Group sequential testing under instrumented difference-in-differences approach

Unmeasured confounding is a major obstacle to reliable causal inference based on observational studies. Instrumented difference-in-differences (iDiD), a novel idea connecting instrumental variable and standard DiD, ameliorates the above issue by explicitly leveraging exogenous randomness in an exposure trend. In this article, we utilize the above idea of iDiD, and propose a novel group sequential testing method that provides valid inference even in the presence of unmeasured confounders. At each time point, we estimate the average or conditional average treatment effect under iDiD setting using the data accumulated up to that time point, and test the significance of the treatment effect. We derive the joint distribution of the test statistics under the null using the asymptotic properties of M-estimation, and the group sequential boundaries are obtained using theα $$ \alpha $$ -spending functions. The performance of our proposed approach is evaluated on both synthetic data and Clinformatics Data Mart Database (OptumInsight, Eden Prairie, MN) to examine the association between rofecoxib and acute myocardial infarction, and our method detects significant adverse effect of rofecoxib much earlier than the time when it was finally withdrawn from the market.

Operative and Nonoperative Outcomes of Emergency General Surgery Conditions: An Observational Study Using a Novel Instrumental Variable

OBJECTIVE

To determine the effect of operative versus nonoperative management of emergency general surgery conditions on short-term and long-term outcomes.

BACKGROUND

Many emergency general surgery conditions can be managed either operatively or nonoperatively, but high-quality evidence to guide management decisions is scarce.

METHODS

We included 507,677 Medicare patients treated for an emergency general surgery condition between July 1, 2015, and June 30, 2018. Operative management was compared with nonoperative management using a preference-based instrumental variable analysis and near-far matching to minimize selection bias and unmeasured confounding. Outcomes were mortality, complications, and readmissions.

RESULTS

For hepatopancreaticobiliary conditions, operative management was associated with lower risk of mortality at 30 days [-2.6% (95% confidence interval: -4.0, -1.3)], 90 days [-4.7% (-6.50, -2.8)], and 180 days [-6.4% (-8.5, -4.2)]. Among 56,582 intestinal obstruction patients, operative management was associated with a higher risk of inpatient mortality [2.8% (0.7, 4.9)] but no significant difference thereafter. For upper gastrointestinal conditions, operative management was associated with a 9.7% higher risk of in-hospital mortality (6.4, 13.1), which increased over time. There was a 6.9% higher risk of inpatient mortality (3.6, 10.2) with operative management for colorectal conditions, which increased over time. For general abdominal conditions, operative management was associated with 12.2% increased risk of inpatient mortality (8.7, 15.8). This effect was attenuated at 30 days [8.5% (3.8, 13.2)] and nonsignificant thereafter.

CONCLUSIONS

The effect of operative emergency general surgery management varied across conditions and over time. For colorectal and upper gastrointestinal conditions, outcomes are superior with nonoperative management, whereas surgery is favored for patients with hepatopancreaticobiliary conditions. For obstructions and general abdominal conditions, results were equivalent overall. These findings may support patients, clinicians, and families making these challenging decisions.

Examining a Hypothesized Causal Chain for the Effects of the 2007 Repeal of the Permit-to-Purchase Licensing Law in Missouri: Homicide Guns Recovered in State and within a Year of Purchase

Firearm-related deaths are a leading cause of death in the USA. Webster et al. (2014) found an association between Missouri's repeal of a permit-to-purchase handgun licensing law and an increase in firearm-related homicides. The evidence for causality of this association would be strengthened by finding that the increase occurred through the hypothesized mechanism of increasing the ease with which those with violent intent could obtain guns. This study examines two measures: (1) proportion of guns recovered and purchased in-state and (2) time between firearm purchase and recovery by police following criminal use. The repeal was associated from 2008 to 2019 with a 0.05 increase in the proportion own-state gun trace (p < 0.0001, 95% confidence interval: 0.08,0.13) and a 0.10 increase in the proportion of guns recovered prior to 1 year after purchase (p = 0.01, 95% confidence interval: 1.20, 1.90). Our study provides supportive evidence for the repeal increasing firearm-related homicides.

Using Malarial Retinopathy to Improve the Diagnosis of Pediatric Cerebral Malaria

In malaria endemic areas, a high proportion of children have detectable parasitemia but show no clinical symptoms. When comatose from a cause other than malaria, this group confounds the cerebral malaria (CM) definition, making accurate diagnosis challenging. One important biomarker of CM is malarial retinopathy, a set of specific features visible in the ocular fundus. In this study, we quantified the contribution of malarial retinopathy in discriminating malaria-caused coma from non-malaria-caused coma. We estimated that 10% of our study cohort of N = 1,192 patients who met the WHO clinical definition of CM in Malawi had non-malarial coma based on a Gaussian mixture model using the parasite protein Plasmodium falciparum histidine-rich protein-2. A classification based on platelets, white blood cells, and retinopathy significantly improved the discriminative power of a previously established model including only platelets plus white blood cells (area under the receiver operating characteristic curve: 0.89 versus 0.75, P value < 0.001). We conclude that malarial retinopathy is highly predictive of malaria-caused versus non-malaria-caused coma and recommend that an ocular funduscopic examination to determine malarial retinopathy status be included in the assessment of parasitemic comatose African children.

The Future of Causal Inference

The past several decades have seen exponential growth in causal inference approaches and their applications. In this commentary, we provide our top-10 list of emerging and exciting areas of research in causal inference. These include methods for high-dimensional data and precision medicine, causal machine learning, causal discovery, and others. These methods are not meant to be an exhaustive list; instead, we hope that this list will serve as a springboard for stimulating the development of new research.

Long-term effect of machine learning–triggered behavioral nudges on serious illness communication and end-of-life outcomes among patients with cancer: A randomized clinical trial

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Background: Early serious illness conversations (SICs) between oncology clinicians and patients are associated with improved mood, quality of life, and quality of end-of-life (EOL) care. Yet, most patients with cancer die without a documented SIC. We report on pre-specified 40-week SIC and EOL outcomes from a stepped-wedge randomized clinical trial (NCT03984773) testing the impact of clinician-directed behavioral nudges to prompt SICs among patients with cancer at high risk of mortality based on a machine learning algorithm. Methods: Our sample consisted of patients with cancer receiving care at one of 9 tertiary or community-based medical oncology clinics between June 2019 and April 2020. We identified high-risk patients using a prospectively validated electronic health record machine learning algorithm to predict 6-month mortality. The intervention consisted of: (1) Weekly emails comparing individual oncologists’ SIC rate relative to peers; (2) Weekly lists of forthcoming encounters with high-risk patients; and (3) Opt-out text messages to prompt SICs before high-risk patient encounters. Clinics were randomized in stepped-wedge fashion to receive the intervention in 4-week intervals through week 16, when all clinics received the intervention. Patients were followed through week 40. The primary outcome was SIC rates for all and high-risk patients. EOL outcomes among decedents were based on ASCO/NQF guidelines and included death in the hospital, intensive care unit admission within 30 days of death, receipt of systemic therapy within 14 days of death, hospice enrollment prior to death, and hospice length of stay. Intention-to-treat analyses were adjusted for clinic and wedge fixed effects and clustered at the oncologist-level. Results: The sample consisted of 20,506 patients and 41,021 encounters. 1,324 (6.5%) patients died by the end of follow-up. Among high-risk patients, the unadjusted SIC rate was 3.4% (59/1754) in the control period and 13.5% (510/3765) in the intervention period and remained >12% throughout follow-up. In adjusted analyses, the intervention was associated with an increase in SICs (adjusted odds ratio 2.09, 95% CI 1.53-2.87, p<0.001) and a decrease in systemic therapy at the end of life, relative to control (6.8% [72/1066]) vs 9.3% [24/258], adjusted odds ratio 0.27, 95% CI 0.12-0.63, p=0.002). There were no differences between control and intervention patients in hospice enrollment or length of stay, inpatient death, or EOL ICU utilization. Conclusions: In this randomized trial, a machine learning-based behavioral intervention led to a sustained increase in serious illness communication and reduction in EOL systemic therapy among outpatients with cancer. Machine learning and behavioral nudges can lead to long-lasting improvements in cancer care delivery. Clinical trial information: NCT03984773.

Comparing Smoking Cessation Interventions among Underserved Patients Referred for Lung Cancer Screening: A Pragmatic Trial Protocol

Smoking burdens are greatest among underserved patients. Lung cancer screening (LCS) reduces mortality among individuals at risk for smoking-associated lung cancer. Although LCS programs must offer smoking cessation support, the interventions that best promote cessation among underserved patients in this setting are unknown. This stakeholder-engaged, pragmatic randomized clinical trial will compare the effectiveness of four interventions promoting smoking cessation among underserved patients referred for LCS. By using an additive study design, all four arms provide standard "ask-advise-refer" care. Arm 2 adds free or subsidized pharmacologic cessation aids, arm 3 adds financial incentives up to $600 for cessation, and arm 4 adds a mobile device-delivered episodic future thinking tool to promote attention to long-term health goals. We hypothesize that smoking abstinence rates will be higher with the addition of each intervention when compared with arm 1. We will enroll 3,200 adults with LCS orders at four U.S. health systems. Eligible patients include those who smoke at least one cigarette daily and self-identify as a member of an underserved group (i.e., is Black or Latinx, is a rural resident, completed a high school education or less, and/or has a household income <200% of the federal poverty line). The primary outcome is biochemically confirmed smoking abstinence sustained through 6 months. Secondary outcomes include abstinence sustained through 12 months, other smoking-related clinical outcomes, and patient-reported outcomes. This pragmatic randomized clinical trial will identify the most effective smoking cessation strategies that LCS programs can implement to reduce smoking burdens affecting underserved populations. Clinical trial registered with clinicaltrials.gov (NCT04798664). Date of registration: March 12, 2021. Date of trial launch: May 17, 2021.

Implementing nudges to promote utilization of low tidal volume ventilation (INPUT): a stepped-wedge, hybrid type III trial of strategies to improve evidence-based mechanical ventilation management

Background

Behavioral economic insights have yielded strategies to overcome implementation barriers. For example, default strategies and accountable justification strategies have improved adherence to best practices in clinical settings. Embedding such strategies in the electronic health record (EHR) holds promise for simple and scalable approaches to facilitating implementation. A proven-effective but under-utilized treatment for patients who undergo mechanical ventilation involves prescribing low tidal volumes, which protects the lungs from injury. We will evaluate EHR-based implementation strategies grounded in behavioral economic theory to improve evidence-based management of mechanical ventilation.

Methods

The Implementing Nudges to Promote Utilization of low Tidal volume ventilation (INPUT) study is a pragmatic, stepped-wedge, hybrid type III effectiveness implementation trial of three strategies to improve adherence to low tidal volume ventilation. The strategies target clinicians who enter electronic orders and respiratory therapists who manage the mechanical ventilator, two key stakeholder groups. INPUT has five study arms: usual care, a default strategy within the mechanical ventilation order, an accountable justification strategy within the mechanical ventilation order, and each of the order strategies combined with an accountable justification strategy within flowsheet documentation. We will create six matched pairs of twelve intensive care units (ICUs) in five hospitals in one large health system to balance patient volume and baseline adherence to low tidal volume ventilation. We will randomly assign ICUs within each matched pair to one of the order panels, and each pair to one of six wedges, which will determine date of adoption of the order panel strategy. All ICUs will adopt the flowsheet documentation strategy 6 months afterwards. The primary outcome will be fidelity to low tidal volume ventilation. The secondary effectiveness outcomes will include in-hospital mortality, duration of mechanical ventilation, ICU and hospital length of stay, and occurrence of potential adverse events.

Discussion

This stepped-wedge, hybrid type III trial will provide evidence regarding the role of EHR-based behavioral economic strategies to improve adherence to evidence-based practices among patients who undergo mechanical ventilation in ICUs, thereby advancing the field of implementation science, as well as testing the effectiveness of low tidal volume ventilation among broad patient populations.

Trial registration

ClinicalTrials.gov, NCT04663802. Registered 11 December 2020.

Understanding clinical practice and survival outcomes in patients with unresectable stage III non-small-cell lung cancer in a single centre in Quebec

Methods

A retrospective cohort study considered patients 18 or more years of age diagnosed between January 2007 and May 2018 with unresectable stage iii non-small-cell lung cancer (nsclc) who received combined chemoradiation (crt). Survival was analyzed using the Kaplan-Meier method to determine median overall (os) and progression-free survival (pfs) and the associated 95% confidence intervals (cis). Cox regression analysis was performed to identify factors prognostic for survival, including age, sex, smoking status, Eastern Cooperative Oncology Group performance status (ecog ps), histology, treatment type, tumour size, and nodal status.

Results

Of 226 patients diagnosed with unresectable stage iii disease, 134 (59%) received combined crt. Mean age was 63 years; most patients were white, were current smokers, had an ecog ps of 0 or 1, and had nonsquamous histology. Median pfs was 7.03 months (95% ci: 5.6 months to 8.5 months), and os for the cohort was 18.7 months (95% ci: 12.4 months to 24.8 months). Of those patients, 78% would have been eligible for durvalumab consolidation therapy. Univariate analysis demonstrated a significant os benefit (p = 0.010) for concurrent crt (ccrt) compared with sequential crt (scrt). Disease-specific survival remained significantly better in the ccrt group (p = 0.004). No difference in pfs was found between the ccrt and scrt groups. In addition, tumour size and nodal involvement were significant discriminating factors for survival (p < 0.05). In this patient cohort, 64% of patients progressed and received subsequent therapy. Based on multivariate analysis, tumour size and nodal station were the only factors predictive of survival in patients with unresectable stage iii nsclc treated with crt.

Conclusions

Combined crt has been the standard treatment for unresectable stage iii nsclc. In our study, a trend of better survival was seen for ccrt compared with scrt. Factors predictive of survival in patients with stage iii disease treated with crt were tumour size and nodal station. Most patients with stage iii disease would potentially be eligible for durvalumab maintenance therapy based on the eligibility criteria from the pacific trial. The use and effectiveness of novel treatments will have to be further studied in our real-world patient population and similar populations elsewhere.

Effect of integrating machine learning mortality estimates with behavioral nudges to increase serious illness conversions among patients with cancer: A stepped-wedge cluster randomized trial

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Background: Most patients with cancer die without a documented serious illness conversation (SIC) about prognosis and goals. Interventions that increase SICs between oncology clinicians and patients may improve goal-concordant care and end-of-life outcomes. Methods: In this stepped-wedge cluster randomized trial (NCT03984773), we tested the effect of an intervention delivering machine learning-based mortality estimates with behavioral nudges to oncologists to increase SICs among patients with cancer. The clinician-focused intervention consisted of 1) weekly emails providing individual SIC performance feedback (number of SICs in the past month) and peer comparisons; 2) a list of patients scheduled for the next week with a ≥10% predicted risk of 6 month mortality by a validated machine learning prognostic algorithm, and 3) automated opt-out text prompts on the patient’s appointment day to consider an SIC. Eight medical oncology clinics were randomized to receive the intervention in a stepped-wedge fashion every four weeks for a total of 16 weeks. Medical oncology clinicians were included if they were trained to use the SIC Guide (Ariadne Labs, Boston MA). Patients were included if they had an outpatient encounter with an eligible clinician between June 17 and November 1, 2019. The primary outcome was the percent of patient encounters with a documented SIC. Intention to treat analyses adjusted for clinic and wedge fixed effects and clustered at the oncologist level. Results: The sample consisted of 78 clinicians and 14,607 patients. The mean age of patients was 61.7 years, 55.7% were female, 70.4% were white, and 19.6% were black. The percent of patient encounters with an SIC was 1.2% (106/8536) during the pre-intervention period and 4.0% (401/10,152) during the intervention period. In intention to treat adjusted analyses, the intervention led to a significant increase in SICs (adjusted odds ratio, 3.7; 95% CI, 2.5 to 5.4, P value < 0.0001). Conclusions: An intervention consisting of machine learning mortality estimates and behavioral nudges to oncology clinicians increased SICs by three-fold over 16 weeks, a significant difference.This is one of the first studies evaluating a machine learning-based behavioral intervention to improve serious illness communication in oncology. Secondary analyses (completed April 2020) will clarify whether this intervention leads to a sustained increase in SIC rates and improves goal-concordant care and end-of-life outcomes. Clinical trial information: NCT03984773 .

Integrating machine-generated mortality estimates and behavioral nudges to promote serious illness conversations for cancer patients: Design and methods for a stepped-wedge cluster randomized controlled trial

INTRODUCTION

Patients with cancer often receive care that is not aligned with their personal values and goals. Serious illness conversations (SICs) between clinicians and patients can help increase a patient's understanding of their prognosis, goals and values.

METHODS AND ANALYSIS

In this study, we describe the design of a stepped-wedge cluster randomized trial to evaluate the impact of an intervention that employs machine learning-based prognostic algorithms and behavioral nudges to prompt oncologists to have SICs with patients at high risk of short-term mortality. Data are collected on documented SICs, documented advance care planning discussions, and end-of-life care utilization (emergency room and inpatient admissions, chemotherapy and hospice utilization) for patients of all enrolled clinicians.

CONCLUSION

This trial represents a novel application of machine-generated mortality predictions combined with behavioral nudges in the routine care of outpatients with cancer. Findings from the trial may inform strategies to encourage early serious illness conversations and the application of mortality risk predictions in clinical settings.

TRIAL REGISTRATION

Clinicaltrials.gov Identifier: NCT03984773.

Remotely Monitored Gamification and Social Incentives to Improve Glycemic Control Among Adults With Uncontrolled Type 2 Diabetes (iDiabetes): Protocol for a Randomized Controlled Trial

Background

Type 2 diabetes is a significant cause of morbidity and mortality in the United States. Lifestyle modifications including increasing physical activity and losing weight have been demonstrated to improve glycemic control. However, most patients struggle to make these changes. Many stakeholders are interested in using gamification and social incentives to increase engagement in healthy behaviors. However, these approaches often do not appropriately leverage insights from behavioral economics that could be used to address predictable barriers to behavior change.

Objective

This study aimed to describe the protocol for the Influencing DIabetics to Adapt Behaviors related to Exercise and weighT by Enhancing Social incentives (iDiabetes) trial, which aimed to evaluate the effectiveness of gamification interventions that leverage insights from behavioral economics to enhance supportive, competitive, or collaborative social incentives to improve glycemic control, promote weight loss, and increase physical activity among overweight and obese adults with type 2 diabetes.

Methods

We are conducting a one-year four-arm randomized controlled trial of 361 overweight and obese patients with type 2 diabetes and a glycated hemoglobin (HbA_1c) level ≥8.0. Wireless weight scales and wearable devices are provided to remotely monitor weight and physical activity and transmit data to the study team. Patients are recruited by email, following which they establish a baseline measure of weight, daily step count, HbA_1c level, and low-density lipoprotein cholesterol level and then repeat these measures at 6 and 12 months. The control arm receives no other interventions. Patients randomized to one of the three intervention arms are entered into a game designed using insights from behavioral economics to enhance supportive, competitive, or collaborative social incentives. To examine predictors of strong or poor performance, participants completed validated questionnaires on a range of areas including their personality, risk preferences, and social network.

Results

Enrollment of 361 patients was completed in January 2019. Results are expected in 2020.

Conclusions

The iDiabetes trial represents a scalable model to remotely monitor the daily health behaviors of adults with type 2 diabetes. Results from this trial will help provide insights into how to improve management of patients with type 2 diabetes.

Trial Registration

ClinicalTrials.gov NCT02961192; https://clinicaltrials.gov/ct2/show/NCT02961192

International Registered Report Identifier (IRRID)

DERR1-10.2196/14180

Cytology cell blocks are suitable for immunohistochemical testing for PD-L1 in lung cancer

Background

PD-L1 immunohistochemistry (IHC) testing is usually carried out on tissue blocks from core needle biopsy or surgical resections. In this study, we assessed the feasibility of using cytology cell blocks for PD-L1 IHC assay.

Methods

A total of 1419 consecutive cases of non-small-cell lung cancer (NSCLC), including 371 cytology cell blocks, 809 small biopsies, and 239 surgical specimens, were included in the study. The cytology cell blocks were prepared with formalin only, methanol/alcohol only or both. PD-L1 expression was examined by staining with Dako PD-L1 IHC 22C3 pharmDx kit. A Tumor Proportion Score (TPS) was categorized as <1%, 1%-49% and ≥50% tumor cells. A total of 100 viable tumor cells were required for adequacy.

Results

Of the cytology cell blocks, 92% of the specimens had an adequate number of tumor cells, not significantly different from small biopsies. The rate of TPS ≥50% differed between sample types and was observed in 42% of cytology cell blocks versus 36% of small biopsies (P = 0.04), and 29% of surgical resections (P = 0.001). The fixative methods did not affect the immunostaining, with overall PD-L1 high expression (TPS ≥50%) rates of 42% in formalin-fixed specimens versus 40% in specimens with combined fixation by methanol/alcohol and formalin (NS). The PD-L1 high expression rate was not associated with EGFR, ALK or KRAS molecular alterations. Higher stage (IV) was associated with higher PD-L1 TPS (P= 0.001).

Conclusion

Our results show that when the TPS ≥50% is used as the end point, PD-L1 IHC performs well with cytology cell blocks. Cell blocks should be considered as a valuable resource for PD-L1 testing in advanced NSCLC. The clinical significance of higher PD-L1 IHC scores in cytology specimens needs to be evaluated prospectively.

The metastatic site does not influence PD-L1 expression in advanced non-small cell lung carcinoma

INTRODUCTION

PD-L1 expression by immunohistochemistry (IHC) testing with Tumor Proportion Score (TPS) ≥50% and ≥1% is required to be eligible for first- and second-line Pembrolizumab treatment for metastatic non-small cell lung cancer (NSCLC) respectively. Stage IV NSCLC often presents with metastasis to multiple distant sites which are easily accessible for biopsy. Knowing whether PD-L1 IHC TPS can be indifferently measured from different metastatic site is therefore an important clinical question. In this study, we evaluated PD-L1 expression in NSCLC from varied distant metastatic sites.

METHODS

A total of 580 NSCLC specimens of distant metastases were retrieved for study, including 35 paired samples from two different metastatic sites. The metastatic sites included brain, bone, remote lymph nodes, serous membranes (pleura, pericardium and peritoneum), extra-thoracic solid organs and skin/soft tissues. The samples were cytology cell blocks, small biopsies or surgical resections. IHC was performed using Dako PD-L1 IHC 22C3 pharmDx. A total of 100 viable tumor cells was required for adequacy. TPS ≥ 50% and 1-49% were defined as high and low PD-L1 expression respectively.

RESULTS

PD-L1 TPS scores were not significantly different across a range of distant metastatic sites nor between metastases in paired samples.

CONCLUSION

Our results suggest that the PD-L1 TPS scoring is similar across different metastatic sites and any site biopsied will yield necessary information for guiding clinical management.

Effect of Financial Bonus Size, Loss Aversion, and Increased Social Pressure on Physician Pay-for-Performance: A Randomized Clinical Trial and Cohort Study

Importance

Despite limited effectiveness of pay-for-performance (P4P), payers continue to expand P4P nationally.

Objective

To test whether increasing bonus size or adding the behavioral economic principles of increased social pressure (ISP) or loss aversion (LA) improves the effectiveness of P4P.

Design, Setting, and Participants

Parallel studies conducted from January 1 to December 31, 2016, consisted of a randomized clinical trial with patients cluster-randomized by practice site to an active control group (larger bonus size [LBS] only) or to groups with 1 of 2 behavioral economic interventions added and a cohort study comparing changes in outcomes among patients of physicians receiving an LBS with outcomes in propensity-matched physicians not receiving an LBS. A total of 8118 patients attributed to 66 physicians with 1 of 5 chronic conditions were treated at Advocate HealthCare, an integrated health system in Illinois. Data were analyzed using intention to treat and multiple imputation from February 1, 2017, through May 31, 2018.

Interventions

Physician participants received an LBS increased by a mean of $3355 per physician (LBS-only group); prefunded incentives to elicit LA and an LBS; or increasing proportion of a P4P bonus determined by group performance from 30% to 50% (ISP) and an LBS.

Main Outcomes and Measures

The proportion of 20 evidence-based quality measures achieved at the patient level.

Results

A total of 86 physicians were eligible for the randomized trial. Of these, 32 were excluded because they did not have unique attributed patients. Fifty-four physicians were randomly assigned to 1 of 3 groups, and 33 physicians (54.5% male; mean [SD] age, 57 [10] years) and 3747 patients (63.6% female; mean [SD] age, 64 [18] years) were included in the final analysis. Nine physicians and 864 patients were randomized to the LBS-only group, 13 physicians and 1496 patients to the LBS plus ISP group, and 11 physicians and 1387 patients to the LBS plus LA group. Physician characteristics did not differ significantly by arm, such as mean (SD) physician age ranging from 56 (9) to 59 (9) years, and sex (6 [46.2%] to 6 [66.7%] male). No differences were found between the LBS-only and the intervention groups (adjusted odds ratio [aOR] for LBS plus LA vs LBS-only, 0.86 [95% CI, 0.65-1.15; P = .31]; aOR for LBS plus ISP vs LBS-only, 0.95 [95% CI, 0.64-1.42; P = .81]; and aOR for LBS plus ISP vs LBS plus LA, 1.10 [95% CI, 0.75-1.61; P = .62]). Increased bonus size was associated with a greater increase in evidence-based care relative to the comparison group (risk-standardized absolute difference-in-differences, 3.2 percentage points; 95% CI, 1.9-4.5 percentage points; P < .001).

Conclusions and Relevance

Increased bonus size was associated with significantly improved quality of care relative to a comparison group. Adding ISP and opportunities for LA did not improve quality.

Trial Registration

ClinicalTrials.gov Identifier: NCT02634879.

Does the presence of emphysema increase the risk of radiation pneumonitis in lung cancer patients?

Introduction

Radiotherapy (rt) plays an important role in the treatment of lung cancer. One of the most common comorbidities in patients with lung cancer is pulmonary emphysema. The literature offers conflicting data about whether emphysema increases the occurrence and severity of radiation pneumonitis (rp). As a result, whether high doses of rt (with curative intent) should be avoided in patients with emphysema is still unclear.

Objective

We measured the documented incidence of rp in patients with and without emphysema who received curative radiation treatment.

Methods

This retrospective cohort study considered patients in the lung cancer clinical database of the Peter Brojde Lung Cancer Centre. Data from the database has been used previously for research studies, including a recent publication about emphysema grading, based on the percentage of lung occupied by emphysema on computed tomography (ct) imaging.

Results

Using previously published methods, chest ct imaging for 498 patients with lung cancer was scored for the presence of emphysema. The analysis considered 114 patients who received at least 30 Gy radiation. Of those 114 patients, 64 (56%) had emphysema, with approximately 23% having severe or very severe disease. The incidence of rp was 34.4% in patients with emphysema (n = 22) and 32.0% in patients with no emphysema (n = 16, p = 0.48). No difference in the incidence of rp was evident between patients with various grades of emphysema (p = 0.96). Similarly, no difference in the incidence of rp was evident between the two treatment protocols-that is, definitive rt 17 (37%) and combined chemotherapy-rt 21 (31%, p = 0.5).

Conclusions

In our cohort, the presence of emphysema on chest ct imaging was not associated with an increased risk of rp. That finding suggests that patients with lung cancer and emphysema should be offered rt when clinically indicated. However, further prospective studies will be needed for confirmation.

A general approach to evaluating the bias of 2-stage instrumental variable estimators

Unmeasured confounding is a common concern when researchers attempt to estimate a treatment effect using observational data or randomized studies with nonperfect compliance. To address this concern, instrumental variable methods, such as 2-stage predictor substitution (2SPS) and 2-stage residual inclusion (2SRI), have been widely adopted. In many clinical studies of binary and survival outcomes, 2SRI has been accepted as the method of choice over 2SPS, but a compelling theoretical rationale has not been postulated. We evaluate the bias and consistency in estimating the conditional treatment effect for both 2SPS and 2SRI when the outcome is binary, count, or time to event. We demonstrate analytically that the bias in 2SPS and 2SRI estimators can be reframed to mirror the problem of omitted variables in nonlinear models and that there is a direct relationship with the collapsibility of effect measures. In contrast to conclusions made by previous studies (Terza et al, 2008), we demonstrate that the consistency of 2SRI estimators only holds under the following conditions: (1) when the null hypothesis is true; (2) when the outcome model is collapsible; or (3) when estimating the nonnull causal effect from Cox or logistic regression models, the strong and unrealistic assumption that the effect of the unmeasured covariates on the treatment is proportional to their effect on the outcome needs to hold. We propose a novel dissimilarity metric to provide an intuitive explanation of the bias of 2SRI estimators in noncollapsible models and demonstrate that with increasing dissimilarity between the effects of the unmeasured covariates on the treatment versus outcome, the bias of 2SRI increases in magnitude.

Effect of Financial Incentives on Glucose Monitoring Adherence and Glycemic Control Among Adolescents and Young Adults With Type 1 Diabetes: A Randomized Clinical Trial

IMPORTANCE

Glycemic control often deteriorates during adolescence and the transition to young adulthood for patients with type 1 diabetes. The inability to manage type 1 diabetes effectively during these years is associated with poor glycemic control and complications from diabetes in adult life.

OBJECTIVE

To determine the effect of daily financial incentives on glucose monitoring adherence and glycemic control in adolescents and young adults with type 1 diabetes.

DESIGN, SETTING, AND PARTICIPANTS

The Behavioral Economic Incentives to Improve Glycemic Control Among Adolescents and Young Adults With Type 1 Diabetes (BE IN CONTROL) study was an investigator-blinded, 6-month, 2-arm randomized clinical trial conducted between January 22 and November 2, 2016, with 3-month intervention and follow-up periods. Ninety participants (aged 14-20) with suboptimally controlled type 1 diabetes (hemoglobin A1c [HbA1c] >8.0%) were recruited from the Diabetes Center for Children at the Children's Hospital of Philadelphia.

INTERVENTIONS

All participants were given daily blood glucose monitoring goals of 4 or more checks per day with 1 or more level within the goal range (70-180 mg/dL) collected with a wireless glucometer. The 3-month intervention consisted of a $60 monthly incentive in a virtual account, from which $2 was subtracted for every day of nonadherence to the monitoring goals. During a 3-month follow-up period, the intervention was discontinued.

MAIN OUTCOMES AND MEASURES

The primary outcome was change in HbA1c levels at 3 months. Secondary outcomes included adherence to glucose monitoring and change in HbA1c levels at 6 months. All analyses were by intention to treat.

RESULTS

Of the 181 participants screened, 90 (52 [57.8%] girls) were randomized to the intervention (n = 45) or control (n = 45) arms. The mean (SD) age was 16.3 (1.9) years. The intervention group had significantly greater adherence to glucose monitoring goals in the incentive period (50.0% vs 18.9%; adjusted difference, 27.2%; 95% CI, 9.5% to 45.0%; P = .003) but not in the follow-up period (15.3% vs 8.7%; adjusted difference, 3.9%; 95% CI, -2.0% to 9.9%; P = .20). The change in HbA1c levels from baseline did not differ significantly between groups at 3 months (adjusted difference, -0.08%; 95% CI, -0.69% to 0.54%; P = .80) or 6 months (adjusted difference, 0.03%; 95% CI, -0.55% to 0.60%; P = .93).

CONCLUSIONS AND RELEVANCE

Among adolescents and young adults with type 1 diabetes, daily financial incentives improved glucose monitoring adherence during the incentive period but did not significantly improve glycemic control.

TRIAL REGISTRATION

clinicaltrials.gov Identifier: NCT02568501.

Lung cancer care trajectory at a Canadian centre: an evaluation of how wait times affect clinical outcomes

BACKGROUND

Lung cancer continues to be one of the most common cancers in Canada, with approximately 28,400 new cases diagnosed each year. Although timely care can contribute substantially to quality of life for patients, it remains unclear whether it also improves patient outcomes. In this work, we used a set of quality indicators that aim to describe the quality of care in lung cancer patients. We assessed adherence with existing guidelines for timeliness of lung cancer care and concordance with existing standards of treatment, and we examined the association between timeliness of care and lung cancer survival.

METHODS

Patients with lung cancer diagnosed between 2010 and 2015 were identified from the Pulmonary Division Lung Cancer Registry at our centre.

RESULTS

We demonstrated that the interdisciplinary pulmonary oncology service successfully treated most of its patients within the recommended wait times. However, there is still work to be done to decrease variation in wait time. Our results demonstrate a significant association between wait time and survival, supporting the need for clinicians to optimize the patient care trajectory.

INTERPRETATION

It would be helpful for Canadian clinicians treating patients with lung cancer to have wait time guidelines for all treatment modalities, together with standard definitions for all time intervals. Any reductions in wait times should be balanced against the need for thorough investigation before initiating treatment. We believe that our unique model of care leads to an acceleration of diagnostic steps. Avoiding any delay associated with referral to a medical oncologist for treatment could be an acceptable strategy with respect to reducing wait time.

Sensitivity analysis for matched pair analysis of binary data: From worst case to average case analysis

In matched observational studies where treatment assignment is not randomized, sensitivity analysis helps investigators determine how sensitive their estimated treatment effect is to some unmeasured confounder. The standard approach calibrates the sensitivity analysis according to the worst case bias in a pair. This approach will result in a conservative sensitivity analysis if the worst case bias does not hold in every pair. In this paper, we show that for binary data, the standard approach can be calibrated in terms of the average bias in a pair rather than worst case bias. When the worst case bias and average bias differ, the average bias interpretation results in a less conservative sensitivity analysis and more power. In many studies, the average case calibration may also carry a more natural interpretation than the worst case calibration and may also allow researchers to incorporate additional data to establish an empirical basis with which to calibrate a sensitivity analysis. We illustrate this with a study of the effects of cellphone use on the incidence of automobile accidents. Finally, we extend the average case calibration to the sensitivity analysis of confidence intervals for attributable effects.

DOCK2 interacts with FLT3 and modulates the survival of FLT3-expressing leukemia cells

The FMS-like tyrosine kinase-3 (FLT3) gene is the most commonly mutated gene in acute myeloid leukemia (AML), and patients carrying internal tandem duplication (ITD) mutations have a poor prognosis. Long-term inhibition of FLT3 activity in these patients has been elusive. To provide a more complete understanding of FLT3 biology, a mass spectroscopy-based screen was performed to search for FLT3-interacting proteins. The screen identified dedicator of cytokinesis 2 (DOCK2), which is a guanine nucleotide exchange factor for Rho GTPases, and its expression is limited to hematolymphoid cells. We show that DOCK2 is expressed in leukemia cell lines and primary AML samples, and DOCK2 co-immunoprecipitates with wild-type FLT3 and FLT3/ITD. Knock-down (KD) of DOCK2 by shRNA selectively reduced cell proliferation and colony formation in leukemia cell lines with increased FLT3 activity, and greatly sensitized these cells to cytarabine treatment, alone and in combination with FLT3 tyrosine kinase inhibitors. DOCK2 KD in a FLT3/ITD-positive leukemia cell line also significantly prolonged survival in a mouse xenograft model. These findings suggest that DOCK2 is a potential therapeutic target for novel AML treatments, as this protein regulates the survival of leukemia cells with elevated FLT3 activity and sensitizes FLT3/ITD leukemic cells to conventional anti-leukemic agents.

A point-process response model for spike trains from single neurons in neural circuits under optogenetic stimulation

Optogenetics is a new tool to study neuronal circuits that have been genetically modified to allow stimulation by flashes of light. We study recordings from single neurons within neural circuits under optogenetic stimulation. The data from these experiments present a statistical challenge of modeling a high-frequency point process (neuronal spikes) while the input is another high-frequency point process (light flashes). We further develop a generalized linear model approach to model the relationships between two point processes, employing additive point-process response functions. The resulting model, point-process responses for optogenetics (PRO), provides explicit nonlinear transformations to link the input point process with the output one. Such response functions may provide important and interpretable scientific insights into the properties of the biophysical process that governs neural spiking in response to optogenetic stimulation. We validate and compare the PRO model using a real dataset and simulations, and our model yields a superior area-under-the-curve value as high as 93% for predicting every future spike. For our experiment on the recurrent layer V circuit in the prefrontal cortex, the PRO model provides evidence that neurons integrate their inputs in a sophisticated manner. Another use of the model is that it enables understanding how neural circuits are altered under various disease conditions and/or experimental conditions by comparing the PRO parameters.

An exploratory comparative analysis of tyrosine kinase inhibitors or docetaxel in second-line treatment of EGFR wild-type non-small-cell lung cancer: a retrospective real-world practice review at a single tertiary care centre

BACKGROUND

Treatment for advanced non-small-cell lung cancer (nsclc), especially in patients with wild-type EGFR, remains limited. Recently, erlotinib, a tyrosine kinase inhibitor (tki) targeting EGFR mutation, was approved as second-line treatment in EGFR wild-type nsclc. Despite evidence of better overall survival (os) with chemotherapy than with tki in second-line treatment, data on the use of tki in the real-life clinical setting remain limited. The present practice review of tki use for second- and third-line treatment in EGFR wild-type nsclc also compares clinical outcomes for tki and single-agent docetaxel as second-line treatment.

METHODS

Our retrospective cohort study included patients with EGFR wild-type nsclc treated at the Jewish General Hospital (Montreal, QC) between 2003 and 2013. Patients received a tki (erlotinib or gefitinib) in the second and third line or docetaxel in the second line. For each group, we determined os, disease control rate, progression-free survival (pfs), and event-free survival (efs).

RESULTS

The tki group included 145 patients, with 92 receiving second-line treatment. In the control group, 53 patients received docetaxel as second-line therapy. In the tki group, os was 6.0 months; pfs, 2.7 months; and efs, 3.0 months. Comparing second-line treatments, os was 5.3 and 5.0 months respectively (p = 0.88), pfs was 2.5 and 1.8 months respectively (p = 0.041), and efs was 3.0 and 1.7 months respectively (p = 0.009).

CONCLUSIONS

In our study cohort, second-line therapy for EGFR wild-type nsclc with tki (compared with docetaxel) was associated with statistically better pfs and efs and noninferior os. Those findings raise the question of whether efs should also be considered when choosing second-line treatment in this patient population.

Bias in estimating the causal hazard ratio when using two-stage instrumental variable methods

Two-stage instrumental variable methods are commonly used to estimate the causal effects of treatments on survival in the presence of measured and unmeasured confounding. Two-stage residual inclusion (2SRI) has been the method of choice over two-stage predictor substitution (2SPS) in clinical studies. We directly compare the bias in the causal hazard ratio estimated by these two methods. Under a principal stratification framework, we derive a closed-form solution for asymptotic bias of the causal hazard ratio among compliers for both the 2SPS and 2SRI methods when survival time follows the Weibull distribution with random censoring. When there is no unmeasured confounding and no always takers, our analytic results show that 2SRI is generally asymptotically unbiased, but 2SPS is not. However, when there is substantial unmeasured confounding, 2SPS performs better than 2SRI with respect to bias under certain scenarios. We use extensive simulation studies to confirm the analytic results from our closed-form solutions. We apply these two methods to prostate cancer treatment data from Surveillance, Epidemiology and End Results-Medicare and compare these 2SRI and 2SPS estimates with results from two published randomized trials.

Impact of dose-escalated radiation on overall survival in men with nonmetastatic prostate cancer

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Background: Infive publishedRCTs, dose-escalated external beam radiation therapy (EBRT) for prostate cancer resulted in improved biochemical and local control. However, the question of whether dose escalation improves overall survival (OS) remains unanswered. We examined OS among men with non-metastatic prostate cancer undergoing EBRT in the modern era. Methods: Using the National Cancer Database (NCDB), we conducted non-randomized comparative effectiveness studies of dose-escalated versus standard-dose EBRT in men diagnosed from 2004-2006 in three analytic cohorts defined by NCCN risk category: low- (N=12,848), intermediate- (N=14,966) or high-risk (N=14,587) prostate cancer. We categorized patients in each risk cohort into 2 treatment groups: standard-dose (68.4 Gy to <75.6 Gy) or dose-escalated (≥75.6 Gy to 90 Gy) EBRT. The primary outcome was time to death from any cause, measured from diagnosis to NCDB date of death or end of follow-up (December 31, 2011). We compared OS between treatment groups in the three analytic cohorts using Cox proportional hazard models. Inverse probability weighted propensity score methods were used to balance differences between treatment groups in age, race, year of diagnosis, AJCC T- and N-stage, PSA, Gleason score, androgen deprivation therapy, IMRT use, comorbid disease, income, insurance, urban/rural location, facility type and facility volume. In secondary analyses, we evaluated dose response for survival by categorizing dose in approximately 2 Gy increments. Results: Median follow up for survivors was between 73 and 74 months in all three risk cohorts. Dose-escalated EBRT was associated with improved survival in the intermediate-risk (adjusted HR 0.81, 95% CI 0.77 and 0.85, p<0.0001) and high-risk groups (aHR 0.85, 95% CI 0.81 and 0.89, p<0.0001), but not the low-risk group (aHR 0.99, 95% CI 0.92-1.06, p=0.803). For every incremental ~2Gy increase in dose, there was a 9% (95% CI 6% – 11%, p<0.0001) and 7% (95% CI 3% - 10%, p=0.004) reduction in the hazard of death for intermediate- and high-risk patients, respectively. Conclusions: Dose-escalated EBRT is associated with improved survival in men with intermediate- and high-risk, but not low-risk, prostate cancer.