TY - JOUR
T1 - Confounding by indication of the safety of de-escalation in community-acquired pneumonia
T2 - A simulation study embedded in a prospective cohort
AU - van Heijl, Inger
AU - Schweitzer, Valentijn A
AU - Boel, C H Edwin
AU - Oosterheert, Jan Jelrik
AU - Huijts, Susanne M
AU - Dorigo-Zetsma, Wendelien
AU - van der Linden, Paul D
AU - Bonten, Marc J M
AU - van Werkhoven, Cornelis H
N1 - Funding Information:
This work received funding from Pfizer for the CAPiTA study to MB, CvW and SH. The funder had a role in the design of the original study and monitored data collection. They had no role in the study design, data analysis, decision to publish, or preparation of the current manuscript. We gratefully acknowledge dr. Claudine Blum (Medizinische Universitätsklinik, Kantonsspital Aarau, Switzerland) and colleagues for sharing unpublished data and Lufang Zhang (University Medical Centre Utrecht, the Netherlands) for assistance with the data analysis.
Publisher Copyright:
© 2019 van Heijl et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
PY - 2019/1/1
Y1 - 2019/1/1
N2 - Observational studies have demonstrated that de-escalation of antimicrobial therapy is independently associated with lower mortality. This most probably results from confounding by indication. Reaching clinical stability is associated with the decision to de-escalate and with survival. However, studies rarely adjust for this confounder. We quantified the potential confounding effect of clinical stability on the estimated impact of de-escalation on mortality in patients with community-acquired pneumonia. Data were used from the Community-Acquired Pneumonia immunization Trial in Adults (CAPiTA). The primary outcome was 30-day mortality. We performed Cox proportional-hazards regression with de-escalation as time-dependent variable and adjusted for baseline characteristics using propensity scores. The potential impact of unmeasured confounding was quantified through simulating a variable representing clinical stability on day three, using data on prevalence and associations with mortality from the literature. Of 1,536 included patients, 257 (16.7%) were de-escalated, 123 (8.0%) were escalated and in 1156 (75.3%) the antibiotic spectrum remained unchanged. Crude 30-day mortality was 3.5% (9/257) and 10.9% (107/986) in the de-escalation and continuation groups, respectively. The adjusted hazard ratio of de-escalation for 30-day mortality (compared to patients with unchanged coverage), without adjustment for clinical stability, was 0.39 (95%CI: 0.19-0.79). If 90% to 100% of de-escalated patients were clinically stable on day three, the fully adjusted hazard ratio would be 0.56 (95%CI: 0.27-1.12) to 1.04 (95%CI: 0.49-2.23), respectively. The simulated confounder was substantially stronger than any of the baseline confounders in our dataset. Quantification of effects of de-escalation on patient outcomes without proper adjustment for clinical stability results in strong negative bias. This study suggests the effect of de-escalation on mortality needs further well-designed prospective research to determine effect size more accurately.
AB - Observational studies have demonstrated that de-escalation of antimicrobial therapy is independently associated with lower mortality. This most probably results from confounding by indication. Reaching clinical stability is associated with the decision to de-escalate and with survival. However, studies rarely adjust for this confounder. We quantified the potential confounding effect of clinical stability on the estimated impact of de-escalation on mortality in patients with community-acquired pneumonia. Data were used from the Community-Acquired Pneumonia immunization Trial in Adults (CAPiTA). The primary outcome was 30-day mortality. We performed Cox proportional-hazards regression with de-escalation as time-dependent variable and adjusted for baseline characteristics using propensity scores. The potential impact of unmeasured confounding was quantified through simulating a variable representing clinical stability on day three, using data on prevalence and associations with mortality from the literature. Of 1,536 included patients, 257 (16.7%) were de-escalated, 123 (8.0%) were escalated and in 1156 (75.3%) the antibiotic spectrum remained unchanged. Crude 30-day mortality was 3.5% (9/257) and 10.9% (107/986) in the de-escalation and continuation groups, respectively. The adjusted hazard ratio of de-escalation for 30-day mortality (compared to patients with unchanged coverage), without adjustment for clinical stability, was 0.39 (95%CI: 0.19-0.79). If 90% to 100% of de-escalated patients were clinically stable on day three, the fully adjusted hazard ratio would be 0.56 (95%CI: 0.27-1.12) to 1.04 (95%CI: 0.49-2.23), respectively. The simulated confounder was substantially stronger than any of the baseline confounders in our dataset. Quantification of effects of de-escalation on patient outcomes without proper adjustment for clinical stability results in strong negative bias. This study suggests the effect of de-escalation on mortality needs further well-designed prospective research to determine effect size more accurately.
UR - https://www.scopus.com/pages/publications/85072701637
U2 - 10.1371/journal.pone.0218062
DO - 10.1371/journal.pone.0218062
M3 - Article
C2 - 31560686
SN - 1932-6203
VL - 14
JO - PLoS ONE
JF - PLoS ONE
IS - 9
M1 - e0218062
ER -