Cancer Clinical Trials Research Articles

Blue-button: A tool for institution-agnostic, EHR-integrated regional clinical trial matching.

65 Background: Research indicates that most people with cancer are willing to enroll in clinical trials when offered the chance, but only 7% actually participate in cancer treatment trials. Barriers to screening and enrollment include time and effort for providers to screen patients for trials, and lack of awareness of available regional trials. Stakeholders recommended creation of free, automated screening tools and processes integrated into provider workflows, directly interfacing with site electronic health records (EHRs), that would search for regional trial eligibility. The need for such tools was independently identified in a large national survey of oncology providers. Methods: The Blue-button tool was developed to automatically identify relevant, regional clinical trials. A collaboration between ACS CAN and MITRE, a not-for-profit organization working in the public interest, created the tool’s functionality. Clinical workflow and research protocol were developed in collaboration with University of Texas Southwestern Simmons Comprehensive Cancer Center. This SMART-on-FHIR application works within existing EHR systems by automatically extracting and sending limited, deidentified patient data elements to third-party trial matching services via the FHIR mCODE standard, a core set of non-proprietary, open-source structured data elements that establishes minimum standards for the structure and content of oncology data in health records. Potential trial matches within a specified radius of the practice are returned in a standard format using the FHIR Research Study resource. Results: Blue-button extracts limited patient data from EHR and provides it in an interface allowing users to update data before sending to trial matching services. Only non-identifiable information is sent to the external clinical trial matching services, which then return prescreen trial matches for manual review to confirm patient eligibility. Thus, with a few clicks in a medical record, the tool quickly identifies comprehensive trial availability within a specified distance of the patient’s location. When used by providers, Blue-button reduces the manual burden that often prevents consideration of clinical trials and identifies regional opportunities beyond the treating institution. Conclusions: Successful feasibility testing demonstrated the effectiveness of automated regional trial screening as a model. We have launched a clinical trial at two sites to assess the effectiveness of the Blue-button tool with patients in healthcare settings. We expect patient enrollment to continue through part or all of 2025. This trial of the Blue-button tool will provide additional information on provider accessibility and uptake and will demonstrate whether EHR-integrated regional trial screening leads to increased opportunities and enrollment in cancer clinical trials. Clinical trial information: NCT05885880 .

Previously unrecognized and potentially consequential challenges facing Hsp90 inhibitors in cancer clinical trials.

Targeting the heat shock protein-90 (Hsp90)chaperone machinery in various cancers with 200 monotherapyor combined-therapy clinical trials since 1999 has not yielded any success of food and drug administration approval. Blames for the failures were unanimously directed at the Hsp90 inhibitorsortumors or both. However, analyses of recent cellular and genetic studies together with the Hsp90 data from the Human Protein Atlas database suggest that the vast variations in Hsp90 expression among different organs in patients might have been the actual cause. It is evident now that Hsp90β is the root of dose-limiting toxicity (DLT), whereas Hsp90α is a buffer of penetrated Hsp90 inhibitors. The more Hsp90α, the safer Hsp90β, and the lower DLT are for the host. Unfortunately, the dramatic variations of Hsp90, from total absence in theeye, muscle, pancreas, and heart to abundance in reproduction organs, lung, liver, and gastrointestinal track, would cause the selection of any fair toxicity biomarker and an effective maximum tolerable dose (MTD) of Hsp90 inhibitor extremely challenging. In theory, a safe MTD for the organs with high Hsp90 could harm the organs with low Hsp90. In reverse, a safe MTD for organs with low or undetectable Hsp90 would have little impact on the tumors, whose cells exhibit average 3-7% Hsp90 over the average 2-3% Hsp90 in normal cells. Moreover, not all tumor cell lines tested follow the "inhibitor binding-client protein degradation" paradigm. It is likely why the oral Hsp90 inhibitor TAS-116 (Pimitespib), which bypasses blood circulation and other organs, showed some beneficiary efficacy by conveniently hitting tumors along the gastrointestinal track. The critical question is what the next step will be for the Hsp90 chaperone as a cancer therapeutic target.

Enhancing minority participation in cancer clinical trials: Insights from a mixed methods study.

70 Background: The urgency to enhance cancer clinical trial enrollment among racial and ethnic minority patients is underscored by the rise in novel therapies. This study examines referral mechanisms from a community-based oncology care clinic to an academic medical center, evaluates the clinical trial knowledge of minority groups, and explores perceptions and attitudes toward trials. Methods: Using a sequential explanatory mixed methods research design, Clinical Trial Knowledge Survey was administered to patients seen at the Hem/Onc clinic in a community-medical center. Descriptive statistics were calculated and multivariate analysis were used to examine associations between variables using STATA 18. Qualitative data from 10 semi-structured interviews were analyzed by two independent investigators using NVivo 14. Themes were identified through a combination of deductive and inductive approaches. Results: Of the 502 mailers sent, 97 individuals responded (response rate of 9.56%). Average age of participants was 54 years, predominantly single and African American. Majority of the of respondents (62%) agreed that patient participation is crucial for generating new and effective treatments. 65% believed that clinical trials are typically conducted on drugs presumed to be effective. However, 32.99% of the respondents perceived participation in clinical trials as a frightening experience. Four qualitative themes emerged: (i) Engagement with one’s health varied between participants. (ii) While clinical trial awareness was limited, willingness to participate was strongly endorsed. (iii) Clinical trial decision-making is a complex process heavily influenced by awareness of and attitudes toward clinical trials. (iv) There is a need to tailor educational strategies to increase awareness of and participation in clinical trials. Conclusions: Our findings emphasize the critical role of awareness and tailored, culturally congruent educational strategies that are crucial to bridge the knowledge gap, alleviate hesitations, and enhance cancer clinical trial participation rates among racial and ethnic minorities.

Patient-Reported Outcomes in Early Phase Trials for Patients with Myelodysplastic Syndromes

Patients with myelodysplastic syndromes (MDS) or acute myeloid leukemia (AML) experience a wide range of symptoms due both to their underlying disease and the effects of treatment. Designing early phase trials to explore effective therapies in these patients should not only examine anti-tumor activity, but also consider the effects of treatments on how patients feel and function. Assessing symptomatic toxicities associated with new therapies in early phase trials from the patient perspective is best measured using patient-reported outcomes (PROs) and offers valuable insight and complementary information to the traditional adverse event reporting in cancer clinical trials. This review describes PROs, highlights their importance in MDS drug development, and outlines the key psychometric properties and practical considerations that make PROs essential and desirable in evaluating the impact of new therapies. We will provide a general overview of PROs and follow with application of PROs in MDS/AML including strategies to be considered in early phase trials. Finally, we describe the creation of the Office of Patient-Centered Outcomes Research at the US National Institutes of Health which has developed a standardized PROs methodology for early phase trials conducted in the Center for Cancer Research at the US National Cancer Institute.

Building partnerships to improve clinical trial accrual in rural and Native American communities through community health educator interventions.

180 Background: Rural populations and racial minorities are often underrepresented in cancer clinical trials. The low representation is determined by multilevel factors, including lack of geographic access to facilities in rural locations and mistrust in the medical and scientific community. Presented here are partial results of an educational intervention to improve clinical trials-related knowledge among rural residents and racial minorities. Methods: The Center to Reduce Cancer Health Disparities (CRCHD) from the National Cancer Institute (NCI) developed the study materials, that were available in English or Spanish, to be utilized according to participants' preferences. The University of Wisconsin Carbone Cancer Center implemented this intervention in northern Wisconsin, which consisted of a baseline questionnaire, a recorded educational intervention, and a post-educational questionnaire. The chosen community is largely rural and Native. The questionnaires consisted of 11-knowledge- and 6-intention-related questions. After being screened by the rural Community Health Educator (CHE), subjects self-administered the intervention online or received the intervention from the CHE during tribal or other educational group events in rural communities. Results: Between January and May 2024, 62 participants started the intervention. Participants’ mean age was 45.1 (±15.36) years, 64.5% (40/62) were female, and 53.2% (33/62) self-identified as American Indian/ Alaska Native. All resided in rural community, defined as Rural-Urban Continuum Codes 7 or 8. Three participants did not respond to the post-educational questionnaire, and one skipped its intentions section. Although the two questions about informed consent presented the highest percent of correct answers post-intervention, the median total knowledge score pre and post-intervention remained the same (p>0.05). Post-intervention, participants more often agreed it is important for minority groups to participate in clinical trials, reported being likely to search for a clinical trial they might be eligible for, join a clinical trial, and talk to family/friends about joining a clinical trial (p<0.05). Conclusions: The CHE successfully engaged rural community members to participate in the intervention. In addition, the intervention facilitated building trust and partnerships for future cancer-related community driven work.

EP.06B.18 Biomarker Landscape of Antibody-Drug Conjugates and Bispecific Antibodies in Clinical Trials for Lung Cancer

EP.06B.18 Biomarker Landscape of Antibody-Drug Conjugates and Bispecific Antibodies in Clinical Trials for Lung Cancer

Assay for the quantification of abemaciclib, its metabolites, and olaparib in human plasma by liquid chromatography-tandem mass spectrometry

An isotope-dilution bioanalytical assay for abemaciclib and its metabolites in combination with olaparib was developed and validated in human plasma K2 EDTA. For the quantitative assay, human plasma samples (or human plasma QC samples) were spiked with internal standard solution before a simple protein precipitation with methanol. The extract was injected onto a liquid chromatography-tandem mass spectrometry (LC-MS/MS) instrument where it was chromatographically separated by a polar end-capped reversed phase column and guard using gradient elution with water and methanol both modified with 0.2% formic acid (v/v) as the mobile phases. The analytes and internal standards were measured by heated electrospray ionization (HESI) in positive polarity using selected reaction monitoring (SRM) on a triple quadrupole mass spectrometer. The assay was validated for linear ranges as follows: 0.4 – 1000nM abemaciclib, 0.35 – 1000nM M2 and M18, 0.5 – 1000nM M20, and 0.75 – 1000nM olaparib. The inter-day or between day precision for the quality controls (n = 18) was < 13% and the accuracy was ± 12%, for all analytes, including the lower limit of quantification (LLOQ). The intra-day or within day precision for the quality controls (n = 6) was ≤ 11% and the accuracy was ± 12% for low, mid, and high and < 19% at LLOQ. The recovery in human plasma was determined to be between 92 and 102% for all analytes spanning the linear range. The validated, bioanalytical quantitative assay was designed to measure abemaciclib, its metabolites, and olaparib for pharmacokinetic evaluation of patients in clinical trials for breast, brain, and ovarian cancers.

Biomarker Landscape of Antibody Drug Conjugates (ADCs) and Bispecific Antibodies in Clinical Trials for Lung Cancer

Biomarker Landscape of Antibody Drug Conjugates (ADCs) and Bispecific Antibodies in Clinical Trials for Lung Cancer

Coping strategies and patient-reported outcomes (PROs) in early phase cancer clinical trial (EP-CT) participants.

245 Background: Individuals with cancer often rely on various coping strategies as they navigate their cancer course. Little is known about coping strategies among patients enrolled on EP-CTs or associations of these coping strategies with other PROs. Methods: We prospectively enrolled adults with cancer participating in EP-CTs at Massachusetts General Hospital from 4/2021-1/2023. Participants completed baseline surveys prior to EP-CT initiation that assessed coping strategies (Brief COPE), quality of life (QOL; Functional Assessment of Cancer Therapy-General), hope (Herth Hope Index), depression/anxiety symptoms (Patient Health Questionnaire-4), and financial wellbeing (COST tool). We used regression models to explore associations of coping strategies with patient characteristics and PROs (QOL, hope, depression/anxiety symptoms, financial wellbeing). Results: Among 205 participants (median age=63.3 [range: 31.8-88.6], 57% female), the most common cancer types were gastrointestinal (35%) and breast (20%). Patients in this cohort utilized the following coping strategies (range 0-6): acceptance (mean=4.81), emotional support (mean=4.63), active (mean=4.30), positive reframing (mean=3.13), religion (mean=2.77), self-blame (mean=.87), denial (mean=.59), and behavioral disengagement (mean=.36). Older age was associated with decreased use of self-blame coping (B=-0.02, p=.025). Female sex was associated with higher scores for denial (B=0.42, p=.009), emotional support (B=0.50, p=.037), positive reframing (B=0.57, p=.036), and religion (B=1.02, p=.001) coping compared with males. See table for associations of coping strategies with PROs (QOL, hope, depression/anxiety symptoms, financial wellbeing). Conclusions: In this cohort of EP-CT participants, we demonstrated that patients use multiple coping strategies and identified differences by age and sex. Notably, we found that some coping behaviors (acceptance, emotional support, positive reframing) were more favorably associated with QOL, hope, depression/anxiety symptoms, and financial wellbeing than others (denial, self-blame, behavioral disengagement). Interventions seeking to enhance PROs in this population should address patients’ use of coping strategies. Coping Strategy QOL Depression Anxiety Hope Financial Wellbeing Beta P Beta P Beta P Beta P Beta P Denial -2.81 .001 0.27 &lt;.001 0.39 &lt;.001 -1.26 &lt;.001 -0.96 .100 Active 0.51 .428 -0.06 .315 0.01 .874 0.98 &lt;.001 0.84 .065 Acceptance 3.13 &lt;.001 -0.15 .013 -0.22 .004 1.31 &lt;.001 1.40 .003 Self-Blame -5.30 &lt;.001 0.44 &lt;.001 0.56 &lt;.001 -1.35 &lt;.001 -2.94 &lt;.001 Emotional Support 1.34 .023 -0.12 .014 0.004 .945 1.03 &lt;.001 0.39 .328 Positive Reframing 1.19 .027 -0.11 .020 -0.08 .184 1.12 &lt;.001 0.13 .715 Behavioral Disengagement -5.99 &lt;.001 0.62 &lt;.001 0.52 &lt;.001 -2.66 &lt;.001 -1.38 .112 Religion 0.57 .195 -0.04 .307 -0.01 .812 0.62 &lt;.001 -0.31 .309

Patient enrollment to industry- versus NIH-sponsored cancer clinical trials.

46 Background: The conduct of cancer clinical research in the U.S. is supported by both private and public sponsors. Industry aims to obtain new drug approvals. Federally-sponsored trials examine a broad set of research questions that are not typically addressed by industry; these trials, which are also more commonly conducted in diverse populations, were recently shown to have contributed to gains of 14 million life-years for patients with cancer. Despite the different mandates, the proportion of patients who participate in industry vs. federally-sponsored cancer studies is unknown. Methods: We evaluated trial enrollment patterns from 2008-2022 using ClinicalTrials.gov data. The ratio of enrollments attributable to industry versus federal sponsors was estimated. A large set of 990 estimates based on different combinations of study characteristics were generated. Point estimates were determined as the mean of combinations and confidence limits by the interquartile range (IQR). Five-year intervals were examined to smooth annual variation. Results: N=26,080 studies were examined. The estimated enrollment ratio from 2018-2022 for all industry vs. federally-sponsored trials was 8.1 (IQR:6.2-9.9). For adult trials, the ratio increased from 4.8 (IQR:4.4-5.3) during 2008-2012 to 9.6 (IQR:7.4-11.8) during 2018-2022; for trials in children, the ratio increased from 0.7 (IQR:0.6-0.7) to 2.3 (IQR:1.8-2.7). For adult trials, annual enrollment attributable to industry sponsorship increased from 54,127 in 2008-2012 to 113,527 for 2018-2022. In contrast, annual enrollment counts for federally-sponsored trials were flat over the entire study period, including 11,282/year for 2008-2012 and 11,798/year in 2018-2022, even as incident cancer cases in the U.S. increased 18% from 1.53 million in 2010 to 1.81 million in 2020. Conclusions: In the U.S., there is a growing reliance on industry to conduct cancer clinical research. Underinvestment in federally-sponsored research comes at a cost for both patients and researchers, with lost opportunities for scientific, clinical, and population advances.

Language-based exclusion associations with racial and ethnic disparities in thyroid cancer clinical trials

BackgroundRacial and ethnic disparities in thyroid cancer care may be mitigated by improving enrollment of more diverse patient populations in clinical trials. We studied trial eligibility criteria and enrollment to assess barriers to equitable representation. MethodsClinicalTrials.gov was searched for studies on thyroid cancer treatment conducted between 1993 and 2023. The inclusion and exclusion criteria of each study were examined. For published studies, reported demographic information was collected. Observed enrollment by race was compared with the expected distribution as determined using data from the US Census and the National Cancer Institute’s Surveillance, Epidemiology, and End Results (SEER) databases. Over- and under-representation was defined as the ratio of observed to expected (O/E) enrollment by the race and ethnicity group. ResultsOf 309 thyroid cancer–related trials, 23 (7.4%) used language as an exclusion criterion. Most were interventional (n = 239, 77.3%), university-initiated (194, 62.8%), and drug/device-focused (195, 63.1%). Of studies that excluded by language, 20 (87.0%) were university-initiated. Eighty-eight trials were subsequently published, with 16 (18.2%) reporting race and/or ethnicity distributions. When comparing O/E ratios, White American participants were over-represented (O/E ratio: 1.2, P < .0001). Under-represented groups included Asian/Native Hawaiian (O/E ratio: 0.6, P = .0085), Black (0.6, P = .014), Native American (0.2, P = .072), and Hispanic patients (0.2, P < .0001). ConclusionOver the last 3 decades, 1 in 13 thyroid cancer–related clinical trials excluded patients based on language. In the fraction of published studies to report on racial and ethnic demographics, Asian/Native Hawaiian, Black, and Hispanic patients were under-represented. Improved reporting of demographics in published studies and elimination of exclusion criteria such as language that hinder enrollment of minority patients could improve equitable representation of patients in thyroid cancer clinical trials.

The cost of doing business: Drug costs in federally sponsored cancer clinical trials.

10 Background: Federally sponsored cancer clinical trials (FS-CCTs) address a broad set of clinical cancer research questions that are avoided by industry sponsors, including combining treatment modalities, examining whether approved drugs may work in other cancers, or examining de-escalation therapy. FS-CCTs routinely extend the lives of patients with cancer and inform treatment guidelines. However, FS-CCTs must often be conducted in partnership with industry sponsors since the cost of drugs is high and cannot be paid for by the government. This limits the independence of FS-CCTs. We aimed to examine the drug costs for trials with federal sponsorship. Methods: We included all US-based cancer treatment trials registered in ClinicalTrials.gov that examined pharmaceuticals and/or biological products and started from 2018-2022. Trials with any NIH or other federal sponsorship (as the sole, lead, or other sponsor) were included. Drug names and number of enrollments per arm and drug were extracted from ClinicalTrials.gov and study protocols. The Wholesale Acquisition Cost (WAC) was obtained from IBM Micromedex RED BOOK (2023) by matching the product name, dose strength and administration route. The product acquisition cost (“cost”) per trial was computed by summing the WAC for each drug and multiplying by the number of enrollments. Results: Overall, N=1020 trials were examined (phase I = 343, phase II = 611, phase III = 66). The mean (median) drug costs were $53.9 million (m) ($7.4m) overall, including $73.8m ($19.8m), $47.2m ($8.7m), and $44.7m ($5.8m) for trials solely sponsored, led by, or with secondary/tertiary participation by federal sponsors, respectively. Trial-level drug costs were $19.2m ($3.6m), $51.9m ($9.4m), and $244.9m ($38.8m) for phase I, II, and III trials, respectively. Drug costs were much greater for trials involving immune and/or targeted therapies ($60.1m [$11.4m]) than those with conventional chemotherapies ($30.8m [$1.5m]). In the subset of n=128 phase 2 or 3 comparative trials, drug costs were $97.7m ($21.8m) for experimental arms and $24.1m ($1.4m) for control arms. Conclusions: The costs for drugs in FS-CCTs were very high, especially for the experimental arms, highlighting the necessity for federally sponsored researchers to collaborate with industry partners to conduct trials. Drug costs for immune and/or targeted therapies were higher yet, suggesting that the cost burden to conduct trials for federal sponsors may continue to increase. These findings also suggest that systemwide costs for cancer drugs in clinical practice will continue to increase substantially. These results have implications for how FS-CCTs are designed and conducted, since the necessity of collaboration between federal and industry sponsors likely limits the independence of federal research. Future public policy efforts should focus on mechanisms for independent investigation of new pharmacologic agents.

A retrospective study of prognostic factors and prostate-specific antigen dynamics in Japanese patients with metastatic hormone-sensitive prostate cancer who received combined androgen blockade therapy with bicalutamide.

This retrospective observational study explored the therapeutic potential of combined androgen blockade (CAB) with bicalutamide (Bic-CAB) as an initial treatment for metastatic hormone-sensitive prostate cancer (mHSPC) in Japan. The electronic health records of 159 patients with mHSPC from three Japanese institutions who received initial treatment with Bic-CAB between 2007 and 2017 were analyzed. The time to prostate-specific antigen (PSA) progression, duration of Bic-CAB treatment, and overall survival (OS), with various definitions for PSA progression, were assessed. A multivariate Cox proportional hazards model was constructed using clinical parameters to predict time to the end of Bic-CAB treatment and OS. The median observation period was 46.4months, and the median age of patients at diagnosis was 71years. A total of 46.5% patients experienced PSA progression with a median survival duration of 29months (according to Prostate Cancer Clinical Trials Working Group 3 criteria), and 49.1% patients achieved a PSA nadir < 0.2ng/mL in a median time of 4.7months. When stratified by PSA nadir and PSA change, patients at low risk for disease progression with a small PSA change due to low initial PSA had a 5-year OS of 100% and a 10-year OS of 75%. The OS during the observation period was 72.9months. These findings highlight the potential effect of Bic-CAB in patients with mHSPC who were at low risk for disease progression. Initial treatment with Bic-CAB and adjusting treatment early based on PSA dynamics may be a reasonable treatment plan for these patients.

Participation in Non-small Cell Lung Cancer Clinical Trials in the United States by Race/Ethnicity

IntroductionDespite efforts by Cancer Centers and community organizations to increase diversity in clinical trials, significant racial/ethnic disparities remain. Given the high mortality rates in non-small cell lung cancer (NSCLC), it is important to increase diversity in NSCLC trials, ensuring all patients benefit from advances in new treatment modalities. Materials and MethodsWe evaluated the distribution of racial/ethnic minority enrollment in NSCLC clinical trials using data from ClinicalTrials.gov. We extracted trial characteristics, including start year, study phase, tumor stage, sample size, sponsor, geographic region, and masking. The number of participants by race/ethnicity was obtained from ClinicalTrials.gov or linked publications. Using annual NSCLC incidence data from SEER*Stat for each racial/ethnic group from 2010 to 2019, we applied a 2-sample test for equality of proportions with continuity correction to assess differences between incidence and trial participation. ResultsA total of 147 unique studies were included in the final analysis. Of the 28,540 participants, 79.6% were White, with 3% Black, 10.4% Asian or Pacific Islander and 3.4% Hispanic/Latino. Most participants were enrolled in phase III trials (63.8%), industry-sponsored (93.9%), and open-label (67.7%). Black patients were more commonly enrolled in academic sponsored trials and less commonly enrolled in masked (i.e., blinded) studies. When comparing trial participation to annual incidence data, we observed underrepresentation among Black participants (Difference: −7.9%) and Hispanic/Latino participants (Difference: −3.2%). ConclusionPersistent underrepresentation exists in NSCLC clinical trials among Black and Hispanic/Latino patients. We urge further investigation of these findings through well-designed clinical trials among diverse patient populations.

An updated comparative analysis of needs and role of patient navigation among early phase cancer clinical trial participants and non-participants at a single cancer center.

237 Background: Early phase clinical trials (EPCTs) assess the safety and toxicity of novel anticancer agents and represent opportunities for patients (pts) to try novel therapies when standard therapies have become ineffective. However, EPCT participants represent a vulnerable population with high financial toxicity and symptom burdens. EPCTs may add to these burdens by requiring frequent, long visits and additional procedures. Pt navigators perform needs assessments and provide guidance to pts as they move through the health care system. Navigation, which has a high level of acceptance among pts with cancer, can improve time from diagnosis to treatment, decrease pt anxiety, and improve participation of minoritized individuals in clinical trials. We hypothesized that EPCT participants would have higher navigation needs than those of non-EPCT participants with cancer. Methods: Utilizing a needs assessment conducted in person or by telephone, pts with cancer treated at Mount Sinai are assessed for 26 individual and systemic social drivers of health (SDoH) barriers by pt navigators at their trial screening visit. EPCT participants were defined as pts participating in a study in the Early Phase Trials Unit. Descriptive characteristics were assessed for all participants regarding demographic characteristics and SDoH barriers. Welch's T-test was used to compare differences in navigation encounters and SDoH barriers between the EPCT and non-EPCT pt groups. Results: From February 2023 to April 2024, 40 EPCT pts and 1290 non-EPCT pts completed the assessment. Median age was 60.5 and 63.1 years, respectively. Racial and ethnic self-identification included 17.5% vs. 19% Black pts and 10% vs. 17% Hispanic pts. EPCT pts had a mean 5.2 navigation encounters per pt compared to 3.05 in non-EPCT pts (p=0.002). Pts in the EPCT group were found to have an average of 2.8 SDoH barriers identified, in contrast to 2.0 in the non-EPCT group (p=0.002). The most common barriers identified in EPCT pts were institutional, knowledge, psychosocial and financial; in non-EPCT pts, transportation, institutional, knowledge and treatment adherence were most common. Interventions related to institutional barriers most frequently involved coordinating with the primary team and among departments. Interventions related to knowledge included providing education and teach back. Conclusions: EPCT pts had more SDoH barriers identified, higher acuity of barriers, and required more navigation encounters than non-EPCT pts. Participants in EPCTs are a vulnerable pt population for whom navigation is particularly warranted. EPCT pts Non-EPCT pts p value Navigation encounters, mean (SD) 5.20 (6.16) 3.05 (4.34) 0.002 SDoH barriers identified, mean (SD) 2.82 (1.83) 2.00 (1.66) 0.002

Development and validation of a risk prediction model for acute care use among patients with advanced cancer on clinical trials.

277 Background: Patients with advanced cancer on clinical trials are at high risk for unplanned Emergency Room visits (ER_visits) and hospital stays (HS). Identifying patients at highest risk could inform personalized intervention strategies. Methods: The data were from the SWOG Cancer Research Network. Medicare claims data were linked to data from advanced cancer clinical trials. The occurrence of any HS or ER visit within 1 year after enrollment was the primary endpoint. Patients must have had 6 months of continuous Medicare claims prior to registration to determine comorbid conditions prior to treatment, and 12 months of claims after registration (or until death) to detect outcomes. We examined 23 sociodemographic (age, sex, race, ethnicity, insurance status), geographic (rural or urban, area-level deprivation), clinical (disease severity, performance status), treatment (line of therapy, therapy type), and individual comorbidity factors to establish a predictive risk model. Model derivation was conducted in a 60% random sample and tested in the remaining 40%. Best subset selection with logistic regression was used with iterative application of 3-, 4-, and 5-fold cross validation repeated 10 times. Results: Among N=1397 total patients from 6 trials (lung, 3; prostate, 2; pancreas, 1), 33.9% were 75+ years, 20.3% were female, and 8.2% were Black. The overall proportion of patients with ≥1 HS/ER visit was 68.8%. In the training set (n=839), a best 5-variable risk was identified with adverse risk factors including cancer type (prostate vs other), performance status (PS; 0 vs. &gt;=1), coronary artery disease (CAD; yes vs. no), hypertension (yes vs. no), and liver disease (yes vs. no). As cancer type was a study-level variable, we derived a risk model using PS, CAD, hypertension, and liver disease and adjusted for cancer type. There were no differences in adverse risk between those in with and without prostate cancer (interaction p-value=.44), justifying combining across cancer types. In the training set, patients with ≥2 risk factors (high risk; n=303, 36.1%) vs. 0/1 risk factor (low risk; n=536, 63.9%) had nearly a 3-fold increased odds of experiencing HS/ER visit (82.2% vs. 59.1%, OR=2.85, 95% CI, 2.01-4.03, p&lt;.001). Results were successfully validated in the test set (OR=1.93, p=.002). In all patients, those in the highest risk quartile (3/4 factors) vs the lowest risk (0 factors) had nearly a fourfold increased odds of HS/ER visits (OR=3.92, 95% CI, 2.25-6.83, p&lt;.001). Conclusions: Rates of HS_ER visits were high within the first year after enrolling on a trial for advanced cancer. We derived and validated a risk model that delineated strong differences in risk. With expansion of eligibility to include patients with more comorbid conditions, personalized interventions aimed at preventing acute care use could decrease the cost and improve the quality of cancer care.

S303 Assessing Enrollment Disparities by Demographics in Colorectal Cancer Clinical Trials Across the United States

S303 Assessing Enrollment Disparities by Demographics in Colorectal Cancer Clinical Trials Across the United States

Health care contact days in older adults enrolled in SWOG cancer clinical trials.

64 Background: Health care contact days—days with health care contact outside the home—are a measure of how much of a patient’s life is consumed by health care. This number of contact days are especially relevant for older adults with advanced cancer facing limited survival. One concern is that patients with different sociodemographic and clinical backgrounds may be at particular risk of increased contact days. Thus, there is a critical need to understand factors associated with contact days. Methods: We linked data from 6 SWOG trials in advanced cancer to Medicare claims data. These trials encompassed a variety of primary cancer types [prostate (S9916, S0421), lung (S0003, S0124, S0819), and pancreas (S0205)]. Health care contact days (days with ambulatory, emergency department, inpatient, or facility-based care) in the first 12 months were calculated using Medicare database files. A day with &gt;1 source of contact counted as 1. We examined sociodemographic (age, race, ethnicity, sex, insurance status, rurality, area deprivation index) and clinical (prognostic risk, cancer type, performance status) predictors of contact days, using negative binomial regression, with a log link and clustering by study ID, including an offset variable for duration of observation. We examined predictors in univariate and multivariable analysis. We report relative risk (RRs) estimates and 95% CI. Results: We included 1,429 patients (median age, 71 years, 7.6% Black, 2.7% Hispanic, 21.4% female, and 23.5% rural residence). Of these, 741 (51.9%) patients died in the first year. The median number of contact days was 48, out of a median of 350 days of observation. At a trial level, median percentage of contact days ranged from 14% (prostate) to 27% (lung). The most common sources of contact days were ambulatory clinician visits (median=17), tests (median=12), and treatments (median=11). In multivariable regression, factors associated with increased contact days included increasing age (per year, RR=1.02 [1.01-1.02], p&lt;.001), insurance status (Medicare alone or with Private or Medicaid insurance, vs Military/VA, none, or other insurance, RR=2.47 [2.16-2.83], p&lt;.001), higher prognostic risk score (RR=1.14 [1.04-1.25], p=.004), and type of cancer (pancreas, RR=1.69 [1.51-1.89] and lung, RR=1.69 [1.54-1.85] vs prostate, p&lt;.001 for both). Conclusions: This novel linkage of trial and claims data to evaluate contact days and associated factors found that older trial participants spent up to one in four days with health care contact. Ambulatory appointments were the most common source of contact days. Encouragingly, rural residence and neighborhood deprivation were not associated with contact days, increasing confidence that participants from diverse geographic areas may receive equitable care in trials. These data highlight the frequency of contact days for trial participants, while identifying factors to consider when benchmarking contact days.

Associations of symptom burden with patient-reported outcomes (PROs) and clinical outcomes among early phase cancer clinical trial (EP-CT) participants.

244 Background: Individuals with cancer often endure a substantial physical and psychological symptom burden. However, little is known about the baseline symptom burden of patients with cancer participating in EP-CTs or the associations of this symptom burden with other PROs and clinical outcomes. Methods: We prospectively enrolled adults with cancer participating in EP-CTs at Massachusetts General Hospital from 4/2021-1/2023. Participants completed baseline surveys prior to EP-CT initiation that assessed symptoms (Edmonton Symptom Assessment System [ESAS]), quality of life (QOL; Functional Assessment of Cancer Therapy-General), hope (Herth Hope Index), depression/anxiety symptoms (Patient Health Questionnaire-4 [PHQ-4]), and financial wellbeing (COST tool, higher scores indicate greater financial wellbeing). We used regression models to explore associations of baseline symptom burden with other PROs (QOL, hope, depression/anxiety, financial wellbeing) and clinical outcomes (time on trial, hospitalizations, overall survival). Results: Among 205 participants (median age=63.3 [range: 31.8-88.6], 57.1% female), the most common cancer types were gastrointestinal (34.6%), breast (20.0%), and head and neck (10.2%). Based on the ESAS, approximately half of participants reported moderate/severe fatigue (50.2%) and poor wellbeing (49.5%). Under half reported moderate/severe drowsiness (35.7%), pain (25.9%), lack of appetite (25.4%), shortness of breath (20.0%), anxiety (18.0%), depression (15.4%), and nausea (9.2%). Higher baseline ESAS total, physical, and psychological scores were associated with worse QOL, lower hope, greater PHQ-4 depression/anxiety symptoms, and worse financial wellbeing (see Table). Higher baseline ESAS scores were associated with decreased time on trial and worse overall survival (see Table). Conclusions: In this study of EP-CT participants, we found associations of baseline symptom burden with other important PROs and clinical outcomes. Specifically, higher baseline symptom burden was associated with decreased QOL, lower hope, increased depression/anxiety symptoms, and diminished financial wellbeing as well as greater risk for shorter time on trial and worse survival. Interventions seeking to enhance care delivery and outcomes for EP-CT participants should strive to address the symptom burden of this population. Outcomes ESAS Total ESAS Physical ESAS Psychological PROs Beta P Beta P Beta P QOL -0.55 &lt;0.001 -0.68 &lt;0.001 -1.93 &lt;0.001 Hope -0.10 &lt;0.001 -0.09 &lt;0.001 -0.53 &lt;0.001 PHQ-4 Depression/Anxiety 0.06 &lt;0.001 0.06 &lt;0.001 0.39 &lt;0.001 Financial Wellbeing -0.13 0.003 -0.16 0.009 -0.36 0.032 Clinical Outcomes HR P HR P HR P Hospitalizations 1.01 0.066 1.02 0.059 1.03 0.290 Time on Trial 1.01 0.069 1.01 0.208 1.04 0.046 Overall Survival 1.02 &lt;0.001 1.03 &lt;0.001 1.04 0.088

Cost of care associated with utilization of telehealth in clinical trials

ObjectiveDue to COVID-19 pandemic restrictions, telehealth was incorporated into standard oncologic care and clinical trial operations. We sought to analyze whether telehealth changed cost of care compared to traditional clinical trial operations. MethodsWe conducted a retrospective cohort study of gynecologic oncology patients enrolled in therapeutic clinical trials at a National Cancer Institute designated center, comparing the cost of cancer care on trial pre-TELEhealth (9/30/2019 to 3/15/2020) versus during TELEhealth (3/16/2020 to 8/20/2020). Inclusion required trial participation during both study periods, ≥1 telehealth visit, and identifiable billing records. The analysis was from a healthcare sector perspective. Cost per patient per month on trial was calculated for scheduled (per protocol) and unscheduled (non-protocol) encounters using 2020 national Medicare reimbursement rates, not institution-specific prices. Pairwise t-tests between pre-TELE and TELE periods were performed. ResultsTwenty-eight patients were included in the study. The majority of patients (93 %) had ovarian cancer. One patient (4 %) had uterine and 1 (4 %) had concurrent ovarian/uterine cancer. Most patients had advanced-stage disease at diagnosis (93 %). Mean cost per patient per month was similar in pre-TELE and TELE periods ($3797 vs. $4720, p = 0.064). There were no cost differences among scheduled or unscheduled encounters, office or ED visits, admissions, outpatient procedures, nor those billed to study sponsors or patient’s insurer. ConclusionsIncorporating telehealth in gynecologic cancer clinical trials during the COVID-19 pandemic did not increase cost of care and may be a mechanism for decentralizing clinical trials, reducing barriers to trial participation, and improving the value of cancer care.