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. © 2014 Giannoni et al.
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
Giannoni A.;Pastormerlo L. E.;
2014-01-01
Abstract
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. © 2014 Giannoni et al.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
