Predictive accuracy of the pneumonia severity index vs CRB-65 for time to clinical stability: Results from the Community-Acquired Pneumonia Organization (CAPO) International Cohort Study

University of Louisville, School of Medicine, Department of Medicine, Division of Infectious Diseases, Louisville, KY 40202, USA.
Respiratory medicine (Impact Factor: 3.09). 11/2010; 104(11):1736-43. DOI: 10.1016/j.rmed.2010.05.022
Source: PubMed


The Pneumonia Severity Index (PSI) and CRB-65 are scores used to predict mortality in patients with community-acquired pneumonia (CAP). It is unknown how well either score predicts time to clinical stability in hospitalized patients with CAP. Thus, it is also not known which score predicts time to clinical stability better.
A secondary analysis of 3087 patients from the Community-Acquired Pneumonia Organization (CAPO) database was performed. Time-dependent receiver-operator characteristic (ROC) curves for time to clinical stability were calculated for the PSI and CRB-65 scores at day seven of hospitalization. Secondary outcomes were to assess the relationship of the PSI and CRB-65 to in-hospital mortality and length of stay (LOS). ROC curves for LOS and mortality were calculated.
The area under the ROC curve (AUC) for time to clinical stability by day seven was 0.638 (95% CI 0.613, 0.660) when using the PSI, and 0.647 (95% CI 0.619, 0.670) while using the CRB-65. The difference in AUC values was not statistically significant (95% CI for difference of -0.03 to 0.01). However, the difference in the AUC values for discharge within 14 days (0.651 for PSI vs 0.63 for CRB-65, 95% CI for difference 0.001-0.049), and 28-day in-hospital mortality (0.738 for PSI vs 0.69 for CRB-65, 95% CI for difference 0.02-0.082) were both statistically significant.
This study demonstrates a moderate ability of both the PSI and CRB-65 scores to predict time to clinical stability, and found that the predictive accuracy of the PSI was equivalent to that of the CRB-65 for this outcome.

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Available from: Guy N Brock
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    • "Results from the ad-hoc estimators are further compared with the advocated way of handling mortality as a competing risk. Differences between the estimators are illustrated using data from the international Community Acquired Pneumonia Organization (CAPO) database [3], as well as simulated data. Supplemental material is also provided which gives illustrative statistical code for investigators to use in their own studies. "
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    ABSTRACT: Hospital length of stay (LOS) and time for a patient to reach clinical stability (TCS) have increasingly become important outcomes when investigating ways in which to combat Community Acquired Pneumonia (CAP). Difficulties arise when deciding how to handle in-hospital mortality. Ad-hoc approaches that are commonly used to handle time to event outcomes with mortality can give disparate results and provide conflicting conclusions based on the same data. To ensure compatibility among studies investigating these outcomes, this type of data should be handled in a consistent and appropriate fashion. Using both simulated data and data from the international Community Acquired Pneumonia Organization (CAPO) database, we evaluate two ad-hoc approaches for handling mortality when estimating the probability of hospital discharge and clinical stability: 1) restricting analysis to those patients who lived, and 2) assigning individuals who die the "worst" outcome (right-censoring them at the longest recorded LOS or TCS). Estimated probability distributions based on these approaches are compared with right-censoring the individuals who died at time of death (the complement of the Kaplan-Meier (KM) estimator), and treating death as a competing risk (the cumulative incidence estimator). Tests for differences in probability distributions based on the four methods are also contrasted. The two ad-hoc approaches give different estimates of the probability of discharge and clinical stability. Analysis restricted to patients who survived is conceptually problematic, as estimation is conditioned on events that happen at a future time. Estimation based on assigning those patients who died the worst outcome (longest LOS and TCS) coincides with the complement of the KM estimator based on the subdistribution hazard, which has been previously shown to be equivalent to the cumulative incidence estimator. However, in either case the time to in-hospital mortality is ignored, preventing simultaneous assessment of patient mortality in addition to LOS and/or TCS. The power to detect differences in underlying hazards of discharge between patient populations differs for test statistics based on the four approaches, and depends on the underlying hazard ratio of mortality between the patient groups. Treating death as a competing risk gives estimators which address the clinical questions of interest, and allows for simultaneous modelling of both in-hospital mortality and TCS / LOS. This article advocates treating mortality as a competing risk when investigating other time related outcomes.
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    ABSTRACT: Adverse outcomes after discharge in patients hospitalized for community-acquired pneumonia (CAP) might be associated with the inflammatory response during hospitalization, recognized by the length of time needed for the patient to reach clinical stability (time to clinical stability [TCS]). The objective of this study was to assess the association between TCS and outcomes after discharge in hospitalized patients with CAP. A retrospective cohort study of consecutive patients discharged alive after an episode of CAP was conducted at the Veterans Hospital of Louisville, Kentucky, between 2001 and 2006. Among the 464 patients enrolled in the study, 82 (18%) experienced an adverse outcome within 30 days after discharge, leading to either readmission or death. Patients with a TCS > 3 days showed a significantly higher rate of adverse outcomes after discharge compared with those with a TCS ≤ 3 days (26% vs 15%, respectively; OR, 1.98; 95% CI, 1.19-3.3; P = .008) as well as adverse outcomes after discharge related to pneumonia (16% vs 4.6%, respectively; OR, 4.07; 95% CI, 2-8.2; P < .001). The propensity-adjusted analysis showed that delay in reaching TCS during hospitalization was associated with a significant increased risk of adverse outcomes. Adjusted ORs comparing patients who reached TCS at days 2, 3, 4, and 5 to those who reached TCS at day 1 were 1.06, 1.54, 2.40, and 10.53, respectively. Patients with CAP who experienced a delay in reaching clinical stability during hospitalization are at high risk of adverse outcomes after discharge and should receive close observation and an early follow-up.
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