TY - JOUR
T1 - Large-scale external validation and comparison of prognostic models: an application to chronic obstructive pulmonary disease
AU - Guerra, Beniamino
AU - Haile, Sarah R
AU - Lamprecht, Bernd
AU - Ramírez, Ana S
AU - Martinez-Camblor, Pablo
AU - Kaiser, Bernhard
AU - Alfageme, Inmaculada
AU - Almagro, Pere
AU - Casanova, Ciro
AU - Esteban-González, Cristóbal
AU - Soler-Cataluña, Juan J
AU - de-Torres, Juan P
AU - Miravitlles, Marc
AU - Celli, Bartolome R
AU - Marin, Jose M
AU - Ter Riet, Gerben
AU - Sobradillo, Patricia
AU - Lange, Peter
AU - Garcia-Aymerich, Judith
AU - Antó, Josep M
AU - Turner, Alice M
AU - Han, Meilan K
AU - Langhammer, Arnulf
AU - Leivseth, Linda
AU - Bakke, Per
AU - Johannessen, Ane
AU - Oga, Toru
AU - Cosio, Borja
AU - Ancochea-Bermúdez, Julio
AU - Echazarreta, Andres
AU - Roche, Nicolas
AU - Burgel, Pierre-Régis
AU - Sin, Don D
AU - Soriano, Joan B
AU - Puhan, Milo A
PY - 2018
Y1 - 2018
N2 - BACKGROUND: External validations and comparisons of prognostic models or scores are a prerequisite for their use in routine clinical care but are lacking in most medical fields including chronic obstructive pulmonary disease (COPD). Our aim was to externally validate and concurrently compare prognostic scores for 3-year all-cause mortality in mostly multimorbid patients with COPD.METHODS: We relied on 24 cohort studies of the COPD Cohorts Collaborative International Assessment consortium, corresponding to primary, secondary, and tertiary care in Europe, the Americas, and Japan. These studies include globally 15,762 patients with COPD (1871 deaths and 42,203 person years of follow-up). We used network meta-analysis adapted to multiple score comparison (MSC), following a frequentist two-stage approach; thus, we were able to compare all scores in a single analytical framework accounting for correlations among scores within cohorts. We assessed transitivity, heterogeneity, and inconsistency and provided a performance ranking of the prognostic scores.RESULTS: Depending on data availability, between two and nine prognostic scores could be calculated for each cohort. The BODE score (body mass index, airflow obstruction, dyspnea, and exercise capacity) had a median area under the curve (AUC) of 0.679 [1st quartile-3rd quartile = 0.655-0.733] across cohorts. The ADO score (age, dyspnea, and airflow obstruction) showed the best performance for predicting mortality (difference AUCADO - AUCBODE = 0.015 [95% confidence interval (CI) = -0.002 to 0.032]; p = 0.08) followed by the updated BODE (AUCBODE updated - AUCBODE = 0.008 [95% CI = -0.005 to +0.022]; p = 0.23). The assumption of transitivity was not violated. Heterogeneity across direct comparisons was small, and we did not identify any local or global inconsistency.CONCLUSIONS: Our analyses showed best discriminatory performance for the ADO and updated BODE scores in patients with COPD. A limitation to be addressed in future studies is the extension of MSC network meta-analysis to measures of calibration. MSC network meta-analysis can be applied to prognostic scores in any medical field to identify the best scores, possibly paving the way for stratified medicine, public health, and research.
AB - BACKGROUND: External validations and comparisons of prognostic models or scores are a prerequisite for their use in routine clinical care but are lacking in most medical fields including chronic obstructive pulmonary disease (COPD). Our aim was to externally validate and concurrently compare prognostic scores for 3-year all-cause mortality in mostly multimorbid patients with COPD.METHODS: We relied on 24 cohort studies of the COPD Cohorts Collaborative International Assessment consortium, corresponding to primary, secondary, and tertiary care in Europe, the Americas, and Japan. These studies include globally 15,762 patients with COPD (1871 deaths and 42,203 person years of follow-up). We used network meta-analysis adapted to multiple score comparison (MSC), following a frequentist two-stage approach; thus, we were able to compare all scores in a single analytical framework accounting for correlations among scores within cohorts. We assessed transitivity, heterogeneity, and inconsistency and provided a performance ranking of the prognostic scores.RESULTS: Depending on data availability, between two and nine prognostic scores could be calculated for each cohort. The BODE score (body mass index, airflow obstruction, dyspnea, and exercise capacity) had a median area under the curve (AUC) of 0.679 [1st quartile-3rd quartile = 0.655-0.733] across cohorts. The ADO score (age, dyspnea, and airflow obstruction) showed the best performance for predicting mortality (difference AUCADO - AUCBODE = 0.015 [95% confidence interval (CI) = -0.002 to 0.032]; p = 0.08) followed by the updated BODE (AUCBODE updated - AUCBODE = 0.008 [95% CI = -0.005 to +0.022]; p = 0.23). The assumption of transitivity was not violated. Heterogeneity across direct comparisons was small, and we did not identify any local or global inconsistency.CONCLUSIONS: Our analyses showed best discriminatory performance for the ADO and updated BODE scores in patients with COPD. A limitation to be addressed in future studies is the extension of MSC network meta-analysis to measures of calibration. MSC network meta-analysis can be applied to prognostic scores in any medical field to identify the best scores, possibly paving the way for stratified medicine, public health, and research.
KW - Aged
KW - Cohort Studies
KW - Female
KW - Humans
KW - Male
KW - Middle Aged
KW - Prognosis
KW - Pulmonary Disease, Chronic Obstructive/diagnosis
KW - Severity of Illness Index
U2 - https://doi.org/10.1186/s12916-018-1013-y
DO - https://doi.org/10.1186/s12916-018-1013-y
M3 - Article
C2 - 29495970
SN - 1741-7015
VL - 16
SP - 33
JO - BMC medicine
JF - BMC medicine
IS - 33
ER -