Rivera, Donna R.

PURPOSE Despite evidence of diagnostic accuracy but unclear long-term clinical benefit, national utilization patterns of prostate-specific membrane antigen positron emission tomography (PSMA-PET) are undefined. METHODS We conducted a serial cross-sectional study to evaluate the use of PET imaging among commercial insurance beneficiaries with prostate cancer using administrative claims from deidentified Blue Cross Blue Shield Axis database. Eligible patients included prevalent and incident prostate cancer cases. We calculated the proportions undergoing PET imaging in semiannual periods from January 1, 2016, through December 31, 2024. We examined the association between regional-level contextual sociodemographic and health care characteristics, and regional use of PSMA-PET imaging in 2024. RESULTS A total of 514,750 male beneficiaries age 40-89 years with prostate cancer were identified between 2016 and 2024. The proportion of individuals with prostate cancer undergoing PET imaging increased from 4.5 [95% CI, 4.1 to 4.9] per 1,000 in the first half of 2016 to 77.6 (95% CI, 76.2 to 79.1) per 1,000 in the second half of 2024, P < .001. Increases in PET were driven by uptake of PSMA-PET following approval in 2021, which increased from 0.8 (95% CI, 0.6 to 0.9) per 1,000 in the second half of 2021 to 77.0 (95% CI, 75.5 to 78.5) per 1,000 in the second half of 2024, P < .001. PSMA-PET use in 2024 was higher in regions with greater education (99.3 v 114.6 per 1,000 in lowest [Q1] v highest [Q4] educated) and income (95.4 v 112.3 per 1,000 in Q1 v Q4 income) measures, P < .001. CONCLUSION PSMA-PET was rapidly incorporated into clinical practice among commercial insurance beneficiaries with prostate cancer with higher adoption in geographic regions with higher income and education.

Abstract Background Opioid stewardship policies could adversely affect pain management for patients with cancer. Yet patients with cancer are also at risk for opioid‐related harms. This study sought to determine trends in opioid prescribing by clinical stratum and pain for patients with cancer from 2016 to 2020. Methods A retrospective study was conducted of opioid‐naive adults with newly diagnosed cancer from 2016 to 2020 ( N = 10,232) in a large Connecticut health system. Logistic regression was used to calculate changes in the predicted probability of opioid prescribing from 2016 to 2020. Two subpopulations were examined: patients treated surgically ( n = 4405) and patients with metastatic cancer ( n = 2158). Flowsheet pain scores for patients with metastatic cancer were used to stratify by no pain (all scores, 0) versus any pain. The main outcomes were new (≥1 prescription in the 0–6 months after diagnosis) and additional (0–6 and 7–9 months) opioid prescriptions. Results A decline was observed in the predicted probability of new (71.1% to 64.6%; p < .001) and additional prescribing (27.2% to 24.2%; p = .07 [not significant]) declined. Among surgical patients, the predicted probability of new opioid prescribing fell (96.0% to 88.6%; p < .001), whereas additional prescribing was stable (13%). For patients with metastatic cancer with pain, new opioid prescribing was stable (56%). For those reporting no pain, the predicted probability of new opioid prescribing declined from 61.6% to 36.1% ( p < .001). Conclusions In the context of widespread policy changes, this study showed a modest decline in new and additional opioid prescribing for patients with cancer. In metastatic cancer, prescribing remained stable for patients reporting pain and declined steeply for those reporting no pain.

AbstractBackgroundThe use of electronic health record (EHR) data for research is limited by a lack of structure and a standard data model. The objective of the ICAREdata (Integrating Clinical Trials and Real‐World Endpoints Data) project was to structure key research data elements in EHRs using a minimal Common Oncology Data Elements (mCODE) data model to extract and transmit data.MethodsThe ICAREdata project captured two EHR data elements essential to clinical trials: cancer disease status and treatment plan change. The project was implemented in clinical sites participating in Alliance for Clinical Trials in Oncology trials. Data were extracted from EHRs and sent by secure Fast Healthcare Interoperability Resource messaging (a standard for exchanging EHRs) to a database. Selected elements were compared with corresponding data from the trial's electronic data capture (EDC) system, Medidata Rave.ResultsBy December 2023, data were extracted and transmitted from 10 sites for 35 patients, involving 367 clinical encounters across 15 clinical trials. Data through March 2023 demonstrated that concordance for the elements treatment plan change and cancer disease status was 79% and 34%, respectively. When disease evaluation was reported by both EHR and EDC (n = 15), there was 87% agreement on cancer disease status.ConclusionsDocumentation, extraction, and aggregation of structured data elements in EHRs using mCODE and ICAREdata methods is feasible in multi‐institutional cancer clinical trials. EDC as a reference data set allowed assessment of the completeness of EHR data capture. Future initiatives will focus on elements with shared definitions in clinical and research environments and efficient workflows.Plain Language Summary Clinical trials use electronic case report forms to report data, and data must be manually entered on these forms, which is costly and time consuming. ICAREdata methods use structured, organized data from clinical trials that can be more easily shared instead having to enter free text into electronic health records.

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]

Background: Limited information is available for patients with breast cancer (BC) and coronavirus disease 2019 (COVID-19), especially among underrepresented racial/ethnic populations. Methods: This is a COVID-19 and Cancer Consortium (CCC19) registry-based retrospective cohort study of females with active or history of BC and laboratory-confirmed severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection diagnosed between March 2020 and June 2021 in the US. Primary outcome was COVID-19 severity measured on a five-level ordinal scale, including none of the following complications, hospitalization, intensive care unit admission, mechanical ventilation, and all-cause mortality. Multivariable ordinal logistic regression model identified characteristics associated with COVID-19 severity. Results: 1383 female patient records with BC and COVID-19 were included in the analysis, the median age was 61 years, and median follow-up was 90 days. Multivariable analysis revealed higher odds of COVID-19 severity for older age (aOR per decade, 1.48 [95% CI, 1.32–1.67]); Black patients (aOR 1.74; 95 CI 1.24–2.45), Asian Americans and Pacific Islander patients (aOR 3.40; 95 CI 1.70–6.79) and Other (aOR 2.97; 95 CI 1.71–5.17) racial/ethnic groups; worse ECOG performance status (ECOG PS ≥2: aOR, 7.78 [95% CI, 4.83–12.5]); pre-existing cardiovascular (aOR, 2.26 [95% CI, 1.63–3.15])/pulmonary comorbidities (aOR, 1.65 [95% CI, 1.20–2.29]); diabetes mellitus (aOR, 2.25 [95% CI, 1.66–3.04]); and active and progressing cancer (aOR, 12.5 [95% CI, 6.89–22.6]). Hispanic ethnicity, timing, and type of anti-cancer therapy modalities were not significantly associated with worse COVID-19 outcomes. The total all-cause mortality and hospitalization rate for the entire cohort was 9% and 37%, respectively however, it varied according to the BC disease status. Conclusions: Using one of the largest registries on cancer and COVID-19, we identified patient and BC-related factors associated with worse COVID-19 outcomes. After adjusting for baseline characteristics, underrepresented racial/ethnic patients experienced worse outcomes compared to non-Hispanic White patients. Funding: This study was partly supported by National Cancer Institute grant number P30 CA068485 to Tianyi Sun, Sanjay Mishra, Benjamin French, Jeremy L Warner; P30-CA046592 to Christopher R Friese; P30 CA023100 for Rana R McKay; P30-CA054174 for Pankil K Shah and Dimpy P Shah; KL2 TR002646 for Pankil Shah and the American Cancer Society and Hope Foundation for Cancer Research (MRSG-16-152-01-CCE) and P30-CA054174 for Dimpy P Shah. REDCap is developed and supported by Vanderbilt Institute for Clinical and Translational Research grant support (UL1 TR000445 from NCATS/NIH). The funding sources had no role in the writing of the manuscript or the decision to submit it for publication. Clinical trial number: CCC19 registry is registered on ClinicalTrials.gov, NCT04354701 .

Abstract Background The impact of ongoing efforts to decrease opioid use on patients with cancer remains undefined. Our objective was to determine trends in new and additional opioid use in patients with and without cancer. Methods This retrospective cohort study used data from Surveillance, Epidemiology, and End Results program–Medicare for opioid-naive patients with solid tumor malignancies diagnosed from 2012 through 2017 and a random sample of patients without cancer. We identified 238 470 eligible patients with cancer and further focused on 4 clinical strata: patients without cancer, patients with metastatic cancer, patients with nonmetastatic cancer treated with surgery alone (“surgery alone”), and patients with nonmetastatic cancer treated with surgery plus chemotherapy or radiation therapy (“surgery+”). We identified new, early additional, and long-term additional opioid use and calculated the change in predicted probability of these outcomes from 2012 to 2017. Results New opioid use was higher in patients with cancer (46.4%) than in those without (6.9%) (P &lt; .001). From 2012 to 2017, the predicted probability of new opioid use was more stable in the cancer strata (relative declines: 0.1% surgery alone; 2.4% surgery+; 8.8% metastatic cancer), than in the noncancer stratum (20.0%) (P &lt; .001 for each cancer to noncancer comparison). Early additional use declined among surgery patients (‒14.9% and ‒17.5% for surgery alone and surgery+, respectively) but was stable among patients with metastatic disease (‒2.8%, P = .50). Conclusions Opioid prescribing declined over time at a slower rate in patients with cancer than in patients without cancer. Our study suggests important but tempered effects of the changing opioid climate on patients with cancer.

1592 Background: While ongoing efforts to decrease opioid use have dramatically altered the prescribing landscape, the impact on patients with cancer is not well understood. We examined trends in new and persistent opioid use in opioid-naïve older patients with and without cancer in the United States. Methods: This retrospective cohort study used SEER-Medicare linked data for patients with solid tumors malignancies diagnosed from 2012 through 2017, and a random sample of patients without cancer. We included patients who did not receive opioids for 3 months prior to the diagnosis or randomly assigned index date. We identified new opioid use (claim in 0-90 days after diagnosis/index date), early persistent opioid use (claims in days 0-90 and 91-180), and long-term persistent opioid use (claims in days 0-90 and 91-180 and months 13-15). Further analysis focused on 4 clinical strata: non-cancer, metastatic cancer, cancer treated with surgery alone, and cancer treated with surgery plus chemotherapy and/or radiotherapy ("surgery+"). We calculated relative changes in the predicted probability of opioid use from 2012 to 2017 based on a logit model adjusted for patient demographics. Results: We identified 238,470 eligible patients with cancer (mean age 76.3 years). Among patients with cancer, 46.4% had new opioid use; use was higher among those receiving surgery+ (70.6%), those treated with surgery alone (58.8%) and those with metastatic cancer (50.0%), compared to patients without cancer (6.9%). From 2012 to 2017, the predicted probability of new opioid use declined in all groups, with lower relative decline in the cancer subgroups (6.8% surgery+; 9.5% surgery alone; 10.2% metastatic cancer) compared to the non-cancer comparator (24.7%). For instance, in patients with metastatic cancer, predicted probability of new use decreased from 52.4 to 47.1% (10.2%) vs. 8.0 to 6.0% (24.7%) in patients without cancer. Relative decline in predicted probability of long-term persistent opioid use was lower in the surgical cancer strata (44.2% surgery+; 46.1% surgery alone) vs. the non-cancer comparator (54.0%). Conclusions: While opioid use remains common in patients with cancer, new and persistent opioid use declined over time in all patients, though with steeper relative declines in non-cancer compared to cancer populations. Our study suggests important but tempered effects of the changing opioid climate on patients with cancer.[Table: see text]

Abstract Background: Overall, patients with cancer experience a greater risk of adverse outcomes following SARS-CoV-2 infection; however, little is known for those with BC. Methods: CCC19 (NCT04354701) is an international cohort study aimed at investigating the impact of COVID-19 in patients with a history of or active cancer using de-identified data on patient demographics, cancer history, clinical course and outcomes of COVID-19. The current analysis includes patients from U.S. and Canada with invasive BC and laboratory-confirmed SARS-CoV-2 entered between March 17, 2020 and July 2, 2020. Co-primary outcomes were hospitalization during COVID-19 illness and 30-day all-cause mortality. Frequencies for categorical variables and medians (range) for continuous variables were estimated. Final presentation will include bivariable and multivariable Cox proportional hazards regression analysis to identify risk factors (including BC subtypes and therapies, for which data collection is ongoing) associated with 30-day all-cause mortality and severe COVID-19 illness (composite of any hospitalization requiring supplemental oxygen, admission to an intensive care unit [ICU], use of mechanical ventilation, or death). Results: During the study period, a total of 2683 patients with cancer and COVID-19 were accrued in the CCC19 registry including 529 (20%) with invasive BC. Among patients with BC, 352 (67%) were 60 years or older; 518 (98%) were women; 275 (52%) non-Hispanic White, 116 (22%) non-Hispanic Black, 70 (13%) Hispanic, 56 (11%) in other categorizations; 178 (34%) had a smoking history; 75 (14%) ECOG performance status ≥2; 191 (36%) with &gt;2 active comorbidities; 64 (12%) with AJCC stage IV disease at BC diagnosis; and 267 (50%) were on anti-cancer treatment including systemic therapy, radiation, or surgery within 3 months of COVID-19 diagnosis. At least 323 (61%) patients with BC had 30-day follow-up after COVID-19 diagnosis, and 35 (7%) had 90-day follow-up. COVID-19 illness at initial diagnosis required outpatient care in 288 (54%), inpatient care in 193 (36%), and ICU care in 40 (8%). Overall, 247 (47%) were hospitalized and 30-day all-cause mortality was 9%. 30-day all-cause mortality rates by receipt of major BC treatment modalities (within past 3 months) were: 10% for those on cytotoxic systemic therapy vs 5% and 12% for noncytotoxic systemic therapy and local therapy, respectively. The table shows hospitalization and mortality outcomes by major demographic and BC treatment strata. The final presentation will incorporate the latest patient accrual and evaluate independent clinical risk factors associated with serious COVID-19 outcomes in patients with BC. Conclusions: This represents the largest study to date of COVID-19 outcomes in patients with invasive BC. Nearly half of the patients with BC required hospitalization during their COVID-19 disease course and we observed a 9% 30-day all-cause mortality. Submitted on behalf of the COVID-19 and Cancer Consortium (ccc19us.org) Table 1. COVID-19 related hospitalization and 30-day all-cause mortality for all patients with invasive BCNAny Hospitalization30-day all-cause MortalityN% [95% CI]N% [95% CI]Total population52924747 [42-51]499 [7-12]Age&lt;601774425 [19-32]21 [0-4]60-691155144 [35-54]87 [3-13]70-791206655 [46-64]1714 [8-22]80+1178674 [65-81]2219 [12-27]ECOG PS0-132212238 [33-43]165 [3-8]2+756181 [71-89]1621 [13-32]Active Comorbidities0741014 [7-23]00 [0-5]1-22239442 [36-49]178 [5-12]&gt;219112968 [60-74]2915 [10-21]Treatment IntentCurative1866434 [28-42]95 [2-9]Palliative743953 [41-64]1216 [9-27]Cancer StatusRemission/NED33115447 [41-52]247 [5-11]Active disease, stable or responding to treatment1194840 [31-50]76 [2-12]Active disease, progressing372773 [56-86]1130 [16-47]Treatment Modality (within 3 months)Cytotoxic chemotherapy833542 [31-54]810 [4-18]Noncytotoxic therapy1856435 [28-42]105 [3-10]Local therapy (surgery or radiation)341750 [32-68]412 [3-27] Citation Format: Ali Raza Khaki, Dimpy P Shah, Maryam B Lustberg, Melissa K Accordino, Daniel G Stover, Gayathri Nagaraj, Donna R Rivera, Edith A Perez, Sara M Tolaney, Jeffrey Peppercorn, Petros Grivas, Jeremy L Warner, Corrie A Painter, Gilberto de Lima Lopes, Jr, Solange Peters, Michael A Thompson, Toni K Choueiri, Brian I Rini, Gary H Lyman, Nicole M Kuderer, Shaveta Vinayak. Characteristics and outcomes of SARS-CoV-2 infection in patients with invasive breast cancer (BC) from the COVID-19 and cancer consortium (CCC19) cohort study [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS7-01.