Trial Oversight

We conducted the Procalcitonin Antibiotic Consensus Trial (ProACT), a patient-level, 1:1 randomized trial, in 14 hospitals in the United States. The trial design and rationale have been published previously.23 The University of Pittsburgh and all site institutional review boards approved the protocol, which is available with the full text of this article at NEJM.org. The National Institute of General Medical Sciences funded the trial and convened an independent data and safety monitoring board (see the Supplementary Appendix, available at NEJM.org). ProACT was coordinated by the University of Pittsburgh Clinical Research, Investigation, and Systems Modeling of Acute Illness Center and the Multidisciplinary Acute Care Research Organization. Procalcitonin assays and laboratory training were provided by bioMérieux, which had no other role in the trial. The investigators remained unaware of the outcomes in each trial group until data lock in October 2017. The authors vouch for the accuracy and completeness of the data and for the fidelity of the trial to the protocol.

Sites and Patients

The sites were predominantly urban academic hospitals that had a high level of adherence to Joint Commission pneumonia core measures,24 and none used procalcitonin in routine care. We enrolled adult patients (≥18 years old) in the emergency department for whom the treating clinician had given an initial diagnosis of acute lower respiratory tract infection (<28 days in duration) but had not yet decided to give or withhold antibiotics and about whom there was uncertainty regarding the need for antibiotics, such that procalcitonin data could influence the prescribing decision. Using baseline characteristics and published criteria, we categorized the initial diagnosis of lower respiratory tract infection into final diagnoses of acute exacerbation of chronic obstructive pulmonary disease (COPD), asthma exacerbation, acute bronchitis, community-acquired pneumonia, and other.11,13,25-31 The definitions and exclusion criteria are provided in the Supplementary Appendix, and full details of the trial are provided in the protocol and statistical analysis plan. All the patients or their authorized representatives provided written informed consent.

Trial Interventions

In both treatment groups, clinicians retained autonomy regarding care decisions. We disseminated national antibiotic guidelines for lower respiratory tract infection and the procalcitonin antibiotic prescribing guideline (Fig. S1 in the Supplementary Appendix) in all promotional tools and training meetings.

In the procalcitonin group, the intervention consisted of measuring and reporting the procalcitonin assay results and providing the procalcitonin guideline to aid the treating clinicians in their interpretation of the results. We measured procalcitonin using a rapid assay with an analytic range of 0.05 to 200 μg per liter (VIDAS B.R.A.H.M.S Procalcitonin, bioMérieux). The guideline used the same cutoff values as had been used previously and approved by the FDA (i.e., with antibiotics strongly discouraged for procalcitonin levels <0.1 μg per liter, discouraged for levels 0.1 to 0.25 μg per liter, recommended for levels >0.25 to 0.5 μg per liter, and strongly recommended for levels >0.5 μg per liter). We obtained blood samples for procalcitonin measurement in the emergency department, and if the patient was hospitalized, 6 to 24 hours later and on days 3, 5, and 7, if the patient was still in the hospital and receiving antibiotics.

We used a multifaceted implementation approach to mimic how a hospital might typically deploy quality-improvement measures when introducing a new intervention (see the Supplementary Appendix). Before the launch of the trial, the site principal investigators sent letters to local primary care providers with a synopsis of the trial. We promoted the rapid delivery of information about procalcitonin to the treating clinicians by tracking delivery times, providing feedback to sites, coordinating the collection of blood samples for the trial with routine morning draws, and embedding the results and guideline into the sites’ electronic health records when feasible (Table S1 in the Supplementary Appendix). If antibiotics were administered when the procalcitonin level was 0.25 μg per liter or lower, the site coordinator queried the treating clinician and recorded the reasons for nonadherence; the coordinators did not ask the clinicians any other questions. We reviewed all cases of nonadherence with the site principal investigators. On discharge, we provided patients with a letter for their primary care provider that included their last procalcitonin assay result, a synopsis of the trial, and the procalcitonin guideline.

In the usual-care group, we drew blood at enrollment for procalcitonin measurement using the same assay, but the results were clinically unavailable. Trial personnel had no bedside role other than the collection of data and blood samples.

Outcome Measures

The primary outcome was total antibiotic exposure, defined as the total number of antibiotic-days within 30 days after enrollment. We defined an antibiotic-day as any day on which a participant received any oral or intravenous antibacterial agent. Our primary safety outcome was a composite of adverse outcomes that could be attributable to withholding antibiotics in lower respiratory tract infection, within 30 days after enrollment (Table S3 in the Supplementary Appendix). Secondary outcomes included prescription of antibiotics in the emergency department, antibiotic receipt by day 30, antibiotic-days during the hospital stay (among patients who were admitted), admission to the intensive care unit, subsequent emergency department visits by day 30, and quality of life as assessed with the Airway Questionnaire 20.32 We obtained data through chart review performed by site research staff and by telephone calls at days 15 and 30 made by coordinating center staff who were unaware of the treatment-group assignments. We collected data on serious adverse events in accordance with federal guidelines.33

Statistical Analysis

We analyzed all data according to the intention-to-treat principle. We used multiple imputations with chained equations for missing outcome data, combined with the use of Rubin’s method.34 For the primary outcome, we hypothesized that procalcitonin-guided antibiotic prescription would be superior to usual care and compared the mean number of antibiotic-days between groups using two-sample t-tests. For the primary safety outcome, we hypothesized that procalcitonin-guided antibiotic prescription would be noninferior to usual care, on the basis of a confidence interval based on a normal distribution for the difference in proportions between groups. The primary efficacy and safety outcomes were considered as coprimary in the design, and significant results for both would be required to declare “success” for the intervention. We initially determined that with 1514 patients, the trial would have at least 80% power to both detect a between-group difference of 1 antibiotic-day and to declare noninferiority on the basis of a predefined noninferiority margin of 4.5 percentage points, with an overall alpha of 0.05, two interim analyses, an assumed 11% rate of adverse outcomes in the usual-care group,8,35 and 10% loss to follow-up. At the second interim analysis in April 2017, the loss to follow-up was 18%, and the data and safety monitoring board approved an increase in enrollment to 1664 patients.

In accordance with CONSORT (Consolidated Standards of Reporting Trials) recommendations for noninferiority trials,36 we conducted a per-protocol analysis in which the intervention group was restricted to patients for whom the trial intervention (i.e., measuring and reporting the procalcitonin results and providing the procalcitonin guideline) was achieved at all time points. To explore the effect of the intervention when clinicians consistently followed the procalcitonin guideline, we conducted a per-guideline analysis in which the intervention group was restricted to patients for whom clinicians adhered to guideline recommendations at all time points. The per-protocol analysis had the potential to be affected by selection bias due to inherent differences between cases in which the protocol was fully executed and those in which it was not; this was also true for the per-guideline analysis for cases in which the clinician was adherent and those in which the clinician was nonadherent.37 We therefore applied instrumental-variable estimation to both analyses, using the randomized assignment as the instrument.38,39

We conducted two sensitivity analyses to assess robustness to missing data: a complete-case analysis, under an assumption that data were missing at random, and a missing-not-at-random analysis, in which all missing data were imputed from the usual-care group.40 We conducted prespecified subgroup analyses of final diagnostic category, age, sex, ethnic group, and race. After unblinding of the data, we performed post hoc analyses to gain an understanding of the primary results. We plotted antibiotic prescription in the emergency department, initial presentation and outcomes, and intervention effect according to initial procalcitonin-level tier, as well as antibiotic exposure over time. To adjust for multiple comparisons, we applied a Bonferroni correction and present 99.86% confidence intervals for the 36 secondary antibiotic-exposure comparisons. We conducted the analyses with R Open software, version 3.4.2 (Microsoft), and SAS software, version 9.4 (SAS Institute). The complete statistical analysis plan is provided in the protocol.