TY - JOUR
T1 - 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
AU - Giannoni, Alberto
AU - Baruah, Resham
AU - Leong, Tora
AU - Rehman, Michaela B.
AU - Pastormerlo, Luigi Emilio
AU - Harrell, Frank E.
AU - Coats, Andrew J S
AU - Francis, Darrel P
PY - 2014/1/27
Y1 - 2014/1/27
N2 - Background: Clinicians are sometimes advised to make decisions using thresholds in measured variables, derived from prognostic studies. Objectives: We 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. Methods: First, 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. Results: 33 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 Findings: First, 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. Conclusions: Emphatic therapeutic guidance based on thresholds from observational studies may be ill-founded. We should not assume that optimal thresholds, or any thresholds, exist.
AB - Background: Clinicians are sometimes advised to make decisions using thresholds in measured variables, derived from prognostic studies. Objectives: We 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. Methods: First, 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. Results: 33 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 Findings: First, 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. Conclusions: Emphatic therapeutic guidance based on thresholds from observational studies may be ill-founded. We should not assume that optimal thresholds, or any thresholds, exist.
UR - http://www.scopus.com/inward/record.url?scp=84899618756&partnerID=8YFLogxK
U2 - 10.1371/journal.pone.0081699
DO - 10.1371/journal.pone.0081699
M3 - Article
C2 - 24475020
AN - SCOPUS:84899618756
SN - 1932-6203
VL - 9
JO - PLoS ONE
JF - PLoS ONE
IS - 1
M1 - e81699
ER -