Isoniazid resistance and death in patients with tuberculous meningitis: retrospective cohort study

Objective To determine whether initial isoniazid resistance is associated with death during the treatment of tuberculous meningitis

Rationale and protocol for a cluster randomized pragmatic clinical trial testing behavioral economic implementation strategies to improve tobacco treatment rates for cancer patients who smoke

Background Routine evidence-based tobacco use treatment minimizes cancer-specific and all-cause mortality, reduces treatment-related toxicity, and improves quality of life among patients receiving cancer care. Few cancer centers employ mechanisms to systematically refer patients to evidence-based tobacco cessation services. Implementation strategies informed by behavioral economics can increase tobacco use treatment engagement within oncology care. Methods A four-arm cluster-randomized pragmatic trial will be conducted across nine clinical sites within the Implementation Science Center in Cancer Control Implementation Lab to compare the effect of behavioral economic implementation strategies delivered through embedded messages (or “nudges”) promoting patient engagement with the Tobacco Use Treatment Service (TUTS). Nudges are electronic medical record (EMR)-based messages delivered to patients, clinicians, or both, designed to counteract known patient and clinician biases that reduce treatment engagement. We used rapid cycle approaches (RCA) informed by relevant stakeholder experiences to refine and optimize our implementation strategies and methods prior to trial initiation. Data will be obtained via the EMR, clinician survey, and semi-structured interviews with a subset of clinicians and patients. The primary measure of implementation is penetration, defined as the TUTS referral rate. Secondary outcome measures of implementation include patient treatment engagement (defined as the number of patients who receive FDA-approved medication or behavioral counseling), quit attempts, and abstinence rates. The semi-structured interviews, guided by the Consolidated Framework for Implementation Research, will assess contextual factors and patient and clinician experiences with the nudges. Discussion This study will be the first in the oncology setting to compare the effectiveness of nudges to clinicians and patients, both head-to-head and in combination, as implementation strategies to improve TUTS referral and engagement. We expect the study to (1) yield insights into the effectiveness of nudges as an implementation strategy to improve uptake of evidence-based tobacco use treatment within cancer care, and (2) advance our understanding of the multilevel contextual factors that drive response to these strategies. These results will lay the foundation for how patients with cancer who smoke are best engaged in tobacco use treatment and may lead to future research focused on scaling this approach across diverse centers. Trial registration Clinicaltrials.gov, NCT04737031 . Registered 3 February 2021

Behavioral economic implementation strategies to improve serious illness communication between clinicians and high-risk patients with cancer: protocol for a cluster randomized pragmatic trial

Background Serious illness conversations (SICs) are an evidence-based approach to eliciting patients’ values, goals, and care preferences that improve patient outcomes. However, most patients with cancer die without a documented SIC. Clinician-directed implementation strategies informed by behavioral economics (“nudges”) that identify high-risk patients have shown promise in increasing SIC documentation among clinicians. It is unknown whether patient-directed nudges that normalize and prime patients towards SIC completion—either alone or in combination with clinician nudges that additionally compare performance relative to peers—may improve on this approach. Our objective is to test the effect of clinician- and patient-directed nudges as implementation strategies for increasing SIC completion among patients with cancer. Methods We will conduct a 2 × 2 factorial, cluster randomized pragmatic trial to test the effect of nudges to clinicians, patients, or both, compared to usual care, on SIC completion. Participants will include 166 medical and gynecologic oncology clinicians practicing at ten sites within a large academic health system and their approximately 5500 patients at high risk of predicted 6-month mortality based on a validated machine-learning prognostic algorithm. Data will be obtained via the electronic medical record, clinician survey, and semi-structured interviews with clinicians and patients. The primary outcome will be time to SIC documentation among high-risk patients. Secondary outcomes will include time to SIC documentation among all patients (assessing spillover effects), palliative care referral among high-risk patients, and aggressive end-of-life care utilization (composite of chemotherapy within 14 days before death, hospitalization within 30 days before death, or admission to hospice within 3 days before death) among high-risk decedents. We will assess moderators of the effect of implementation strategies and conduct semi-structured interviews with a subset of clinicians and patients to assess contextual factors that shape the effectiveness of nudges with an eye towards health equity. Discussion This will be the first pragmatic trial to evaluate clinician- and patient-directed nudges to promote SIC completion for patients with cancer. We expect the study to yield insights into the effectiveness of clinician and patient nudges as implementation strategies to improve SIC rates, and to uncover multilevel contextual factors that drive response to these strategies. Trial registration ClinicalTrials.gov , NCT04867850 . Registered on April 30, 2021. Funding National Cancer Institute P50CA24469

First Use of Multiple Imputation with the National Tuberculosis Surveillance System

Aims. The purpose of this study was to compare methods for handling missing data in analysis of the National Tuberculosis Surveillance System of the Centers for Disease Control and Prevention. Because of the high rate of missing human immunodeficiency virus (HIV) infection status in this dataset, we used multiple imputation methods to minimize the bias that may result from less sophisticated methods. Methods. We compared analysis based on multiple imputation methods with analysis based on deleting subjects with missing covariate data from regression analysis (case exclusion), and determined whether the use of increasing numbers of imputed datasets would lead to changes in the estimated association between isoniazid resistance and death. Results. Following multiple imputation, the odds ratio for initial isoniazid resistance and death was 2.07 (95% CI 1.30, 3.29); with case exclusion, this odds ratio decreased to 1.53 (95% CI 0.83, 2.83). The use of more than 5 imputed datasets did not substantively change the results. Conclusions. Our experience with the National Tuberculosis Surveillance System dataset supports the use of multiple imputation methods in epidemiologic analysis, but also demonstrates that close attention should be paid to the potential impact of missing covariates at each step of the analysis