Currently, clinicians rely mostly on population-level treatment effects from RCTs, usually considering the treatment's benefits. This study proposes a process, focused on practical usability, for translating RCT data into personalized treatment recommendations that weighs benefits against harms and integrates subjective perceptions of relative severity. Intensive blood pressure treatment (IBPT) was selected as the test case to demonstrate the suggested process, which was divided into three phases: (1) Prediction models were developed using the Systolic Blood-Pressure Intervention Trial (SPRINT) data for benefits and adverse events of IBPT. The models were externally validated using retrospective Clalit Health Services (CHS) data; (2) Predicted risk reductions and increases from these models were used to create a yes/no IBPT recommendation by calculating a severity-weighted benefit-to-harm ratio; (3) Analysis outputs were summarized in a decision support tool. Based on the individual benefit-to-harm ratios, 62 and 84% of the SPRINT and CHS populations, respectively, would theoretically be recommended IBPT. The original SPRINT trial results of significant decrease in cardiovascular outcomes following IBPT persisted only in the group that received a "yes-treatment" recommendation by the suggested process, while the rate of serious adverse events was slightly higher in the "no-treatment" recommendation group. This process can be used to translate RCT data into individualized recommendations by identifying patients for whom the treatment's benefits outweigh the harms, while considering subjective views of perceived severity of the different outcomes. The proposed approach emphasizes clinical practicality by mimicking physicians' clinical decision-making process and integrating all recommendation outputs into a usable decision support tool.

BACKGROUND: Although pregnant women are believed to have elevated risks of severe influenza infection and are targeted for influenza vaccination, no study to date has examined influenza vaccine effectiveness (IVE) against laboratory-confirmed influenza-associated hospitalizations during pregnancy, primarily because this outcome poses many methodological challenges.

OBJECTIVE: The Pregnancy Influenza Vaccine Effectiveness Network (PREVENT) was formed in 2016 as an international collaboration with the Centers for Disease Control and Prevention; Abt Associates; and study sites in Australia, Canada, Israel, and the United States. The primary goal of this collaboration is to estimate IVE in preventing acute respiratory or febrile illness (ARFI) hospitalizations associated with laboratory-confirmed influenza virus infection during pregnancy. Secondary aims include (1) describing the incidence, clinical course, and severity of influenza-associated ARFI hospitalization during pregnancy; (2) comparing the characteristics of ARFI-hospitalized pregnant women who were tested for influenza with those who were not tested; (3) describing influenza vaccination coverage in pregnant women; and (4) comparing birth outcomes among women with laboratory-confirmed influenza-associated hospitalization versus other noninfluenza ARFI hospitalizations.

METHODS: For an initial assessment of IVE, sites identified a retrospective cohort of pregnant women aged from 18 to 50 years whose pregnancies overlapped with local influenza seasons from 2010 to 2016. Pregnancies were defined as those that ended in a live birth or stillbirth of at least 20 weeks gestation. The analytic sample for the primary IVE analysis was restricted to pregnant women who were hospitalized for ARFI during site-specific influenza seasons and clinically tested for influenza virus infection using real-time reverse transcription polymerase chain reaction.

RESULTS: We identified approximately 2 million women whose pregnancies overlapped with influenza seasons; 550,344 had at least one hospitalization during this time. After restricting to women who were hospitalized for ARFI and tested for influenza, the IVE analytic sample included 1005 women.

CONCLUSIONS: In addition to addressing the primary question about the effectiveness of influenza vaccination, PREVENT data will address other important knowledge gaps including understanding the incidence, clinical course, and severity of influenza-related hospitalizations during pregnancy. The data infrastructure and international partnerships created for these analyses may be useful and informative for future influenza studies.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/11333.

BACKGROUND: To date, no study has examined influenza vaccine effectiveness (IVE) against laboratory-confirmed influenza-associated hospitalizations during pregnancy.

METHODS: The Pregnancy Influenza Vaccine Effectiveness Network (PREVENT) consisted of public health or healthcare systems with integrated laboratory, medical, and vaccination records in Australia, Canada (Alberta and Ontario), Israel, and the United States (California, Oregon, and Washington). Sites identified pregnant women aged 18 through 50 years whose pregnancies overlapped with local influenza seasons from 2010 through 2016. Administrative data were used to identify hospitalizations with acute respiratory or febrile illness (ARFI) and clinician-ordered real-time reverse transcription polymerase chain reaction (rRT-PCR) testing for influenza viruses. Overall IVE was estimated using the test-negative design and adjusting for site, season, season timing, and high-risk medical conditions.

RESULTS: Among 19450 hospitalizations with an ARFI discharge diagnosis (across 25 site-specific study seasons), only 1030 (6%) of the pregnant women were tested for influenza viruses by rRT-PCR. Approximately half of these women had pneumonia or influenza discharge diagnoses (54%). Influenza A or B virus infections were detected in 598/1030 (58%) of the ARFI hospitalizations with influenza testing. Across sites and seasons, 13% of rRT-PCR-confirmed influenza-positive pregnant women were vaccinated compared with 22% of influenza-negative pregnant women; the adjusted overall IVE was 40% (95% confidence interval = 12%-59%) against influenza-associated hospitalization during pregnancy.

CONCLUSION: Between 2010 and 2016, influenza vaccines offered moderate protection against laboratory-confirmed influenza-associated hospitalizations during pregnancy, which may further inform the benefits of maternal influenza vaccination programs.