Utilization of Medical Services by Veterans Health Study (VHS) Respondents.

The first objective of this study was to profile Veterans Health Study (VHS) respondents\u27 use of medical services-the types of services used, use of a regular source of care, and the propensity to use services for selected symptoms. We focused on differential use of VA and non-VA services and highlighted differences in use by age group. The second objective was to use multivariate analysis to identify factors associated with respondents\u27 use of any medical services and with VA services specifically. We incorporated 2 self-reported variables not used in previous studies of VA utilization-health status and disease burden. Patients receiving ambulatory care services in 4 VA ambulatory outpatient clinics in the greater Boston area were eligible for inclusion in the VHS. A sample of 2425 community-dwelling male veterans was randomly selected from among veterans receiving ambulatory services at Boston-area VA facilities. This analysis focuses on 1909 respondents for whom we had complete data. Interviews and questionnaires were used to collect cross-sectional, observational data on sociodemographic, economic, and clinical characteristics; health status; disease burden; and service-connected disability (SCD) rating. To measure health status, we used 2 summary measures, the Physical Component Summary (PCS) and the Mental Component Summary (MCS), derived from the 8 scales of the Medical Outcomes Study Short Form 36-item Health Survey (MOS SF-36). To measure disease burden, we used the Physical Comorbidity Index (PHYCI) and Mental Comorbidity Index (MENCI), composed of 30 physical and 6 mental health conditions and symptoms, respectively. Information on the availability of non-VA insurance was obtained from administrative VA files. Information on utilization prior to the interview was self-reported. Recall periods of 3 and 12 months were used for ambulatory and inpatient services, respectively. We used descriptive statistics to profile respondents and their utilization patterns. We used multivariate probit models to identify respondent characteristics associated with use of any medical services, medical visits, mental health visits, and hospital stays. Independent variables used in the models were socioeconomic and demographic characteristics, and measures of disease burden, health status, and VA eligibility. The respondents relied heavily on the VA for medical care: 74% of the respondents said the VA was their regular source of care; 72% of all the respondents and 87% of those who had used any medical service in the recall period had used a VA service; 68% of those who were hospitalized used a VA hospital; and 76% of the medical care the respondents received and 60% of their hospital stays were in VA facilities. Younger veterans (aged 22-44) used substantially more mental health services than older respondents, but they were less likely than older veterans to have seen a doctor recently for most of the medical symptoms studied. PHYCI and PCS were significantly related to use of any medical services and to use of inpatient services; MENCI and MCS were significantly related to use of mental health services (

Preliminary validation of a health-related quality of life symptom index for persons treated or actively monitored for anal HSIL (AMC –A02, -A03)

Background: Precancerous anal high-grade squamous intraepithelial lesions (HSIL) and its associated treatments have the potential to reduce health-related quality of life (HRQoL) in impacted individuals. The ANCHOR (ANal Cancer HSIL Outcomes Research) trial aims to determine whether treating anal HSIL, versus active monitoring, is effective in reducing incidence of anal cancer in HIV-infected individuals. The present study sought to establish preliminary psychometric evidence of the 25-item ANCHOR Health-Related Symptom Inventory (A-HRSI). Methods: Eligible ANCHOR participants recruited within two-weeks post-treatment or randomization to active surveillance completed the A-HRSI and well-established legacy HRQoL measures (i.e., Functional Assessment of Cancer Therapy – General [FACT-G] and MD Anderson Symptom Inventory [MDASI]) via telephone. Construct validity was assessed using an exploratory factor analysis (EFA). Pearson correlations were then calculated between summed items within the resulting A-HRSI latent factors and legacy measure outcome subscales to establish convergent and divergent validity. Results: 200 participants were enrolled. EFA provided initial confirmation that the A-HRSI items are best represented by the proposed broad three-factor structure (e.g., physical symptoms, physical impacts, psychological symptoms). These three factors had fair to moderate Pearson correlations with FACT-G Total and MDASI Symptom Severity and Interference subscales. Conclusions: Preliminary psychometric evidence exists to support the construct validity of the A-HRSI, indicating this measure can capture disease- and treatment-related physical and psychological symptoms and physical impacts. Clinical responsiveness and Spanish-translation of this measure will be completed prior to ultimately deploying this measure in the ANCHOR trial to facilitate participant reporting of their HRQoL to inform clinical decision-making

Applications of Methodologies of the Veterans Health Study in the VA Healthcare System: Conclusions and Summary

The Veterans Health Study (VHS) had as its overarching goal the development, testing, and application of patient-centered assessments for monitoring patient outcomes in ambulatory care in large integrated care systems such as the Department of Veterans Affairs (VA). Unlike other previous studies, the VHS has capitalized on rich administrative databases restricted to the VA and linked to patient-centered outcomes. The VHS has developed a comprehensive set of general and disease-specific measures for use by systems of care for ambulatory patients. Chief among these assessments is the Veterans SF-36 Health Survey for measuring health-related quality of life in veteran ambulatory populations. The Veterans SF-36 Health Survey provides the cornerstone for this study and historically has been extensively disseminated and used in the VA with close to 2 million administrations nationally as part of its quality management system. National surveys administered by the VA since 1996 using the Veterans SF-36 Health Survey indicate important regional differences with implications for varying resource needs. Based upon the rich foundation provided by the VHS methodology, the VA has implemented some of these approaches as part of its quality monitoring system and can serve as a model for other large integrated systems of care

Preliminary Validation of a Patient-based Self-assessment Measure of Severity of Illness in Type 2 Diabetes: Results from the Pilot Phase of the Veterans Health Study.

Measures of case mix are needed to control for patients\u27 clinical status in studies assessing the process and outcomes of care. The Veterans Health Study (VHS) is a longitudinal study of determinants of health outcomes in ambulatory veterans. This study assessed the validity of a case-mix measure developed to quantify severity of illness in ambulatory type 2 diabetic patients. As part of the pilot phase of the VHS, 245 veterans using 4 primary care clinics in Boston were screened for diabetes and 5 other chronic illnesses when they presented for care. Subjects screening positive for diabetes returned to complete severity of illness and outcome measures. The variables for the diabetes case-mix module were chosen based upon the principles of parsimony, duration of follow-up, and clinical validity and credibility. Variables were selected to predict function, as measured by the Medical Outcomes Study Short-Form 36 (SF-36). The diabetic patients in this study had a heavy burden of chronic illness, with an average of 3.9 comorbid conditions and a mean general health perceptions score of 48 on the SF-36 (scored from 0 to 100, with 100 indicating best health). A summary variable called DMSEV was created for diabetes severity . This included atherosclerotic complications(stroke, transient ischemic attack or myocardial infarction; chest pain frequency; and claudication), plus any history of eye, foot, or neuropathic symptoms. DMSEV correlated with all 8 outcome scales of the SF-36, and in particular was highly associated with physical function (r=0.49, P=.0001). Least squares linear regression analysis controlling for age and comorbidity confirmed the association of DMSEV with all 8 SF-36 scales. The correlation with physical function remained highly significant (

Brief Report: Comprehensive Clinicogenomic Profiling of Small Cell Transformation From EGFR-Mutant NSCLC Informs Potential Therapeutic Targets

Introduction: NSCLC transformation to SCLC has been best characterized with EGFR-mutant NSCLC, with emerging case reports seen in ALK, RET, and KRAS-altered NSCLC. Previous reports revealed transformed SCLC from EGFR-mutant NSCLC portends very poor prognosis and lack effective treatment. Genomic analyses revealed TP53 and RB1 loss of function increase the risk of SCLC transformation. Little has been reported on the detailed clinicogenomic characteristics and potential therapeutic targets for this patient population. Methods: In this study, we conducted a single-center retrospective analysis of clinical and genomic characteristics of patients with EGFR-mutant NSCLC transformed to SCLC. Demographic data, treatment course, and clinical molecular testing reports were extracted from electronic medical records. Kaplan-Meier analyses were used to estimate survival outcomes. Next generation sequencing-based assays was used to identify EGFR and co-occurring genetic alterations in tissue or plasma before and after SCLC transformation. Single-cell RNA sequencing (scRNA-seq) was performed on a patient-derived-xenograft model generated from a patient with EGFR-NSCLC transformed SCLC tumor. Results: A total of 34 patients were identified in our study. Median age at initial diagnosis was 58, and median time to SCLC transformation was 24.2 months. 68% were female and 82% were never smokers. 79% of patients were diagnosed as stage IV disease, and over half had brain metastases at baseline. Median overall survival of the entire cohort was 38.3 months from initial diagnoses and 12.4 months from time of SCLC transformation. Most patients harbored EGFR exon19 deletions as opposed to exon21 L858R alteration. Continuing EGFR tyrosine kinase inhibitor post-transformation did not improve overall survival compared with those patients where tyrosine kinase inhibitor was stopped in our cohort. In the 20 paired pretransformed and post-transformed patient samples, statistically significant enrichment was seen with PIK3CA alterations (p = 0.04) post-transformation. Profiling of longitudinal liquid biopsy samples suggest emergence of SCLC genetic alterations before biopsy-proven SCLC, as shown by increasing variant allele frequency of TP53, RB1, PIK3CA alterations. ScRNA-seq revealed potential therapeutic targets including DLL3, CD276 (B7-H3) and PTK7 were widely expressed in transformed SCLC. Conclusions: SCLC transformation is a potential treatment resistance mechanism in driver-mutant NSCLC. In our cohort of 34 EGFR-mutant NSCLC, poor prognosis was observed after SCLC transformation. Clinicogenomic analyses of paired and longitudinal samples identified genomic alterations emerging post-transformation and scRNA-seq reveal potential therapeutic targets in this population. Further studies are needed to rigorously validate biomarkers and therapeutic targets for this patient population

Brief Report: Clinical Response, Toxicity, and Resistance Mechanisms to Osimertinib Plus MET Inhibitors in Patients With EGFR-Mutant MET-Amplified NSCLC

Introduction: MET amplification is a known resistance mechanism to EGFR tyrosine kinase inhibitor (TKI) treatment in EGFR-mutant NSCLC. Dual EGFR-MET inhibition has been reported with success in overcoming such resistance and inducing clinical benefit. Resistance mechanisms to dual EGFR-MET inhibition require further investigation and characterization. Methods: Patients with NSCLC with both MET amplification and EGFR mutation who have received crizotinib, capmatinib, savolitinib, or tepotinib plus osimertinib (OSI) after progression on OSI at MD Anderson Cancer Center were included in this study. Molecular profiling was completed by means of fluorescence in situ hybridization (FISH) and next-generation sequencing (NGS). Radiological response was assessed on the basis of Response Evaluation Criteria in Solid Tumors version 1.1. Results: From March 2016 to March 2022, 23 treatments with dual MET inhibitor and osi were identified with a total of 20 patients included. Three patients received capmatinib plus OSI after progression on crizotinib plus OSI. Median age was 64 (38–89) years old and 75% were female. MET amplification was detected by FISH in 14 patients in the tissue, NGS in 10 patients, and circulating tumor DNA in three patients. Median MET gene copy number was 13.6 (6.4–20). Overall response rate was 34.8% (eight of 23). In assessable patients, tumor shrinkage was observed in 82.4% (14 of 17). Median time on treatment was 27 months. Two of three patients responded to capmatinib plus OSI after progression on crizotinib plus OSI. Dual EGFR-MET inhibition was overall well tolerated. Two patients on crizotinib plus OSI and one pt on capmatinib plus OSI discontinued therapy due to pneumonitis. One pt discontinued crizotinib plus OSI due to gastrointestinal toxicity. Six patients were still on double TKI treatment. At disease progression to dual EGFR-MET inhibition, FISH and NGS on tumor and plasma were completed in six patients. Notable resistance mechanisms observed include acquired MET D1246H (n = 1), acquired EGFR C797S (n = 2), FGFR2 fusion (n = 1, concurrent with C797S), and EGFR G796S (n = 1, concurrent with C797S). Four patients lost MET amplification. Conclusions: Dual EGFR and MET inhibition yielded high clinical response rate after progression on OSI. Resistance mechanisms to EGFR-MET double TKI inhibition include MET secondary mutation, EGFR secondary mutation, or loss of MET amplification