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Record W2998308557 · doi:10.2215/cjn.10330819

Exclusion of Persons with Kidney Disease in Trials of Peripheral Artery Disease

2019· review· en· W2998308557 on OpenAlexaboutno aff
Yumeng Wen, Onur Potok, Xin Wei, Ishan Paranjpe, Lili Chan, Rakesh Malhotra, Steven G. Coca, Jagat Narula, Jeffrey W. Olin, Girish N. Nadkarni, Pranav S. Garimella

Bibliographic record

VenueClinical Journal of the American Society of Nephrology · 2019
Typereview
Languageen
FieldMedicine
TopicPeripheral Artery Disease Management
Canadian institutionsnot available
FundersNational Institute of Diabetes and Digestive and Kidney DiseasesNational Institutes of HealthAmerican Kidney Fund
KeywordsMedicineRandomized controlled trialKidney diseaseClaudicationPsychological interventionPhysical therapyIntermittent claudicationClinical trialCritical limb ischemiaDiseaseMEDLINERevascularizationInternal medicineCoronary artery diseaseArterial diseaseVascular diseaseIntensive care medicineMyocardial infarction

Abstract

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Patients with CKD are at higher risk of developing peripheral artery disease (PAD) and have worse outcomes than persons without CKD (1,2). Current PAD treatment strategies include exercise, medications, and revascularization techniques. However, it is likely that persons with advanced CKD are excluded from trials of these interventions as in trials of cardiovascular disease and cancer (3,4). We aimed to perform a systematic review to determine the representation or exclusion of patients with CKD in randomized controlled trials of PAD intervention. We systematically searched the MEDLINE database from January 1, 2000 through October 31, 2018. The search strategy included articles indexed under the Medical Subject Headings of “intermittent claudication” or “peripheral artery disease,” as well as “peripheral artery disease,” “intermittent claudication,” “critical limb ischemia,” “randomized controlled trial,” or “randomised controlled trial” under title/abstract. We included randomized trials of PAD treatment including critical limb ischemia and intermittent claudication, with at least 50 participants that reported clinical outcomes and were published in English. We extracted information on journal, publication year, study characteristics, country, funding source, intervention, whether the interventions were American Heart Association/American College of Cardiology Class (AHA/ACC) 1 or 2 recommendations, measures of kidney function used, and criteria for exclusion of patients with CKD. We reviewed methods reports and registered protocols of studies for completeness. For studies with multiple reports, the first published report was used. We assigned trials to four groups based on their publication year and sample size, and six groups based on the intervention studied. We grouped interventions into surgery, endovascular procedure, medication, exercise, other, and more than one intervention. We tested differences in exclusion by each characteristic with the chi-squared test and one-way ANOVA test. We identified 1218 citations of which 900 (74%) did not meet inclusion criteria. After reviewing full texts of the remaining 318 trials, 237 trials randomizing 157,520 participants met inclusion criteria. Of these, 104 (44%) trials excluded patients with CKD based on various criteria including serum creatinine (n=48), eGFR (n=17), creatinine clearance (n=4), renal replacement therapy (n=19), and nonspecific description (n=28). Trials that evaluated interventions of class 1 or 2 recommendations in current guidelines—such as statin medication, antiplatelet therapy for general patients with PAD, or supervised exercise—were less likely to exclude patients with CKD (38% versus 53%, P=0.03). Industry-funded trials were more likely to exclude patients with CKD compared with academic- or government-funded ones (54% versus 38%, P=0.04). Trials evaluating endovascular procedures or medications were more likely to exclude patients with CKD compared with those evaluating surgical interventions (52% in endovascular procedures versus 57% in medications versus 21% in surgical interventions, P<0.001). Frequency of exclusion did not differ by time period of publication, trial size, number of centers, location, and diagnostic categories (Table 1). Table 1. - Characteristics of peripheral artery disease trials Characteristics Trials Patients Explicit Exclusion of Kidney Disease Based on Index Report, Methods Report of Registered Protocol, Trials (% [N]) P Value Overall 237 157,520 104 (44%) Publication year 0.16 2000–2004 43 12,848 20 (47%) 2005–2009 45 12,140 15 (33%) 2010–2014 86 78,728 35 (41%) 2015–2018 63 53,804 34 (54%) Class 1/2 recommendation 0.03 Yes 144 62,294 55 (38%) No 93 95,226 49 (53%) Trial enrollment size 0.47 50–99 76 5164 34 (45%) 100–499 136 27,671 61 (45%) 500–999 12 8601 6 (50%) >1000 13 116,084 3 (23%) Sites 0.19 Single center 72 8261 27 (38%) Multicenter 165 149,259 77 (47%) Location 0.68 United States/Canada 82 128,373 39 (48%) Europe 132 25,412 56 (42%) Other (Asia, Australia, South America) 23 3735 9 (39%) Funding source 0.04 Academic grant/government 61 10,143 23 (38%) Industry 90 132,846 49 (54%) Both 20 3132 10 (50%) Not specified 66 11,399 22 (33%) Diagnostic category 0.57 Critical limb ischemia 31 5517 11 (36%) Intermittent claudication 114 29,406 55 (48%) All PAD 39 90,728 16 (41%) Other a 53 31,869 22 (42%) Specific therapeutic class <0.001 Surgery 14 2844 3 (21%) Endovascular 65 10,356 34 (52%) Exercise 28 2947 8 (29%) Medication 90 134,385 51 (57%) Other b 30 4647 6 (20%) More than one intervention 10 2341 2 (20%) PAD, peripheral artery disease.aOther: atherosclerotic disease including patients with PAD, patients with PAD who undergo procedure without specifying clinical presentation.bOther: gene therapy, stem cell therapy, smoking cessation, ultrasound therapy, external beam radiation, phlebotomy, dressing, suture, pneumatic compression, psychologic intervention, remote ischemic preconditioning, brachytherapy, negative pressure wound therapy, ultrasound-guided stent delivery. The criteria for exclusion varied across trials. Of the 104 trials that excluded patients with kidney disease, 48 (46%) used serum creatinine, 17 (16%) used eGFR, 4 (4%) used creatinine clearance, 19 (18%) used KRT of any form, and 28 (27%) used nonspecific qualitative exclusion criteria (such as “significant renal impairment,” “renal dysfunction,” and “severe renal insufficiency”). Among the 48 studies using serum creatinine, the threshold for exclusion was 1.5–2 mg/dl in 20 studies, 2.1–2.9 mg/dl in 24 studies, and ≥3.0 mg/dl in four studies. Among 17 studies using eGFR, the threshold of exclusion was ≤30 ml/min per 1.73 m2 in 13 studies, 31–60 ml/min per 1.73 m2 in two studies, and 61–90 ml/min per 1.73 m2 in one study. The trend of using serum creatinine or nonspecific thresholds did not change across years (P=0.82). Only 27 (11%) trials reported baseline kidney function, with serum creatinine being the most commonly used (n=23) followed by eGFR (n=4), and two trials used both measures. In summary, trials of PAD therapies frequently exclude persons with CKD and use imprecise and inconsistent methods for reporting kidney function. The lower enrollment of patients with CKD in PAD-therapy trials impairs the quality of evidence available in this high-risk population. Frequent use of creatinine rather than the guideline-recommended use of eGFR complicates the interpretation of true kidney function and thus patients with mild CKD may be excluded. We acknowledge several limitations. First, we limited the search to studies published between 2000 and 2018. Given prior data showing that inclusion of persons with CKD in clinical trials has only modestly improved over time, inclusion of older data would only strengthen our case (5). Secondly, we limited our search to trials randomizing >50 patients. Smaller trials may have been more likely to include patients with CKD. However, our results showed consistent rates of exclusion across sample size. Our findings emphasize the need for inclusion of patients with CKD in future PAD trials and the use of eGFR rather than serum creatinine as a method to quantify kidney function. We encourage future studies to include assessment of efficacy and safety related to therapy based on kidney function, and to evaluate the outcomes among patients with CKD. These recommendations will provide evidence to improve PAD care in CKD. Disclosures Dr. Coca reports receiving personal fees from Bayer, CHF Solutions, Goldfinch Bio, InRegen, Janssen, pulseData, Quark, Relypsa, RenalytixAI, and Takeda, all outside of the submitted work; owning stock options in pulseData; and owning equity and stock options in RenalytixAI. Dr. Garimella reports receiving a grant from the University of California, San Diego’s Altman Clinical and Translational Research Institute, speaker fees from Otsuka Pharmaceutical and clinical trial support from Kadmon Corporation outside of the submitted work. Dr. Nadkarni reports receiving personal fees from BioVie, GLG Consulting, and Precision Xtract outside of the submitted work. Dr. Nadkarni is also the Scientific Founder of RenalytixAI and reports receiving grant funding from outside of the submitted work and holding equity in Renalytix AI. Dr. Chan, Dr. Malhotra, Dr. Narula, Dr. Olin, Dr. Paranjpe, Dr. Potok, Dr. Wei, and Dr. Wen have nothing to disclose. Funding Dr. Chan is supported by a National Institutes of Health T32 grant. Dr. Garimella is supported by a grant from National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK; K23 DK114556). Dr. Nadkarni is supported by a grant from the NIDDK (1K23 DK107908-01A1). Dr. Potok is supported by grants from the NIDDK (T32 DK104717), Akebia Therapeutics, Inc. and the American Kidney Fund Clinical Scientist in Nephrology Fellow Program.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.649
Threshold uncertainty score0.934

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0070.007
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.114
GPT teacher head0.422
Teacher spread0.307 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations4
Published2019
Admission routes1
Has abstractyes

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