SynthesisPloS one2014
Do optimal prognostic thresholds in continuous physiological variables really exist? Analysis of origin of apparent thresholds, with systematic review for peak oxygen consumption, ejection fraction and BNP.
Synthesis in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 24 papers, 1 of them a synthesis that pooled 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.
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.
Who cites it
24 citing papers in PubMed, 1 synthesis or guideline pooled it, 48 citations in OpenAlex.
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- Article
Corrections and comments
- Erratum issued
Authors and funding
8 authors at 5 institutions in 4 countries.
Funding
Abstract
backgroundClinicians are sometimes advised to make decisions using thresholds in measured variables, derived from prognostic studies.
objectivesWe studied why there are conflicting apparently-optimal prognostic thresholds, for example in exercise peak oxygen uptake (pVO2), ejection fraction (EF), and Brain Natriuretic Peptide (BNP) in heart failure (HF). DATA SOURCES AND ELIGIBILITY CRITERIA: Studies testing pVO2, EF or BNP prognostic thresholds in heart failure, published between 1990 and 2010, listed on Pubmed.
methodsFirst, we examined studies testing pVO2, EF or BNP prognostic thresholds. Second, we created repeated simulations of 1500 patients to identify whether an apparently-optimal prognostic threshold indicates step change in risk.
results33 studies (8946 patients) tested a pVO2 threshold. 18 found it prognostically significant: the actual reported threshold ranged widely (10-18 ml/kg/min) but was overwhelmingly controlled by the individual study population's mean pVO2 (r = 0.86, p<0.00001). In contrast, the 15 negative publications were testing thresholds 199% further from their means (p = 0.0001). Likewise, of 35 EF studies (10220 patients), the thresholds in the 22 positive reports were strongly determined by study means (r = 0.90, p<0.0001). Similarly, in the 19 positives of 20 BNP studies (9725 patients): r = 0.86 (p<0.0001). Second, survival simulations always discovered a "most significant" threshold, even when there was definitely no step change in mortality. With linear increase in risk, the apparently-optimal threshold was always near the sample mean (r = 0.99, p<0.001). LIMITATIONS: This study cannot report the best threshold for any of these variables; instead it explains how common clinical research procedures routinely produce false thresholds. KEY
findingsFirst, shifting (and/or disappearance) of an apparently-optimal prognostic threshold is strongly determined by studies' average pVO2, EF or BNP. Second, apparently-optimal thresholds always appear, even with no step in prognosis.
conclusionsEmphatic therapeutic guidance based on thresholds from observational studies may be ill-founded. We should not assume that optimal thresholds, or any thresholds, exist.
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Registered trials
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.