Evidence map›Paper›PMID 27207819›Full record

ArticleSeminars in dialysis2016

Balancing the Evidence: How to Reconcile the Results of Observational Studies vs. Randomized Clinical Trials in Dialysis.

Jenny I Shen, Erik L Lum, Tara I Chang

Abstract readEditorial
In one paragraph

Article in Seminars in dialysis, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Jenny I ShenDepartment of Medicine, Division of Hypertension and Nephrology, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, California. jshen@labiomed.org.
Erik L LumDepartment of Medicine, Division of Nephrology, David Geffen School of Medicine at UCLA, Los Angeles, California.
Tara I ChangDepartment of Medicine, Division of Nephrology, Stanford University School of Medicine, Stanford, California.

Funding

Trajectories of Adherence to Cardiovascular Medications in Patients on DialysisK23DK103972 · NIDDK · LUNDQUIST INSTITUTE FOR BIOMEDICAL INNOVATION AT HARBOR-UCLA MEDICAL CENTER · PI SHEN, JENNY I · 2015 to 2019
$934k
Towards optimizing care for cardiovascular disease in chronic kidney diseaseK23DK095914 · NIDDK · STANFORD UNIVERSITY · PI CHANG, TARA I-HSIN · 2013 to 2017
$908k
NIDDK NIH HHS K23 DK095914NIDDK NIH HHS K23 DK103972
6 · The paper itself

Abstract

Because large randomized clinical trials (RCTs) in dialysis have been relatively scarce, evidence-based dialysis care has depended heavily on the results of observational studies. However, when results from RCTs appear to contradict the findings of observational studies, nephrologists are left to wonder which type of study they should believe. In this editorial, we explore the key differences between observational studies and RCTs in the context of such seemingly conflicting studies in dialysis. Confounding is the major limitation of observational studies, whereas low statistical power and problems with external validity are more likely to limit the findings of RCTs. Differences in the specification of the population, exposure, and outcomes can also contribute to different results among RCTs and observational studies. Rigorous methods are required regardless of what type of study is conducted, and readers should not automatically assume that one type of study design is superior to the other. Ultimately, dialysis care requires both well-designed, well-conducted observational studies and RCTs to move the field forward.

Indexed as

Observational Studies as TopicRandomized Controlled Trials as TopicRenal DialysisEvidence-Based MedicineHumansResearch Design

Identifiers

PMID27207819
PMCPMC5014621

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.