Randomized Trial of a Volunteer-Led Symptom Assessment Intervention on Documentation, Patient-Reported Outcomes, and Health Care Use Among Veterans With Lung Cancer

PURPOSE

Identification and documentation of Veterans' symptoms are crucial for optimal lung cancer care delivery. The objective of this study was to determine whether a volunteer-led proactive telephone symptom assessment intervention could improve comprehensive symptom documentation.

METHODS

Veterans with lung cancer were randomly assigned to usual care (control group) or usual care with proactive symptom assessment in which a peer volunteer made weekly phone calls to assess patient symptoms under nurse practitioner supervision. The primary outcome was oncologist documentation of symptoms in the electronic health record at all clinical visits within 6 months after enrollment. Secondary outcomes included patient satisfaction with decision, patient activation, health-related quality of life (HRQOL), and symptom burden, measured at baseline, and 3, 6, and 9 months after enrollment, and acute care use within 9 months after enrollment.

RESULTS

Among 60 Veterans randomly assigned, median (range) age was 70.2 (50-86) years; 57 (95.0%) were male. More intervention participants had oncologist documentation of symptoms than control group participants (24 [77.4%] v seven [24.1%], respectively; odds ratio, 16.46 [95% CI, 4.58 to 59.16]). Intervention group participants had greater improvements over time in HRQOL (expected mean difference, 25.3 [95% CI, 15.00 to 35.70]) and patient activation (expected mean difference, 13.6 [95% CI, 3.79 to 23.39]), lower symptom burden (expected mean difference, -6.39 [95% CI, -15.21 to -2.46]), lower rates of emergency room visits (incidence rate ratio, 0.48 [95% CI, 0.30 to 0.75]), and hospitalizations (incidence rate ratio, 0.47 [95% CI, 0.28 to 0.77]) than control group participants.

CONCLUSION

This symptom assessment intervention is an effective strategy for Veterans with lung cancer.

Effect of a Community Health Worker-Led Intervention Among Low-Income and Minoritized Patients With Cancer: A Randomized Clinical Trial

PURPOSE

To determine whether a community health worker (CHW)-led intervention could improve health-related quality of life (HRQoL; primary outcome) more than usual care among low-income and racial and ethnic minoritized populations newly diagnosed with cancer.

METHODS

This randomized clinical trial was conducted from November 1, 2018, until August 31, 2021, in outpatient cancer clinics in Atlantic City, NJ, and Chicago, IL. Hourly low-wage worker members of an employer union health fund age 18 years or older with newly diagnosed solid tumor and hematologic malignancies were randomly assigned 1:1 to usual care (control group) or usual care augmented with a trained CHW for 12 months (intervention group). The CHW assisted participants with advance care planning (ACP), proactively screened symptoms, and referred participants to community-based resources for identified health-related social needs. Usual care comprised nurse case management and benefits redesign (waived copayments and free transportation for any cancer care received at preferred oncology clinics in each city). The primary outcome was HRQoL. Secondary outcomes included patient activation, satisfaction with decision, ACP documentation, health care use, total health care costs, and overall survival.

RESULTS

A total of 160 participants were enrolled. Intervention group participants had a greater increase in mean HRQoL scores at 4-month and 12-month follow-up as compared with baseline than control group participants (expected mean difference, 11.25 [95% CI, 7.28 to 15.22]; 11.29 [95% CI, 6.96 to 15.62], respectively).

CONCLUSION

In this randomized trial, a CHW-led intervention significantly improved HRQoL for low-income and racial and ethnic minoritized patients with cancer more than usual care alone.

An Overview of Current Methods for Real-World Applications to Generalize or Transport Clinical Trial Findings to Target Populations of Interest

It has been well established that randomized clinical trials have poor external validity, resulting in findings that may not apply to relevant - or target - populations. When the trial is sampled from the target population, generalizability methods have been proposed to address the applicability of trial findings to target populations. When the trial sample and target populations are distinct, transportability methods may be applied for this purpose. However, generalizability and transportability studies present challenges, particularly around the strength of their conclusions. We review and summarize state-of-the-art methods for translating trial findings to target populations. We additionally provide a novel step-by-step guide to address these challenges, illustrating principles through a published case study. When conducted with rigor, generalizability and transportability studies can play an integral role in regulatory decisions by providing key real-world evidence.

Transporting observational study results to a target population of interest using inverse odds of participation weighting

Inverse odds of participation weighting (IOPW) has been proposed to transport clinical trial findings to target populations of interest when the distribution of treatment effect modifiers differs between trial and target populations. We set out to apply IOPW to transport results from an observational study to a target population of interest. We demonstrated the feasibility of this idea with a real-world example using a nationwide electronic health record derived de-identified database from Flatiron Health. First, we conducted an observational study that carefully adjusted for confounding to estimate the treatment effect of fulvestrant plus palbociclib relative to letrozole plus palbociclib as a second-line therapy among estrogen receptor (ER)-positive, human epidermal growth factor receptor (HER2)-negative metastatic breast cancer patients. Second, we transported these findings to the broader cohort of patients who were eligible for a first-line therapy. The interpretation of the findings and validity of such studies, however, rely on the extent that causal inference assumptions are met.

Characterizing real world safety profile of oral Janus kinase inhibitors among adult atopic dermatitis patients: evidence transporting from the rheumatoid arthritis population

OBJECTIVE

To address potential safety concerns of Janus Kinase Inhibitors (JAK-Is), we characterized their safety profile in the atopic dermatitis (AD) patient population.

METHODS

In this retrospective observational study, we used propensity score-based methods and a Poisson modeling framework to estimate the incidence of health outcomes of interest (HOI) for the AD patient. To that end, two mutually exclusive cohorts were created using a real world data resource: a rheumatoid arthritis (RA) cohort, where we directly quantify the safety risk of JAK-Is on HOIs, and an AD cohort, that comprises the target population of interest and to whom we transport the results obtained from the RA cohort. The RA cohort included all adults who filled at least one prescription for a JAK-I (tofacitinib, baricitinib, or upadacitinib) between 1 January 2017 and 31 January 2020. The AD cohort consisted of all adults diagnosed with AD during the same period. We first estimated the incidence rate of each HOI in the RA cohort, and then transported the results to the AD population.

RESULTS

The RA and AD cohorts included 5,296 and 261,855 patients, respectively. On average, patients in the AD cohort were younger, more often male, more likely to be Asian, and had higher household income. They also had a lower prevalence of several comorbid conditions including hypertension, chronic kidney disease, obesity, and depression. Overall, the transported incidence rates of the HOIs to the AD cohort were lower than those obtained in the RA cohort by 13-50%.

CONCLUSION

We applied transportability methods to characterize the risk of the HOIs in the AD population and found absolute risks higher than that of the general population. Future work is needed to validate these conclusions in comparable populations.

Improving supportive care for patients with thoracic cancer

1520

Background: Improving lung cancer care among Veterans is a priority within the Veterans Affairs due to higher rates of lung cancer incidence, morbidity, and mortality among Veterans compared to non-veterans. Unaddressed symptom burden is common due to many factors including complex comorbidities, psychosocial challenges, smoking history and limited social support networks. Additionally, complications from social determinants of health can obstruct successful discussions of symptom-burden between Veterans and their clinical care teams which can limit compliance with recommended symptom management strategies. To overcome these barriers, we conducted a randomized controlled trial to test the effectiveness of a lay volunteer-led proactive symptom assessment and symptom intervention. The objective was to determine if the intervention improved clinician documentation from baseline to 6-months post-enrollment compared to usual care. Secondary outcomes included change in patient activation, health-related quality of life (HrQOL), and symptom-burden. Methods: Patients were randomized into the lay volunteer proactive symptom assessment intervention plus usual cancer care (intervention group) or usual cancer care alone (control group). We conducted electronic health record review to assess primary cancer-clinician symptom documentation of Veterans’ symptoms identified as moderate-to-severe at baseline and 6-months using the Edmonton Symptom Assessment Scale. Patient surveys with validated assessments were used to assess patient activation, HrQOL and symptom burden at baseline (time of enrollment) and 6-months post-enrollment. We used regression models to evaluate differences in our primary and secondary outcomes. Results: 60 Veterans were consented and randomized into the study (29 control; 31 intervention). There were no differences in demographic or clinical factors across groups. The median age was 70 years (range 56-85), 95% were male, 70% identified their race as White, 53% were married and 48% had a 2-year or 4-year college degree. The majority had at least 3 comorbidities (54%), diagnosed with stage 3 or 4 (62%) and received systemic treatment with chemotherapy and/or radiation (77%). At 6-months post-enrollment as compared to baseline, the intervention group had greater improvements in symptom documentation (56% from 12.5% vs. 29% from 43%, p = 0.01), greater improvements in patient activation (p<0.001), HrQOL (<0.001), and lower symptom burden (p<0.001) than the control group. Conclusions: Integration of proactive symptom assessment by lay volunteers has a significant and meaningful effect on symptom documentation, patient activation, quality of life, and reducing symptom burden among Veterans with lung cancer. Clinical trial information: NCT03216109.

The effect of a multilevel community health worker-led intervention on health-related quality of life, patient activation, acute care use, and total costs of care: A randomized controlled trial

6500

Background: Low-income and minority populations have less activation in their cancer care, lower health-related quality of life, greater acute care use and total costs of care than affluent and white populations. Community-based interventions are needed to improve patient experiences and quality of cancer care equitably among these populations. We used community-based participatory methods to refine a previously tested intervention for use in urban communities. The intervention, LEAPS, uses community health workers trained to activate patients in discussions with their cancer clinicians regarding advance care planning and symptom-burden and to connect patients with community-based resources to overcome social determinants of health. We conducted a randomized controlled trial of LEAPS in collaboration with an employer-union health plan in Atlantic City, NJ and Chicago, IL. Members of the employer-union health plan with newly diagnosed with hematologic and solid tumor cancers were randomized to the 6-month LEAPS intervention. The objective of the study was to determine whether LEAPS improved quality of life (primary). Secondarily, we evaluated the effect of LEAPS on patient activation, acute care use, and total costs of care. Methods: We used generalized linear regression models to evaluate differences in quality of life and patient activation scores between groups from baseline to 4- and 12-months post-enrollment and regression models offset for length of follow-up to compare emergency department use, hospitalizations, and total costs of care. Results: A total of 160 patients were consented and randomized into the study (80 intervention; 80 control). There were no differences in demographic or clinical factors across groups. The majority were non-White (74%), female (53%), mean age 57 years with breast (31%) or lung cancer (21%) and Stage 3 or 4 (63%) disease. At 4- and 12-months follow-up, the intervention group had greater improvements in quality of life overtime as compared to the control group (difference in difference: 11.5 p < 0.001) and greater change in patient activation overtime (difference in difference: 11.9 (p < 0.001)). At 12-months follow-up there were no differences in emergency department use (0.44 (0.71) versus 0.73 (0.22) p = 0.22) however intervention group participants had fewer hospitalizations (1.55 (0.86) vs. 2.29 (1.31), p = 0.002) and lower median total costs of care ($72,585 vs. $153,980, p = 0.04). Conclusions: Integrating community-based interventions into clinical cancer care delivery for low-income and minority populations can significantly improve patient activation, reduce hospitalizations and total costs of care. These interventions may represent a sustainable resource to facilitate equitable, value-based cancer care. Clinical trial information: NCT03699748.

Feasibility, preliminary efficacy, and accessibility of a twitter-based social support group vs Fitbit only to decrease sedentary behavior in women

BACKGROUND

Health behavior change interventions delivered by social media allow for real-time, dynamic interaction, peer social support, and experimenter-provided content.

AIMS

We tested the feasibility, acceptability, and preliminary efficacy of a novel Twitter-based walking break intervention with daily behavior change strategies and prompts for social support, combined with a Fitbit, vs. Fitbit alone.

METHODS

In a 2-group pilot, 45 sedentary women from a heart clinic were randomized to Twitter + Fitbit activity tracker (Tweet4Wellness, n = 23) or Fitbit-only (control, n = 22). All received a Fitbit and 13 weeks of tailored weekly step goals. Tweet4Wellness consisted of a private Twitter support group, with daily automated behavior change "tweets" informed by behavior change theory, and encouragement to communicate within the group. Feasibility outcomes included recruitment and enrollment numbers, implementation challenges, and number and type of help requests from participants throughout the study period. Preliminary efficacy outcomes provided by Fitbit data were sedentary minutes, number of hours with >250 steps, maximum sitting bout, weighted sedentary median bout length, total steps, intensity minutes (>3.0 METS), and ratio of time spent sitting-to-moving. Acceptability outcomes included level of Twitter participation within Tweet4Wellness, and Likert scale plus open-ended survey questions on enjoyment and perceived effectiveness of intervention components. Survey data on acceptability of the features of the intervention were collected at 13 weeks (end-of-treatment [EOT]) and 22 weeks (follow-up).

RESULTS

The study was feasible, with addressable implementation challenges. Tweet4Wellness participants changed significantly from baseline to EOT relative to control participants on number of active hours p = .018, total steps p = .028, and ratio of sitting-to-moving, p = .014. Only sitting-to-moving was significant at follow-up (p = .047). Among Tweet4Wellness participants, each tweet sent during treatment was associated with a 0.11 increase in active hours per day (p = .04) and a 292-step increase per day (p < .001). Tweet4Wellness participants averaged 54.8 (SD = 35.4) tweets, totaling 1304 tweets, and reported liking the accountability and peer support provided by the intervention.

CONCLUSION

A Twitter-delivered intervention for promoting physical activity among inactive women from a heart clinic was feasible, acceptable, and demonstrated preliminary efficacy in increasing daily active hours, daily total steps, and the ratio of sitting-to-moving from pre to post for the intervention compared with the control. Lessons learned from this pilot suggest that the next study should expand the recruitment pool, refine the intervention to increase group engagement, and select active hours, total steps, and ratio of sitting-to-movement as primary sedentary behavior measures.

How to Apply Multiple Imputation in Propensity Score Matching with Partially Observed Confounders: A Simulation Study and Practical Recommendations

Propensity score matching (PSM) has been widely used to mitigate confounding in observational studies, although complications arise when the covariates used to estimate the PS are only partially observed. Multiple imputation (MI) is a potential solution for handling missing covariates in the estimation of the PS. However, it is not clear how to best apply MI strategies in the context of PSM. We conducted a simulation study to compare the performances of popular non-MI missing data methods and various MI-based strategies under different missing data mechanisms. We found that commonly applied missing data methods resulted in biased and inefficient estimates, and we observed large variation in performance across MI-based strategies. Based on our findings, we recommend 1) estimating the PS after applying MI to impute missing confounders; 2) conducting PSM within each imputed dataset followed by averaging the treatment effects to arrive at one summarized finding; 3) a bootstrapped-based variance to account for uncertainty of PS estimation, matching, and imputation; and 4) inclusion of key auxiliary variables in the imputation model.

Alcohol Use and Breast Cancer Survival among Participants in the Women's Health Initiative

BACKGROUND

Alcohol increases the risk of breast cancer even at moderate levels of intake. However, the relationship between alcohol consumption and mortality among breast cancer patients is less clear.

METHODS

This study included women from the Women's Health Initiative observational study and randomized trial diagnosed with breast cancer (n = 7,835). Cox proportional hazards regression was used to estimate adjusted HRs and 95% confidence intervals (CI) for overall and breast cancer-specific (BCS) mortality associated with drinking alcohol before or after a breast cancer diagnosis. We also assessed whether changes in drinking habits after diagnosis are related to mortality.

RESULTS

Women who were consuming alcohol prior to their breast cancer diagnosis had a nonstatistically significant 24% (95% CI, 0.56-1.04) reduced risk of BCS mortality and a 26% (95% CI, 0.61-0.89) reduced risk of all-cause mortality. Some variation was observed by estrogen receptor (ER) status as alcohol consumption was associated with a 49% (95% CI, 0.31-0.83) reduced risk of BCS mortality among ER(-) patients with no change in risk observed among ER(+) patients (HR = 0.97; 95% CI, 0.31-1.54), though the difference between these risks was not statistically significant (P for interaction = 0.39). Postdiagnosis alcohol consumption, and change in consumption patterns after diagnosis, did not appear to be associated with all-cause or BCS mortality.

CONCLUSION

In this large study, consumption of alcohol before or after breast cancer diagnosis did not increase risks of overall or cause-specific mortality.

IMPACT

Coupled with existing evidence, alcohol consumption is unlikely to have a substantial impact on mortality among breast cancer patients. Cancer Epidemiol Biomarkers Prev; 25(8); 1268-73. ©2016 AACR.

Weight loss on low-fat vs. low-carbohydrate diets by insulin resistance status among overweight adults and adults with obesity: A randomized pilot trial

OBJECTIVE

To test for differential weight loss response to low-fat (LF) vs. low-carbohydrate (LC) diets by insulin resistance status with emphasis on overall quality of both diets.

METHODS

Sixty-one adults, BMI 28-40 kg/m(2) , were randomized in a 2 × 2 design to LF or LC by insulin resistance status in this pilot study. Primary outcome was 6-month weight change. Participants were characterized as more insulin resistant (IR) or more insulin sensitive (IS) by median split of baseline insulin-area-under-the-curve from an oral glucose tolerance test. Intervention consisted of 14 one-hour class-based educational sessions.

RESULTS

Baseline % carbohydrate:% fat:% protein was 44:38:18. At 6 months, the LF group reported 57:21:22 and the LC group reported 22:53:25 (IR and IS combined). Six-month weight loss (kg) was 7.4 ± 6.0 (LF-IR), 10.4 ± 7.8 (LF-IS), 9.6 ± 6.6 (LC-IR), and 8.6 ± 5.6 (LC-IS). No significant main effects were detected for weight loss by diet group or IR status; there was no significant diet × IR interaction. Significant differences in several secondary outcomes were observed.

CONCLUSIONS

Substantial weight loss was achieved overall, but a significant diet × IR status interaction was not observed. Opportunity to detect differential response may have been limited by the focus on high diet quality for both diet groups and sample size.