prediction model for serious adverse events within 90 days of primary shoulder replacement surgery. METHODS: Linked data from the National Joint Registry, National Health Service Hospital Episode Statistics Admitted Patient Care of England, and Civil Registration Mortality databases and Danish Shoulder Arthroplasty Registry and National Patient Register were used for our modelling study. Patients aged 18-100 years who had a primary shoulder replacement between April 1, 2012, and Oct 2, 2020, in England, and April 1, 2012, and Oct 2, 2018, in Denmark, were included. We developed a multivariable logistic regression model using the English dataset to predict the risk of 90-day serious adverse events, which were defined as medical complications requiring admission to hospital and all-cause death. We undertook internal validation using bootstrapping, and internal-external cross-validation across different geographical regions of England. The English model was externally validated on the Danish dataset. FINDINGS: Data for 40 631 patients undergoing primary shoulder replacement (mean age 72·5 years [SD 9·9]; 28 709 [70·7%] women and 11 922 [29·3%] men) were used for model development, of whom 2270 (5·6%) had a 90-day serious adverse event. On internal validation, the model had a C-statistic of 0·717 (95% CI 0·707-0·728) and was well calibrated. Internal-external cross-validation showed consistent model performance across all regions in England. Upon external validation on the Danish dataset (n=6653; mean age 70·5 years [SD 10·3]; 4503 [67·7%] women and 2150 [32·3%] men), the model had a C-statistic of 0·750 (95% CI 0·723-0·776). Decision curve analysis showed clinical utility, with net benefit across all risk thresholds. INTERPRETATION: This externally validated prediction model uses commonly available clinical variables to accurately predict the risk of serious medical complications after primary shoulder replacement surgery. The model is generalisable and applicable to most patients in need of a shoulder replacement. Its use offers support to clinicians and could inform and empower patients in the shared decision-making process. FUNDING: National Institute for Health and Care Research and the Department of Orthopaedic Surgery, Herlev and Gentofte Hospital, Denmark.

Calculating the power of a planned individual participant data meta-analysis to examine prognostic factor effects for a binary outcome.

Collecting data for an individual participant data meta-analysis (IPDMA) project can be time consuming and resource intensive and could still have insufficient power to answer the question of interest. Therefore, researchers should consider the power of their planned IPDMA before collecting IPD. Here we propose a method to estimate the power of a planned IPDMA project aiming to synthesise multiple cohort studies to investigate the (unadjusted or adjusted) effects of potential prognostic factors for a binary outcome. We consider both binary and continuous factors and provide a three-step approach to estimating the power in advance of collecting IPD, under an assumption of the true prognostic effect of each factor of interest. The first step uses routinely available (published) aggregate data for each study to approximate Fisher's information matrix and thereby estimate the anticipated variance of the unadjusted prognostic factor effect in each study. These variances are then used in step 2 to estimate the anticipated variance of the summary prognostic effect from the IPDMA. Finally, step 3 uses this variance to estimate the corresponding IPDMA power, based on a two-sided Wald test and the assumed true effect. Extensions are provided to adjust the power calculation for the presence of additional covariates correlated with the prognostic factor of interest (by using a variance inflation factor) and to allow for between-study heterogeneity in prognostic effects. An example is provided for illustration, and Stata code is supplied to enable researchers to implement the method.

Sample size in multistakeholder Delphi surveys: at what minimum sample size do replicability of results stabilize?

BACKGROUND AND OBJECTIVE: The minimum sample size for multistakeholder Delphi surveys remains understudied. Drawing from three large international multistakeholder Delphi surveys, this study aimed to: 1) investigate the effect of increasing sample size on replicability of results; 2) assess whether the level of replicability of results differed with participant characteristics: for example, gender, age, and profession. METHODS: We used data from Delphi surveys to develop guidance for improved reporting of health-care intervention trials: SPIRIT (Standard Protocol Items: Recommendations for Interventional Trials) and CONSORT (Consolidated Standards of Reporting Trials) extension for surrogate end points (n = 175, 22 items rated); CONSORT-SPI [CONSORT extension for Social and Psychological Interventions] (n = 333, 77 items rated); and core outcome set for burn care (n = 553, 88 items rated). Resampling with replacement was used to draw random subsamples from the participant data set in each of the three surveys. For each subsample, the median value of all rated survey items was calculated and compared to the medians from the full participant data set. The median number (and interquartile range) of medians replicated was used to calculate the percentage replicability (and variability). High replicability was defined as ≥80% and moderate as 60% and <80% RESULTS: The average median replicability (variability) as a percentage of total number of items rated from the three datasets was 81% (10%) at a sample size of 60. In one of the datasets (CONSORT-SPI), a ≥80% replicability was reached at a sample size of 80. On average, increasing the sample size from 80 to 160 increased the replicability of results by a further 3% and reduced variability by 1%. For subgroup analysis based on participant characteristics (eg, gender, age, professional role), using resampled samples of 20 to 100 showed that a sample size of 20 to 30 resulted to moderate replicability levels of 64% to 77%. CONCLUSION: We found that a minimum sample size of 60-80 participants in multistakeholder Delphi surveys provides a high level of replicability (≥80%) in the results. For Delphi studies limited to individual stakeholder groups (such as researchers, clinicians, patients), a sample size of 20 to 30 per group may be sufficient.

Kidney cancer in the Middle East and North Africa region: a 30-year analysis (1990-2019).

Kidney cancer, a type of urogenital cancer, imposes a high burden on patients. Despite this, no recent research has evaluated the burden of this type of cancer in the Middle East and North Africa (MENA) region. This study explored the burden of kidney cancer from 1990 to 2019 according to age, sex and socio-demographic index (SDI). The Global Burden of Disease (GBD) 2019 data was utilized to estimate the incidence, death, and disability-adjusted life-years (DALYs) caused by kidney cancer. These estimates were reported as counts and as age-standardised rates with 95% uncertainty intervals (UIs). The estimated age-standardised incidence, mortality, and DALY rates of kidney cancer in 2019 were 3.2 (2.8-3.6), 1.4 (1.2-1.6), and 37.2 (32.0-42.6) per 100,000, respectively. Over the period from 1990 to 2019, these rates have increased by 98.0%, 48.9%, and 37.7%, respectively. In 2019, the United Arab Emirates, Qatar, and Lebanon had the largest age-standardised incidence, mortality, and DALY rates. The smallest age-standardised incidence rates were seen in Yemen, Afghanistan, and the Syrian Arab Republic. Additionally, the smallest age-standardised mortality and DALY rates were observed in the Syrian Arab Republic, Yemen, and Morocco. The highest incidence rates were found among individuals aged 75-79 in both males and females. In 2019, the MENA/Global DALY ratio exceeded one for females aged 5-19 age and males aged 5-14, compared to 1990age groups in males. The burden of kidney cancer consistently rose with increasing SDI levels from 1990 to 2019. The increasing burden of kidney cancer highlights the urgent need for interventions aimed at improving early diagnosis and treatment in the region.

Reporting completeness of nutrition and diet-related randomised controlled trials protocols.

BACKGROUND AND AIMS: There is a need to consolidate reporting guidance for nutrition randomised controlled trial (RCT) protocols. The reporting completeness in nutrition RCT protocols and study characteristics associated with adherence to SPIRIT and TIDieR reporting guidelines are unknown. We, therefore, assessed reporting completeness and its potential predictors in a random sample of published nutrition and diet-related RCT protocols. METHODS: We conducted a meta-research study of 200 nutrition and diet-related RCT protocols published in 2019 and 2021 (aiming to consider periods before and after the start of the COVID pandemic). Data extraction included bibliometric information, general study characteristics, compliance with 122 questions corresponding to items and subitems in the SPIRIT and TIDieR checklists combined, and mention to these reporting guidelines in the publications. We calculated the proportion of protocols reporting each item and the frequency of items reported for each protocol. We investigated associations between selected publication aspects and reporting completeness using linear regression analysis. RESULTS: The majority of protocols included adults and elderly as their study population (n = 73; 36.5%), supplementation as intervention (n = 96; 48.0%), placebo as comparator (n = 89; 44.5%), and evaluated clinical status as the outcome (n = 80; 40.0%). Most protocols described a parallel RCT (n = 188; 94.0%) with a superiority framework (n = 141; 70.5%). Overall reporting completeness was 52.0% (SD = 10.8%). Adherence to SPIRIT items ranged from 0% (n = 0) (data collection methods) to 98.5% (n = 197) (eligibility criteria). Adherence to TIDieR items ranged from 5.5% (n = 11) (materials used in the intervention) to 98.5% (n = 197) (description of the intervention). The multivariable regression analysis suggests that a higher number of authors [ß = 0.53 (95%CI: 0.28-0.78)], most recent published protocols [ß = 3.19 (95%CI: 0.24-6.14)], request of reporting guideline checklist during the submission process by the journal [ß = 6.50 (95%CI: 2.56-10.43)] and mention of SPIRIT by the authors [ß = 5.15 (95%CI: 2.44-7.86)] are related to higher reporting completeness scores. CONCLUSIONS: Reporting completeness in a random sample of 200 diet or nutrition-related RCT protocols was low. Number of authors, year of publication, self-reported adherence to SPIRIT, and journals' endorsement of reporting guidelines seem to be positively associated with reporting completeness in nutrition and diet-related RCT protocols.

Anterior Cruciate Ligament Return to Sport after Injury Scale (ACL-RSI) Scores over Time After Anterior Cruciate Ligament Reconstruction: A Systematic Review with Meta-analysis.

BACKGROUND: Psychological readiness is an important consideration for athletes and clinicians when making return to sport decisions following anterior cruciate ligament reconstruction (ACLR). To improve our understanding of the extent of deficits in psychological readiness, a systematic review is necessary. OBJECTIVE: To investigate psychological readiness (measured via the Anterior Cruciate Ligament-Return to Sport after Injury scale (ACL-RSI)) over time after ACL tear and understand if time between injury and surgery, age, and sex are associated with ACL-RSI scores. METHODS: Seven databases were searched from the earliest date available to March 22, 2022. Articles reporting ACL-RSI scores after ACL tear were included. Risk of bias was assessed using the ROBINS-I, RoB-2, and RoBANS tools based on the study design. Evidence certainty was assessed for each analysis. Random-effects meta-analyses pooled ACL-RSI scores, stratified by time post-injury and based on treatment approach (i.e., early ACLR, delayed ACLR, and unclear approach). RESULTS: A total of 83 studies were included in this review (78% high risk of bias). Evidence certainty was 'weak' or 'limited' for all analyses. Overall, ACL-RSI scores were higher at 3 to 6 months post-ACLR (mean = 61.5 [95% confidence interval (CI) 58.6, 64.4], I2 = 94%) compared to pre-ACLR (mean = 44.4 [95% CI 38.2, 50.7], I2 = 98%), remained relatively stable, until they reached the highest point 2 to 5 years after ACLR (mean = 70.7 [95% CI 63.0, 78.5], I2 = 98%). Meta-regression suggests shorter time from injury to surgery, male sex, and older age were associated with higher ACL-RSI scores only 3 to 6 months post-ACLR (heterogeneity explained R2 = 47.6%), and this reduced 1-2 years after ACLR (heterogeneity explained R2 = 27.0%). CONCLUSION: Psychological readiness to return to sport appears to improve early after ACL injury, with little subsequent improvement until ≥ 2-years after ACLR. Longer time from injury to surgery, female sex and older age might be negatively related to ACL-RSI scores 12-24 months after ACLR. Due to the weak evidence quality rating and the considerable importance of psychological readiness for long-term outcomes after ACL injury, there is an urgent need for well-designed studies that maximize internal validity and identify additional prognostic factors for psychological readiness at times critical for return to sport decisions. REGISTRATION: Open Science Framework (OSF), https://osf.io/2tezs/ .

SPIN-PM: a consensus framework to evaluate the presence of spin in studies on prediction models.

OBJECTIVES: To develop a framework to identify and evaluate spin practices and its facilitators in studies on clinical prediction model regardless of the modeling technique. STUDY DESIGN AND SETTING: We followed a three-phase consensus process: (1) premeeting literature review to generate items to be included; (2) a series of structured meetings to provide comments discussed and exchanged viewpoints on items to be included with a panel of experienced researchers; and (3) postmeeting review on final list of items and examples to be included. Through this iterative consensus process, a framework was derived after all panel's researchers agreed. RESULTS: This consensus process involved a panel of eight researchers and resulted in SPIN-Prediction Models which consists of two categories of spin (misleading interpretation and misleading transportability), and within these categories, two forms of spin (spin practices and facilitators of spin). We provide criteria and examples. CONCLUSION: We proposed this guidance aiming to facilitate not only the accurate reporting but also an accurate interpretation and extrapolation of clinical prediction models which will likely improve the reporting quality of subsequent research, as well as reduce research waste.

The burden of schizophrenia in the Middle East and North Africa region, 1990-2019.

Schizophrenia ranks as the third-most common cause of disability among mental disorders globally. This study presents findings on the prevalence, incidence and years lived with disability (YLDs) as a result of schizophrenia in the Middle East and North Africa (MENA), stratified by age, sex and sociodemographic index (SDI). We collected publicly accessible data from the Global Burden of Disease (GBD) study 2019. This study reports the burden of schizophrenia, from 1990 to 2019, for the 21 countries that comprise MENA. In 2019, MENA exhibited an age-standardised point prevalence of 248.2, an incidence rate of 14.7 and an YLD rate of 158.7 per 100,000, which have not changed substantially between 1990 and 2019. In 2019, the age-standardised YLD rate was highest in Qatar and lowest in Afghanistan. No MENA countries demonstrated noteworthy changes in the burden of schizophrenia from 1990 to 2019. Furthermore, in 2019, the highest number of prevalent cases and the point prevalence were observed among those aged 35-39, with a higher prevalence among males in almost all age categories. Additionally, in 2019, the age-standardised YLD rates in MENA were below the worldwide average. Finally, there was a positive correlation between the burden of schizophrenia and the SDI from 1990 to 2019. The disease burden of schizophrenia has remained relatively stable over the past thirty years. Nevertheless, as the regional life-expectancy continues to increase, the burden of schizophrenia is also expected to rise. Therefore, early planning for the increase in the burden of the disease is urgently needed in the region.

Reverse total shoulder replacement versus anatomical total shoulder replacement for osteoarthritis: population based cohort study using data from the National Joint Registry and Hospital Episode Statistics for England.

OBJECTIVES: To answer a national research priority by comparing the risk-benefit and costs associated with reverse total shoulder replacement (RTSR) and anatomical total shoulder replacement (TSR) in patients having elective primary shoulder replacement for osteoarthritis. DESIGN: Population based cohort study using data from the National Joint Registry and Hospital Episode Statistics for England. SETTING: Public hospitals and publicly funded procedures at private hospitals in England, 2012-20. PARTICIPANTS: Adults aged 60 years or older who underwent RTSR or TSR for osteoarthritis with intact rotator cuff tendons. Patients were identified from the National Joint Registry and linked to NHS Hospital Episode Statistics and civil registration mortality data. Propensity score matching and inverse probability of treatment weighting were used to balance the study groups. MAIN OUTCOME MEASURES: The main outcome measure was revision surgery. Secondary outcome measures included serious adverse events within 90 days, reoperations within 12 months, prolonged hospital stay (more than three nights), change in Oxford Shoulder Score (preoperative to six month postoperative), and lifetime costs to the healthcare service. RESULTS: The propensity score matched population comprised 7124 RTSR or TSR procedures (126 were revised), and the inverse probability of treatment weighted population comprised 12 968 procedures (294 were revised) with a maximum follow-up of 8.75 years. RTSR had a reduced hazard ratio of revision in the first three years (hazard ratio local minimum 0.33, 95% confidence interval 0.18 to 0.59) with no clinically important difference in revision-free restricted mean survival time, and a reduced relative risk of reoperations at 12 months (odds ratio 0.45, 95% confidence interval 0.25 to 0.83) with an absolute risk difference of -0.51% (95% confidence interval -0.89 to -0.13). Serious adverse events and prolonged hospital stay risks, change in Oxford Shoulder Score, and modelled mean lifetime costs were similar. Outcomes remained consistent after weighting. CONCLUSIONS: This study's findings provide reassurance that RTSR is an acceptable alternative to TSR for patients aged 60 years or older with osteoarthritis and intact rotator cuff tendons. Despite a significant difference in the risk profiles of revision surgery over time, no statistically significant and clinically important differences between RTSR and TSR were found in terms of long term revision surgery, serious adverse events, reoperations, prolonged hospital stay, or lifetime healthcare costs.