Citations

e23171 Background: A011502 is a phase 3 trial that randomized high-risk nonmetastatic breast cancer (BC) patients (pts) to aspirin 300 mg daily vs. placebo. Obesity and Black race have been shown to be associated with worse clinical outcomes. We studied the association of stress, depression, sleep and pain with each other, and with BMI and race. Methods: At baseline, 2735, 2610, 2720, and 2422 pts completed Perceived Stress Scale (PSS), Center for Epidemiologic Studies Depression Scale Revised (CESD-R), Brief Pain Inventory (BPI), and Pittsburgh Sleep Quality Index (PSQI) respectively. Stress was categorized with PSS scores: low (0-13), moderate (14-26) or high (27-40). Depression was categorized with CESD-R scores: no depression (0-15) or depression (≥16). Pain was categorized with BPI scores: none/mild (0-3) or moderate/severe (≥4). Sleep quality was categorized with PSQI scores: good (0-5) or poor ( > 5). Associations of measures by race and BMI were analyzed using chi-square test. Results: There was a statistically significant association among stress, depression, pain, and sleep quality (p < 0.01 for all). Compared to pts with BMI < 25, overweight and obese women reported higher stress (2.9%, 2.3% vs. 1.7%, p = 0.04), depression (13.4%, 18% vs. 9.6%, p < 0.01), moderate/severe pain (16.5%, 20.3% vs. 12%, p < 0.01), and poor sleep (64.9%, 71.5% vs. 60.4%, p < 0.01). Black women reported more moderate/severe pain compared to White women or other races (32.9% vs. 14.2% vs. 27.8%, p < 0.01). There was no association of other symptoms with race (Table 1). Conclusions: Obesity was associated with higher stress, depression, poor sleep and pain among BC pts from A011502. Black women reported higher pain compared to other races. Future studies are warranted that determine causal associations, how symptoms may relate to outcome disparities, and develop approaches to address them. U10CA180821, U10CA180882, UG1CA233196; https://acknowledgments.alliancefound.org . Clinical trial information: NCT02927249 . [Table: see text]

11167 Background: Successful outcomes of surgical treatment of cancer requires expertise and high-quality supportive services for surgical care. Previous studies have shown that case volume and availability of other in-house supportive services affect surgical outcomes. Latest studies have shown that this gap has now significantly reduced. Issues related to access, availability of funding for latest technologies and continuous medical education still exist and likely still impact the surgical outcomes. The objective of the study is to understand the impact of surgical center related factors on survival outcomes for cancer patients based on race and other demographic features. Methods: We conducted a retrospective analysis of patients diagnosed with Stage I-III Non-small cell lung cancer (NSCLC) between 2004 to 2020 using the National Cancer Database (NCDB). Patients were divided into 4 cohorts of NCDB assigned facility type (Community Cancer Program, Comprehensive Community Cancer Program, Academic/Research Program, Integrated Network Cancer Program). Racial and other demographic data was analyzed for each of the facility types. Differences in categorical variables were evaluated using a Chi-square test. Results: 298,393 adenocarcinoma and 129,144 squamous cell carcinoma patients underwent surgery for NSCLC between 2004-2020. 326,798 patients with clinical stages I-III were selected for the analysis. Most surgeries were performed at the academic/research programs and comprehensive community programs. Utilization of each facility type was uniform across all races. The 30-day mortality rate was lowest for the academic/research programs (Community Cancer Program 3.1%, Comprehensive Community Cancer Program 2.6%, Academic/Research Program 1.8%, Integrated Network Cancer Program 2.3%; p=0.000). 30-day mortality rate was higher for American Indian, Aleutian, or Eskimo racial subgroups amongst all age-groups at all the surgical facility types especially for Stage IIIB NSCLC (White: 6%, Black: 3.4%, American Indian, Aleutian, or Eskimo: 14.3%, p=0.006). For each race, the 30-day mortality rate was better at the academic/research programs. Females had lower 30-day mortality for all racial subgroups. Having private insurance was associated with the lowest 30-day mortality rate. This was noted for all races across all the facility types. Lower income status was associated with higher mortality rates across all facility types. This difference was statistically significant for white patients. Majority of patients had less than 10 days of length of stay at all the surgical facility types. Conclusions: Outcomes of NSCLC surgery are significantly better at academic/research programs where a higher number of procedures are performed and access to latest surgical technologies is available. Short-term mortality rates are higher for American Indian, Aleutian, or Eskimo racial subgroup.

11176 Background: Progression-free survival (PFS) is frequently measured in oncology clinical trials. In analyses outside of the trial setting, various strategies have been utilized to assess real-world PFS (rwPFS), including manual abstraction of clinical records, natural language processing (NLP) of oncology notes and radiology reports, and longitudinal analyses of radiologic images. Here we develop and validate a new semi-automated workflow that combines NLP of clinical notes with structured electronic health record data to facilitate the evaluation of rwPFS in patients with metastatic breast cancer (mBC). Methods: This study analyzes de-identified EHR data using nference nSights. The data is extracted following privacy-preserving protocols and is HIPAA compliant. The overall cohort included 316 patients with HR-positive, HER2-negative mBC who initiated Palbociclib and Letrozole combination therapy between January 1, 2015 and December 31, 2021. We developed and implemented an ensemble of deep-learning NLP frameworks to capture progression events from unstructured clinical notes and radiology reports. A change in the line of therapy, as determined by structured drug order/administration records, was also considered a progression event. We used manually curated “ground-truth” datasets to evaluate the performance of the progression-event capture workflow at the levels of both sentences (N = 1000) and patients (N = 100) by calculating sensitivity, specificity, precision, accuracy, and F1 scores. Progression events and censoring events (death, loss to follow-up, end of study period) were considered to compute rwPFS. Results: At the sentence level, progression events were captured from clinical notes and radiology reports with a sensitivity of 99.8%, specificity of 96.7%, and accuracy of 98.2% (Table). At the patient level, initial progression was correctly captured within a window of +/-30 days with a sensitivity of 92.5%, specificity of 83.0%, and accuracy of 88.0% (Table). In a sample of 100 patients, the median rwPFS was determined to be 25 months (95% CI; 15-35 months) by manual curation and 22 months (95% CI; 15-35 months) by the semi-automated workflow. In the overall cohort, median rwPFS was 20 months (95% CI; 18-25 months). Conclusions: An ensemble of NLP algorithms extracted progression events from clinical notes and radiology reports with high accuracy. A semi-automated workflow enabled rapid and accurate determination of rwPFS in mBC patients receiving a combination chemotherapy regimen. Further evaluation of this workflow to estimate rwPFS in other cancers and therapeutic settings is warranted. [Table: see text]

11135 Background: Cancer screening programs can improve outcomes and may reduce treatment cost and utilization by shifting cancers to earlier, more curable stages at diagnosis (Dx). Few studies have evaluated the impact of screening on outcomes prior to diagnosis. Such information is needed to better understand the potential impact of newer blood-based multicancer early detection technologies. Methods: We conducted a retrospective cohort study using SEER cancer registry data linked with Medicare claims. Patients with a breast cancer (BC) or colorectal cancer (CRC) Dx between 2010-2019 were included if they were 65-74 years old at Dx, continuously enrolled in Medicare Parts A&B, had a Charlson Comorbidity Index of ≤2, and no cancer for ≥12 months prior to Dx. Those enrolled in an HMO or with high genetic risk for BC (in BC cohort) were excluded. Patients were assigned to screening groups prior to Dx; screening was defined as ≥1 screening procedure in the 6 months prior to Dx using CPT/HCPCS codes. Screening included FIT/FOBT, sigmoidoscopy, colonoscopy, CT colonography, mt-sDNA (CRC), and mammography (BC). Screened and not screened groups were compared for statistical significance using chi-squared for categorical variables, Wilcoxon rank-sum test for continuous variables. Results: Screening procedures were more prevalent in the BC cohort (68%) than the CRC cohort (44%) (table). Both screened subgroups (vs non-screened subgroups) had significantly lower proportions of patients diagnosed at stage 4 (2% vs 10% BC, 16% vs 27% CRC) and shorter times from first screening or imaging procedure to confirmed diagnosis (BC: 33 vs 227 days, CRC: 14 vs 29 days). Screened patients in both cancer cohorts had a similar number of average procedures prior to treatment initiation as non-screened (BC: 4.8 vs 4.2, CRC: 3.3 vs 3.3 respectively, including screening procedures). Conclusions: Individuals diagnosed with BC and CRC through screening exhibit earlier stage diagnoses and shorter intervals to diagnosis. Novel screening technologies such as MCED tests can potentially improve peri-diagnostic outcomes in cancers lacking existing or widely adopted screening methods. [Table: see text]

11128 Background: To improve documentation quality in Medical Onc outpatient clinics, a standardized template was created. In this template we embedded: 1. An Epic SmartForm to collect structured data (SD) about patient, disease, and response status at each encounter. Minimal Common Oncology Data Elements (mCODE) compatible SD elements were used to enhance interoperability. 2. Several clinically impactful quality metrics (QM) selected based on the Quality Onc Practice Initiative (QOPI) guidelines. In this analysis, we aim to assess how template use impacted documentation quality. Methods: 113,376 outpatient encounters occurred between 01/2018 – 12/2022 (41 providers: 35 physicians, 6 APPs). The template go live was 3/19/2019. 2,520 randomly selected encounters were manually reviewed. Distinct documentation of 8 items served as QMs (Table). Of note, using the template was voluntary and data entry in the embedded form is not mandated. Documentation of each QM was compared between notes authored with/without template. For each note, a completeness score was calculated based on total number of QMs present/note. Categorical comparisons were made using chi-squared or Fisher’s exact tests. Numerical/continuous values were summarized using means and standard deviations. A template “user” was defined as a provider using the template in >10% of encounters after go live. This QI project was exempted by IRB. Results: 154/2520 encounters were excluded after manual review (visits not for solid tumor malignancy). The template was used in 38.7% (917/2366) of the reviewed notes. Cancer diagnosis was documented in >99.8% of notes regardless of template use. Template use was associated with increased documentation of 7 QMs (Table). Documentation overall completeness improved from 62% to 90% with a very large effect size (Table). Template use positively correlated with female gender and fewer years since last training (p<0.001). In the subgroup of notes written by “users” (21 physicians, 4 APPs), individual QM and overall completeness scores improved with template use (p<0.001). Conclusions: Template use profoundly improved QM documentation (statistically significant and clinically meaningful) by Onc clinic providers. This strategy enhances mCODE compatible structured data collection and semantic interoperability between systems, strengthening the available real-world data (RWD) in EHR. [Table: see text]

11079 Background: Phase 3 randomized clinical trials (RCTs) inform the standard of care in cancer treatment yet have a mixed track record of success. In this study, we sought to 1) determine the overall success rate of phase 3 RCTs; 2) assess whether authorship patterns differ between successful (positive) and unsuccessful (negative) trials; and 3) explore if individual authors have distinct track records of success. Methods: The HemOnc knowledgebase (KB) was queried for initial publications of phase 3 RCTs of systemic anticancer therapy; those without primary outcome described were excluded. RCTs were labeled positive if the primary endpoint was met per HemOnc standard criteria (P value ≤ 0.05 or hazard ratio upper bound ≤ 1 for any experimental arm[s]) and negative if they did not meet these criteria or if the experimental arm was statistically inferior. Trial metadata and author information were extracted from the HemOnc KB. Author positive publication rate (PPR) was defined as % of publications reporting a positive result divided by total number of eligible publications. Prolific authors were defined as those with 6+ eligible publications. Author count for manuscripts reporting positive vs negative results was evaluated with the Mann-Whitney U test; other statistics were descriptive. Results: 3328 studies met criteria as of February 5, 2024; these were associated with 3305 initial publications between 1960-2023, involving 25,412 unique authors. 1474 (44.3%) of the studies were positive. Publications reporting positive trial results had, on average, 3 more authors, median (interquartile range) of 18 (12-23) vs 15 (11-20), p<0.0001. The mean (±SD) PPR for n=1967 prolific authors was 47.7% (±22.3%). The PPR was not related to individual author output; mean PPR for non-prolific authors was 48.0% (SD not reported). Differences in PPR were apparent by the disease under study and the years of publication (Table). Among the 46 prolific authors who had a PPR 2+ SD above the mean, 26 (55%) were from China followed by Italy with 3 (6%). Conclusions: Despite known positive publication bias, the success rate of published phase 3 RCTs remains <50%. Publications reporting positive results had significantly more authors; this finding requires further study including adjustment for trial sample size. Significant variation in PPR amongst fields could be due to watershed therapeutic advances, differential selection of primary endpoints, and/or selective reporting of results. Finally, a signal for geographic association of outlier PPRs suggests the need for further investigation. [Table: see text]

11059 Background: Some opioid stewardship policies could negatively affect patients with cancer pain. However, patients with cancer are also at risk for opioid related harms, especially with persistent use. We assessed opioid prescribing trends in the context of cancer treatment and patient reported pain in a large health system in Connecticut. Methods: We conducted a retrospective cohort study of opioid-naïve adult patients with solid tumor malignancies diagnosed from 2016 through 2020 within the Yale New Haven Health System. We identified new (≥1 opioid prescription in 0-6 months following diagnosis) and additional (0-6 and 6-9 months) opioid prescriptions. The analysis evaluated all eligible patients as well as two clinical cohorts: patients treated surgically and patients with metastatic cancer. For patients with metastatic cancer and a documented pain score in the electronic health record flowsheet data, we further stratified by any (any score≥1) or no (all scores=0) pain in the 6 months since diagnosis and prior to first opioid, if given. For these patients, we noted therapeutic class of the first opioid. We used a logistic model adjusted for patient demographics to calculate predicted probability of opioid prescription and change over time. Results: A total of 10,868 patients met study criteria. Overall, we observed a decline in new opioid prescribing from 69.0% to 62.7% (p<.001) (Table). Additional opioid use also declined from 23.4% to 20.2% (p=.02). In the surgery cohort, new opioid prescribing fell from 95.7% to 88.2% (p<.001), while additional opioid use was stable over time (approximately 12%). For patients with metastatic cancer with any documented pain, new opioid prescribing was stable over time (approximately 56%). For those with documented pain scores=0, new opioid prescribing declined from 59.7% to 34.2% (p<.001). In these patients, the class listed on the first opioid prescription was analgesia in 86.6% and cough in 13.4%. Conclusions: Overall, and in patients treated with oncological surgeries, our study in a single large US health system suggests a modest, gradual decline in opioid prescribing for patients with cancer over time. On the other hand, among patients with metastatic cancer, opioid prescribing remained stable for those with documented pain and declined steeply for those without documented pain. [Table: see text]

11030 Background: Drug regulators operate on their own timelines to assess the safety and efficacy of new drugs and/or extensions to existing indications, such that there are delays between regulators. During such a gap, patients in the “early” domain have access to the approved drug, while those in the “late” domain do not, outside of compassionate use. Our study aimed to quantify the “opportunity lost” for new therapies approved by FDA and EMA, assuming patients in the late domain receive standard-of-care (SOC) therapy – which is presumably inferior to the new drug – during the gap. Methods: Anticancer drugs approved by both FDA and EMA were identified through the HemOnc knowledgebase. Inclusion criteria included: 1) drugs approved in both domains based on the same randomized clinical trial (RCTs) for the same indication; 2) a primary time-to-event endpoint; and 3) a quantitated median time-to-event for the primary endpoint. For each included trial, the approval gap between FDA and EMA in days and the ratio of approval gap to median control arm time-to-event duration was calculated. A ratio ≥2 implies that, on average, no late domain patients starting treatment in the first half of the gap would be expected to have access to the new drug prior to an event. Results: Of 60 eligible RCTs, 59 had calculable median event durations. 25 (42%) had a primary overall survival endpoint; the most common surrogate endpoint was progression-free survival (PFS; 29/59; 49%). The median (interquartile range [IQR]) approval gap was 186 (124-271) days, with FDA being the first approver in 56/59 (95%) cases. The median (IQR) ratio of approval gap to median control arm event duration was 0.63 (0.35-1.11). Drugs with ratio ≥2 (Table) were targeted or immunotherapies; 7/8 (88%) were approved with PFS endpoint; 5/8 (62.5%) were approved for second line or later. Conclusions: Our study shows that FDA approves most drugs prior to EMA and a nontrivial number of patients may experience progression or death events while awaiting access to anticancer therapies already approved in another domain. The analysis does not take into consideration scenarios in which the new therapy is inferior to SOC or delays in patient access (due to slow uptake; regulatory barriers [in Europe/UK]; or patient affordability [in US]). Further regulatory collaboration (e.g., Project Orbis) between FDA and EMA could help to reduce and potentially ameliorate this differential in access to new cancer drugs in the future. [Table: see text]

11023 Background: Randomized clinical trials (RCTs) in cancer typically compare experimental to control arm regimens. The choice of an appropriate control (ctrl) arm can have a major impact on the expected success of an RCT. The frequency with which cancer RCTs use control arms based on established dosing and scheduling protocols has not been described. Methods: The HemOnc knowledgebase (KB) was used to identify systemic anti-cancer therapy (SACT) regimen variants, defined as regimens with identical components that differ in dosing, scheduling, and/or route. Non-cancer, nonrandomized, and non-SACT studies were excluded. Study publication year was used to define standard variants as those evaluated in the experimental arm of a positive phase 3 RCT >1 year prior to publication as a control arm, regardless of cancer type or context of treatment. Study-variant dyads were evaluated to determine whether the variant was standard. Success rates of RCTs with standard vs non-standard control arms were evaluated with Fisher’s exact test. Results: 5221 studies were associated with ≥1 named variant in the HemOnc KB, as of 2024-02-06. After exclusions, there were 3511 study-variant dyads (2386 studies; 1714 variants). The 9 most common regimens are shown in the Table. The median (IQR) number of variants per regimen was 2 (1-3); carboplatin & paclitaxel (CP) had the most variants (n=33). Across all control arm study-variant dyads, 2228/3492 (64%) utilized non-standard variants. For example, 60/97 studies (62%) of docetaxel as control used the 75 mg/m2 q3wk variant after it was established in 2000, whereas n=27 others used 19 non-standard variants. Trials that used a standard control arm had a numerically higher success rate, 45% vs 42% (OR 1.10, 95% CI 0.92-1.32). Conclusions: Non-standard regimen variants are frequently used in cancer RCTs. Reasons for this could include toxicity, patient convenience, or emerging data from smaller studies that establish comparable efficacy or improved toxicity to standard variants. However, the a priori efficacy of non-standard control arms is less rigorously established, and trials with standard control arms might be more successful. Future directions include quantifying the granular differences between standard and non-standard variants and investigating whether certain types of non-standard variation (e.g. fewer cycles, lower doses) associate with trial success rates. [Table: see text]

11016 Background: A011502 is a phase 3 randomized double-blind clinical trial that enrolled high-risk nonmetastatic breast cancer (BC) patients (pts) and randomized pts to aspirin 300 mg daily vs. placebo. There was no significant difference in invasive disease-free survival (iDFS) between the two arms. A secondary objective was to determine the association of inflammation-affiliated factors (stress, depression, poor sleep quality and pain) with iDFS and overall survival (OS). We hypothesized that these baseline factors are associated with worse clinical outcomes. Methods: At baseline, 2735, 2720, 2422 and 2610 pts completed Perceived Stress Scale (PSS), Brief Pain Inventory (BPI), Pittsburgh Sleep Quality Index (PSQI) and Center for Epidemiologic Studies Depression Scale Revised (CESD-R) respectively. Stress was categorized with PSS scores: low (0-13), moderate (14-26) or high stress (27-40). Pain was categorized with BPI scores: none/mild (0-3) or moderate/severe (≥4). Sleep quality was categorized with PSQI scores: good (0-5) or poor ( > 5).Depression was categorized with CESD-R scores: no depression (0-15) or depression (≥16). Associations between the measures of interest and outcomes were performed with multivariable Cox models controlling for age, body mass index, time since diagnosis, race, ethnicity, hormone receptor status and treatment arm. Results: Median follow up was 35 months. The associations from multivariable Cox model are shown in Table 1. Pts who reported high PSS had significantly worse iDFS and (non-significant) worse OS. Moderate/severe average (avg) pain was significantly associated with worse iDFS and OS. Poor sleep quality and depression were associated with worse iDFS and OS but not statistically significant. Conclusions: Pts reporting higher stress and pain at baseline had worse outcomes. We acknowledge that both pain and stress may be related to other non-cancer issues (chronic comorbidities). Our study highlights the need for clinical trials to consider including questionnaires to assess pt-reported outcomes. Future studies are warranted to determine if measures to decrease pain and stress would improve BC outcomes. U10CA180821, U10CA180882, UG1CA233196; https://acknowledgments.alliancefound.org . NCT02927249: Clinical trial information: NCT02927249 . [Table: see text]