Ioannidis, John P A

Significance Statement Why are there so few biomarkers accepted by health authorities and implemented in clinical practice, despite the high and growing number of biomaker studies in medical research ? In this meta-epidemiological study, including 804 studies that were critically appraised by expert reviewers, the authors have identified all prognostic kidney transplant biomarkers and showed overall suboptimal study designs, methods, results, interpretation, reproducible research standards, and transparency. The authors also demonstrated for the first time that the limited number of studies challenged the added value of their candidate biomarkers against standard-of-care routine patient monitoring parameters. Most biomarker studies tended to be single-center, retrospective studies with a small number of patients and clinical events. Less than 5% of the studies performed an external validation. The authors also showed the poor transparency reporting and identified a data beautification phenomenon. These findings suggest that there is much wasted research effort in transplant biomarker medical research and highlight the need to produce more rigorous studies so that more biomarkers may be validated and successfully implemented in clinical practice. Background Despite the increasing number of biomarker studies published in the transplant literature over the past 20 years, demonstrations of their clinical benefit and their implementation in routine clinical practice are lacking. We hypothesized that suboptimal design, data, methodology, and reporting might contribute to this phenomenon. Methods We formed a consortium of experts in systematic reviews, nephrologists, methodologists, and epidemiologists. A systematic literature search was performed in PubMed, Embase, Scopus, Web of Science, and Cochrane Library between January 1, 2005, and November 12, 2022 (PROSPERO ID: CRD42020154747). All English language, original studies investigating the association between a biomarker and kidney allograft outcome were included. The final set of publications was assessed by expert reviewers. After data collection, two independent reviewers randomly evaluated the inconsistencies for 30% of the references for each reviewer. If more than 5% of inconsistencies were observed for one given reviewer, a re-evaluation was conducted for all the references of the reviewer. The biomarkers were categorized according to their type and the biological milieu from which they were measured. The study characteristics related to the design, methods, results, and their interpretation were assessed, as well as reproducible research practices and transparency indicators. Results A total of 7372 publications were screened and 804 studies met the inclusion criteria. A total of 1143 biomarkers were assessed among the included studies from blood ( n =821, 71.8%), intragraft ( n =169, 14.8%), or urine ( n =81, 7.1%) compartments. The number of studies significantly increased, with a median, yearly number of 31.5 studies (interquartile range [IQR], 23.8–35.5) between 2005 and 2012 and 57.5 (IQR, 53.3–59.8) between 2013 and 2022 ( P < 0.001). A total of 655 studies (81.5%) were retrospective, while 595 (74.0%) used data from a single center. The median number of patients included was 232 (IQR, 96–629) with a median follow-up post-transplant of 4.8 years (IQR, 3.0–6.2). Only 4.7% of studies were externally validated. A total of 346 studies (43.0%) did not adjust their biomarker for key prognostic factors, while only 3.1% of studies adjusted the biomarker for standard-of-care patient monitoring factors. Data sharing, code sharing, and registration occurred in 8.8%, 1.1%, and 4.6% of studies, respectively. A total of 158 studies (20.0%) emphasized the clinical relevance of the biomarker, despite the reported nonsignificant association of the biomarker with the outcome measure. A total of 288 studies assessed rejection as an outcome. We showed that these rejection studies shared the same characteristics as other studies. Conclusions Biomarker studies in kidney transplantation lack validation, rigorous design and methodology, accurate interpretation, and transparency. Higher standards are needed in biomarker research to prove the clinical utility and support clinical use.

Abstract This is a protocol for a co‐registered Cochrane and Campbell Review (Methodology). The objectives are as follows: To identify, describe and assess methods for: when to replicate a systematic review; how to replicate a systematic review.

Background: Paclitaxel-containing devices (PTXDs) significantly reduce reintervention in patients with symptomatic femoropopliteal peripheral artery disease. A recent aggregate-data meta-analysis reported increased late mortality in patients with peripheral artery disease treated with PTXDs. We performed an individual patient data meta-analysis to evaluate mortality. Methods: Manufacturers of US Food and Drug Administration–approved and commercially available devices in the United States provided deidentified individual patient data for independent analysis. Cox proportional hazards 1-stage meta-analysis models using intention-to-treat methods were used for the primary analysis. A secondary analysis of recovered missing vital status data was performed. The impact of control crossover to PTXDs, cause-specific mortality, and drug dose mortality were assessed. Results: A total of 2185 subjects and 386 deaths from 8 PTXD trials with 4-year median follow-up were identified. The primary analysis indicated a 38% (95% CI, 6% to 80%) increased relative mortality risk, corresponding to 4.6% absolute increase, at 5 years associated with PTXD use. Control and treatment arm loss to follow-up and withdrawal were 24% and 23%, respectively. With inclusion of recovered vital status data, the excess relative mortality risk was 27% (95% CI, 3%–58%). This observation was consistent across various scenarios, including as-treated analyses, with no evidence of increased risk over time with PTXDs. Mortality risk tended to be increased for all major causes of death. There were no subgroup differences. No drug dose–mortality association was identified. Conclusions: This individual patient data meta-analysis, based on the most complete available data set of mortality events from PTXD randomized controlled trials, identified an absolute 4.6% increased mortality risk associated with PTXD use.

ABSTRACTBackgroundVariants within the leucine‐rich repeat kinase 2 gene are recognized as the most frequent genetic cause of Parkinson's disease. Leucine‐rich repeat kinase 2 variation related to disease susceptibility displays many features that reflect the nature of complex, late‐onset sporadic disorders like Parkinson's disease.MethodsThe Genetic Epidemiology of Parkinson's Disease Consortium recently performed the largest genetic association study for variants in the leucine‐rich repeat kinase 2 gene across 23 different sites in 15 countries.ResultsHerein, we detail the allele frequencies for the novel risk factors (p.A419V and p.M1646T) and the protective haplotype (p.N551K‐R1398H‐K1423K) nominated in the original publication. Simple population allele frequencies not only can provide insight into the clinical relevance of specific variants but also can help genetically define patient groups.ConclusionsEstablishing individual patient‐based genomic susceptibility profiles that incorporate both risk factors and protective factors will determine future diagnostic and treatment strategies. © 2013 International Parkinson and Movement Disorder Society