bluuebunny/crossref_metadata_2025 huggingface dataset:
Can synthetic data accurately mimic oncology clinical trials?
Authors: El Kababji Samer , Mitsakakis Nicholas , Fang Xi , Beltran-Bless Ana-Alicia , Pond Gregory Russell , Vandermeer Lisa , Radhakrishnan Dhenuka , Mosquera Lucy , Clemons Mark J. , El Emam Khaled
Published: June 2023

1554

Background: There is strong interest by researchers, the pharmaceutical industry, medical journal editors, funders of research, and regulators in sharing clinical trial data. Reusing data extracts the most utility possible from patient contributions. The majority of patients do want to share their data for secondary research purposes. However, data access for secondary analysis remains a challenge. A key reason why individual-level data is not made directly available to data users by authors and data custodians is concern over breaches of patient privacy. Synthetic data generation (SDG) is an effective way to address privacy concerns that can enable the broader sharing of clinical trial datasets. However, a key question is whether the reproducibility of the generated data is adequate to draw reliable conclusions. Methods: We synthesized datasets from five pragmatic breast cancer clinical trials performed by the REaCT group (https://react.ohri.ca/). A sequential synthesis method, a type of machine learning was performed. The published analysis of each trial was repeated on each synthetic dataset to evaluate reproducibility. We evaluated reproducibility on three criteria: (a) decision agreement: the direction and statistical significance of the primary endpoint effect estimates are the same as the real data, (b) estimate agreement: the parameter estimates from the synthetic data are within the 95% confidence interval of the real data, and (c) the confidence interval overlap between real and synthetic parameters is above 50%. In addition, we evaluated privacy using a membership disclosure metric. This evaluates the ability of an adversary to determine that a target individual was in the original dataset using the synthetic data, computed as an F1 classification accuracy score. Results: Our results show that decision and estimate agreements held true across all five trials, and the confidence interval overlap was high. The risks of membership disclosure are all below the established 0.2 threshold. Conclusions: In this study, we were able to successfully generate synthetic datasets that accurately replicated original data from 5 oncology trials and yielded the same results as in the original published studies, with a very low risk of membership disclosure. With proper modeling techniques, synthetic datasets can play a key role in data democratization and the reuse of oncology clinical trials.[Table: see text]
An intelligent machine learning model for real-time early detection of undesirable cancer events: AIM2REDUCE.
Authors: Grant Robert C. , Kabir Muammar , Yuan Baijiang , Grant Benjamin , Narine Sharon , He Kevin , Ajaj Rami , Zhan Luna Jia , Fawzy Aly , Xu Janine , Zhang Yuhua , Yu Vivien , French Conor , Xu Wei , Krishnan Rahul G. , Gallinger Steven , Krzyzanowska Monika K. , Truong Tran , Liu Geoffrey
Published: June 2023

1557

Background: Cancer and its treatment cause undesirable cancer events (UCEs). Automated warning systems could reduce the frequency and severity of UCEs by alerting the healthcare team and allocating preventative interventions. Most previous studies predicted single UCEs at the initiation of treatment. In AIM2REDUCE, we developed and evaluated a general-purpose system for predicting UCEs during outpatient systemic anti-cancer therapy. Methods: Each time a patient receives treatment, AIM2REDUCE applies machine learning to the preceding data in the electronic medical record (EMR) to predict future UCEs. We identified patients treated for aerodigestive cancers from the EMR at Princess Margaret Cancer Centre, who were randomly split into development, validation, and test cohorts. Features included cancer diagnosis, treatment sessions with doses, laboratory tests, and patient-reported symptoms. UCEs are listed in the Table. We trained LASSO regression and random forests models in the training cohort and tuned hyperparameters in the validation cohort using Bayesian optimization. We evaluated performance across discrimination, calibration, and net benefit in the test cohort. Results: The cohort included 5,760 patients who received 175,565 treatment sessions, with 13,612,746 unique data points across 102 features. Of these patients, 2,352 (40.8%) were female, the median age was 64.0 years (interquartile range 14.0), the most common diagnoses were lung cancer (2,071, 36.0%) and pancreatic cancer (926, 16.1%), and the most common treatment regimens were weekly gemcitabine (433, 7.5%) and maintenance pemetrexed (417, 7.2%). The Table shows the performance of AIM2REDUCE. Conclusions: We demonstrate that longitudinal machine learning systems trained using EMR data can accurately predict a wide range of UCEs. Based on these results, automated warning systems should be implemented and evaluated in real-time clinical practice. [Table: see text]
Early assessment of sotorasib for treatment of patients with advanced non-small cell lung cancer using real-world data in the United States.
Authors: Aran Dvir , Shahoha Meishar , Rosenberg-Katz Keren , Amar-Farkash Shlomit
Published: June 2023

1560

Background: Sotorasib is the first small molecule for targeting tumors with KRAS G12C mutations. Despite promising early results which led to expedited approval, recent interim results from the phase III clinical trial suggest similar efficacy to standard-of-care chemotherapy docetaxel. Here we perform the first evaluation of sotorasib for the treatment of non-small cell lung cancer (NSCLC) in real-world setting. Methods: Elevance Health claims data was used. Lung cancer (LC) patients with sotorasib claims between June 2021-August 2022 were identified (assumed to be NSCLC). LC patients treated with docetaxel as second-line+ were used as control group. Potential confounding factors, including social determinant index (SDI), age, gender, Charlson Comorbidity Index (CCI), and metastases profile were addressed using inverse probability treatment weighting (IPTW). Outcomes were hospitalizations and real-world overall survival (rwOS), which was estimated using weighted Kaplan-Meier estimator. For comparison with the clinical trial population-level adjustments were performed. Results: Cohorts included 105 sotorasib-treated and 448 docetaxel-treated patients. Sotorasib-treated were primarily female, of older age and had more comorbidities. Posttreatment all-cause hospitalization rates were similar during the first 3 months (36% in both). Most common hospitalization diagnosis was gastrointestinal (GI) related which was uncommon in the control group (29% vs. 8%, p<.001). No evidence for liver toxicity was identified. For a subset of patients it was possible to perform survival analysis. Adjusted survival curves of RWD and the clinical trial (CodeBreak-100) were indistinguishable following population-level adjustment (p=0.92). Adjusted RWD sotorasib and the control cohorts revealed non-significant difference in rwOS up to 6-months of follow-up (62% sotorasib vs. 55% docetaxel; p=0.1). Conclusions: We present the first analysis of sotorasib in US real-world settings. This early analysis suggests that sotorasib does not provide survival benefit at 6-months follow-up. Sotorasib is associated with increased GI-related severe adverse events. RWD can be used to provide early information in expedited FDA approved treatments. [Table: see text]
ALAN as an omic tool to build gene signatures and to stratify patients.
Authors: Bergom Hannah E. , Day Abderrahman , Shabaneh Ashraf , Ali Atef , Boytim Ella , Wang Jinhua , Hwang Justin
Published: June 2023

1563

Background: Understanding aberrant gene behavior is critical towards devising clinical therapeutics or gene based diagnostic panels. Clustering and AI/ML have clinical utility, but they do not contextualize changes in gene behavior that result from differences in cell type, microenvironment, or prior treatments. Here, we developed the Algorithm for Linking Activity Networks (ALAN), an informatics algorithm that allows rapid functional comparisons of all detectable genes between clinically annotated patient cohorts. ALAN outputs quantify gene behavior without any additional inputs and can be applied on all forms of clinical omic data. We tested the utility of ALAN to identify the molecular features of resistance and novel precision therapeutics. Methods: We applied the ALAN algorithm in prostate tissue using whole-transcriptome sequencing (WTS) data from SU2C/PCF (n = 209, metastatic prostate cancer), TCGA (n = 493, primary prostate cancer), and GTEX (n = 245, benign prostate tissue). We conducted informatics analysis of whole-exome sequencing (WES) data from SU2C/PCF (n = 444 mPC), Fred Hutch (n = 130 mPC), and MCTP (n = 61 mPC) to identify mPC patients with amplifications in RSPO2. We scored an ALAN gene signature in a patient with single-cell RNA sequencing pre and post AR inhibition (n = 112, 83). We examined ChIP-seq data to evaluate binding of AR and Co-factors at the CD276 transcription regulatory sequences. Results: In mPCs, ALAN unbiasedly identified genes that prior studies have implicated as resistance mechanisms towards enzalutamide. In this process, ALAN nominated RSPO2, a secreted protein, as a potential resistant gene that has never been targeted in mPC. In recent studies, we found RSPO2 amplifications in 19.7-28.5% of mPC. We utilized ALAN outputs to build a novel gene signature that was exclusively enriched (p-value < 0.0001) in the transcriptome collected from single cells of a post-resistant mPC sample. We also utilized ALAN to stratify the optimal mPC patients in receiving precision therapies against B7-H3 ( CD276). B7-H3 is an immune regulatory molecule in the B7 superfamily that includes PD-L1 and CTLA-4 and has not been targeted in mPC. B7-H3 was unlike other B7 family members and exhibited robust association with AR co-factors and AR signaling. We confirmed ALAN findings as multiple B7-H3 transcriptional enhancers and promoters were bound by AR and AR-cofactors. Conclusions: ALAN is an algorithm that can be readily deployed on existing clinical omic data to build gene signatures, identify resistant genes, and risk stratify patients. ALAN nominated a novel therapeutic target, RSPO2, which is recurrently amplified in mPC patients. ALAN predicted that mPCs with high baseline levels of AR activity would be optimal candidates for B7-H3 precision therapeutics. Altogether, ALAN outputs should be considered for making clinical decisions that would benefit by comprehensive comparisons of all detectable genes.
The inclusion of health-related quality of life and other patient-reported outcomes in landmark trials for Food and Drug Administration oncology drug approvals: An analysis of cancer drug approvals between 2006 and 2022.
Authors: Ojo Ademola Samuel , Ali Ahmed
Published: June 2023

1569

Background: How patients feel and function are essential elements of the clinical benefit of interventions which is often not captured by traditional measures of clinical benefit such as progression-free survival and overall survival. Health-related quality of life, functional status, symptom burden, and other patient-reported outcomes (PROs) assess the impact of interventions from the patient’s point of view. The aim of this study is to assess the inclusion of PROs in landmark trials leading to FDA oncology drug approvals. Methods: This is a retrospective cross-sectional study of pivotal trials leading to FDA oncology approvals between January 2006 and December 2022 based on the FDA oncology approval notifications. The trial protocols of all pivotal trials were evaluated for inclusion of health-related quality of life or other PROs as an outcome measure. The approved therapies were classified into first-line, adjuvant/maintenance, and second or later line of treatment. Chi-square tests were used to assess the relationship between the line of treatment and the inclusion of PROs in the trial protocol. Results: There were 420 oncology approvals during the study period with the highest number of approvals in a single year in 2020 (56) and the least in 2007 (7). Lung cancer has the highest number of approvals (61, 14.5%) followed by lymphoma (50, 12%), leukemia (49, 11.7%), genitourinary malignancies (48, 11.4%), breast cancer (36, 8.6%), gastrointestinal malignancies (32, 7.6%), plasma cell disorders (30, 7.1%) melanoma (20, 4.8%), gynecological malignancies (20, 4.8%), hepatobiliary malignancies (14, 3.3%) and head/neck cancers (14, 3.3%). The approved therapies were first line (146, 34.8%), second or higher line (226, 53.8%), and adjuvant/maintenance therapies (48, 11.4%). PROs were included in 40.7% of the pivotal trials. There is a rising trend in the inclusion of PROs from 5.5% of pivotal trials in 2006 to 31% in 2022. Trials on first-line therapies are more likely to include PROs compared to second or higher-line therapies (44.5% vs 36.7%; p = 0.13). Conclusions: Although there is a rising trend in the inclusion of health-related quality of life and other PROs in pivotal trials for FDA oncology drug approvals, most pivotal trials did not include PROs as outcome measures.[Table: see text]
Endpoints reported in phase 3 randomized clinical trials at ASCO 2022.
Authors: Teuwen Laure-Anne Marie Nicole , Young Joanna Alyse , Bourlon Maria Teresa , Segelov Eva , Prenen Hans
Published: June 2023

1570

Background: The goal of phase 3 randomized clinical trials (RCTs) is to show clinically meaningful benefit for patients. An analysis of phase 3 RCTs presented at the ASCO 2022 Annual Meeting (ASCO22) was undertaken to assess which endpoints were evaluated. Methods: A systematic analysis was undertaken of ASCO22 abstracts from phase 3 RCTs reporting primary, secondary, interim, updated, and subgroup analyses, as well as trials reporting methodology of currently enrolling studies. Trials that reported posthoc, exploratory, biomarker, and retrospective analyses of RCTs were excluded. Information from ASCO22 materials and clinical trial registration websites was recorded by two independent researchers. Results: In total, 166 RCTs were identified: 93 trials with 50,781 enrolled patients and 73 trials expected to enroll 52,098 patients. More trials reported on patients with locally advanced/metastatic cancer (64.5%) compared to localized cancer (35.5%). Funding source was pharmaceutical or biotechnology company in 62%. Within locally advanced/metastatic trials, overall survival (OS) was a primary endpoint in 40%, while progression-free survival (PFS) was a primary or co-primary endpoint in 45% and 13% respectively. Other primary endpoints included (invasive) disease-free survival ((i)DFS), event free survival (EFS), overall response rate and pathological complete response. In trials that did not include OS as a primary endpoint, OS was a secondary endpoint in 88% (n = 56/64). Within the localized group, trials were subdivided into adjuvant, neo-adjuvant, definitive and other categories. Within the adjuvant trials (n = 27), the most common primary endpoint was (i)DFS (37%), followed by OS (15%). Other primary endpoints included recurrence-free survival, invasive breast cancer free survival, metastasis-free survival, EFS, and PFS. Across all trials, quality of life (QOL) was never reported as a primary endpoint, however it was as a secondary or other outcome in 53% for locally advanced/metastatic trials and 42% for localized trials. When comparing the endpoints reported in the ASCO22 abstract and meeting materials with those listed on the trial registration website, discordance was noted in 14%. Conclusions: Phase 3 RCTs presented at ASCO22 represented participation from over 100,000 patients, however, fewer than half in locally advanced/metastatic cancer and fewer than one quarter in localized disease utilized OS as a primary endpoint. QOL was listed as an endpoint in roughly one half of all trials. Endpoints reported did not match registration data in a significant minority. Debate over which endpoints should be used for cancer RCTs should be informed by this data.
Global adoption of remote technologies to enable patient-centric oncology clinical trials: Analysis by the Bloomberg New Economy International Cancer Coalition.
Authors: Daly Robert Michael , Brawley Otis W. , Gospodarowicz Mary K. , Olopade Olufunmilayo I. , Fashoyin Ibilola , Wolodzko Smart Victoria , Chang I-Fen , Tendler Craig L. , Kim Geoff , Fuchs Charles S. , Zhang Lianshan , Legos Jeffrey J. , Duran Cristina , Kalidas Chitkala , Qian Jing , Finnegan Justin , Pilarski Piotr , Silverstein Amy , Wu Yi-Long , Li Bob T.
Published: June 2023

1584

Background: Fewer than 5% of patients with cancer enroll in a clinical trial, partly due to the significant financial and logistical burden on patients, especially among underserved populations. The COVID-19 pandemic marked a significant shift in the adoption of remote technologies and decentralized trial operations by major pharmaceutical companies. We sought to determine the current global state of adoption of these technologies, understand factors that are driving or preventing adoption of them, and highlight aspirations and direction for industry to enable more patient-centric trials. Methods: The multi-stakeholder Bloomberg New Economy International Cancer Coalition composed of patient advocacy, industry, government regulators, and academic medical centers developed a survey directed to global biopharmaceutical companies of the Coalition with a focus on registrational clinical trials. The survey was organized into three main sections: 1) Impact of different remote monitoring and data collection technologies on patient-centricity; 2) Adoption of these technologies in oncology and all therapeutic areas; 3) Barriers/facilitators to adoption. Results: Administered from October 1 to December 31, 2022, a total of 8 companies completed the survey (response rate: 100%), representing 33% of oncology market by revenues in 2021. Across nearly all remote monitoring and data collection technologies, adoption in oncology trials lags that of all trials. In the current state, eDiary/eCOA is the most utilized technology with 56% and 51% adoption for all trials and oncology trials, respectively, whereas visits in local physician networks is the least adopted at 12% and 7%, respectively. Looking forward, the difference between the current and aspired adoption rate in 5 years for oncology is large, with respondents expecting a 40% or greater absolute adoption increase in 8 out of the 11 technologies (Table). Furthermore, respondents identified digitally enabled recruitment, local or mobile imaging capabilities, and local physician networks as those technologies that would be most impactful for improving patient centricity in the long term. Conclusions: This survey is the first by a coalition of global stakeholders to determine the current state and future aspirations for the use of remote technologies in oncology clinical trials. These efforts may galvanize momentum towards greater adoption of enabling technologies supporting a new paradigm of trials that are more accessible, less burdensome, and more inclusive.[Table: see text]
Association of state policies regulating short-term limited-duration insurance plans and cancer stage at diagnosis.
Authors: Barnes Justin Michael , Kirchhoff Anne C. , Yabroff Robin , Chino Fumiko
Published: June 2023

1589

Background: In 2018, federal regulations expanded access to short-term limited duration insurance (STLD) plans. STLD plans generally limit coverage of medical services and have no cost-sharing caps, which can delay a cancer diagnosis. Furthermore, uptake of STLD plans can destabilize individual insurance markets, leading to increased prices and subsequent barriers to care for comprehensive insurance plan enrollees. Several states introduced legislation prohibiting and/or limiting STLD plans, but it is unclear whether STLD plans or policies restricting their proliferation have affected cancer stage at diagnosis. Methods: Individuals ages 18-64 years with staged first primary malignancies diagnosed 2016-2019 were identified from the Surveillance, Epidemiology, and End Results (SEER) database. Difference-in-differences (DID) analyses evaluated changes in early-stage (stages 0 [breast and bladder only] through II) diagnoses from pre- (2016-2017) to post- STLD expansion (2019; 2018 was excluded as washout/phase-in period) between states with policies prohibiting and/or limiting STLD plans vs. states with no policies regulating STLD plans. In some states limiting but not prohibiting STLD plans, insurers stopped selling STLD plans; we conducted additional analyses by state STLD plan availability in 2019. Linear probability models utilized cluster-robust standard errors (clustered at state level) and adjusted for fixed state and year effects, sociodemographic covariates, and cancer site. Sensitivity analyses excluded states that expanded and/or substantially changed Medicaid eligibility during the study period. The plausibility of the parallel trends assumption was tested in adjusted models restricted to the pre-policy period (2016-2017) and was satisfied for all analyses. Results: 398,190 individuals were included. In adjusted DID analyses, early-stage diagnoses increased 0.95 percentage points (95% CI = 0.53 to 1.38, p<.001) in states that prohibited vs. did not regulate STLD plans, but there was no relative change in early-stage diagnoses in states with other policies limiting STLD plans (p=.25). Relative to states where STLD plans remained available, there was a nonsignificant increase in early-stage diagnoses in states where legislation stopped the sale of STLD plans, with greater evidence for an increase after excluding states with Medicaid eligibility changes (1.03, 95% CI = 0.71 to 1.35, p<.001). There were no differential changes in early-stage diagnoses by state group in falsification tests limited to individuals >65 years-old, who were Medicare-age-eligible. Conclusions: State legislation prohibiting and/or leading to the cessation of STLD plans was associated with an increased rate of early-stage cancer diagnoses. Alternatively, the proliferation of STLD plans was associated with a differential decreased rate of early-stage cancers.
Clinical practice guideline descriptions of oncologic drugs granted FDA accelerated approval: A cross-sectional study.
Authors: Mooghali Maryam , Wallach Joshua David , Mitchell Aaron Philip , Skydel Joshua J , Ross Joseph S. , Ramachandran Reshma
Published: June 2023

1590

Background: The Food and Drug Administration’s (FDA's) accelerated approval (AA) pathway allows drugs to be approved using surrogate endpoints, while requiring that sponsors complete postmarketing requirement (PMR) studies verifying clinical benefit. Subsequently, FDA determines whether AA can be converted to standard approval or be withdrawn. It is unclear whether clinical practice guidelines reflect PMR results or FDA regulatory decisions. As most drugs granted AA are cancer therapies, we investigated whether and how National Comprehensive Cancer Network (NCCN) guidelines reflect underlying evidence supporting AAs and subsequent FDA decisions. Methods: In this cross-sectional study, we used Drugs@FDA to identify drug indications granted AA by FDA for oncologic indications from 2016-2018, PMR status and results, and whether AA was converted to regular approval or withdrawn. We excluded pediatric and tumor-agnostic indications. PMR studies were classified as positive if the results from primary efficacy endpoint were statistically significant ( P<0.05) favoring the drug. For each AA indication, we searched relevant NCCN guidelines for their recommendations and examined if AA status, PMR results, and updated FDA decisions were reflected. Results: Among 36 oncology drug indications granted AA from 2016 to 2018, 29 (81%) NCCN guidelines did not mention that the drug was approved via AA pathway or had not yet verified clinical benefit. For all 36 (100%) indications, NCCN guidelines did not state that approval was based on surrogate endpoints. As of December 31, 2022, among 16 drug indications that were converted to standard approval, 13 (81%) guidelines reflected FDA’s updated decisions. Among 8 indications withdrawn after AA, 5 (63%) guidelines reflected the withdrawn status. Of 6 drug indications with negative PMR study results that were withdrawn, 2 (33%) were still recommended in NCCN guidelines thereafter. Conclusions: NCCN guidelines do not consistently reflect FDA regulatory status or PMR study results, highlighting the need for more up-to-date and accurate information to guide clinical practice.[Table: see text]
Trends in new and persistent opioid use in older adults with cancer.
Authors: Baum Laura Van Metre , KC Madhav , Soulos Pamela R. , Jeffery Molly , Ruddy Kathryn Jean , Leapman Michael , Jairam Vikram , Dinan Michaela Ann , Lerro Catherine , Woods Corinne , Lee Hana , Ho Amy , Graham David J. , Liberatore Mark , Rivera Donna , Gross Cary Philip , Park Henry Soo-Min
Published: June 2023

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]
Data transparency and demographic representation in approval packages of FDA-approved oncology drugs from 2012-2021.
Authors: Liu Jingyi , Jayaram Gowri , Varma Tanvee , Sammut Stephen , Guerra Carmen , Miller Jennifer E.
Published: June 2023

1594

Background: Over the past decade, the U.S. Food and Drug Administration (FDA) has leveraged regulations and guidance documents to accelerate improvements in demographic reporting and encourage adequate representation of minorities in clinical trials. This cross-sectional study aims to assess the impact of these interventions by characterizing demographic data reporting and representation by sex, age, and racial and ethnic identity in pivotal trials supporting novel cancer therapeutics approved by the FDA from 2012 through 2021. Methods: Study demographic data were abstracted from FDA drug approval packages and US cancer population demographic data was abstracted from US Cancer Statistics. The percentages of trials reporting sex, age, racial and ethnic identity of participants in drug approval packages were calculated and participation to prevalence ratios (PPRs) were calculated by dividing the percentage of participants in each demographic by the percentage of the US cancer population in each group. PPRs were constructed for each pivotal trial by cancer type. Adequate representation was defined as PPR 0.8-1.2 and the proportion of trials which were adequately representative of each demographic was calculated and trended over time. Results: From 2012 through 2021, the FDA approved 118 cancer therapeutics, based on 131 pivotal trials. For drugs approved 2012-2016, the majority of associated pivotal trials reported participation based on sex (100% of trials), age (100%) and White (98%), Black (75%) or Asian (84%) racial identity, but not American Indian or Alaskan Native racial identity (18%) or Hispanic ethnic identity (41%). For drugs approved 2017-2021, there were no significant improvements in demographic data reporting, although there was a trend towards increased reporting on Hispanic ethnic identity from 2012-2016 (41%) to 2017-2021 (65%) (p= 0.06). For drugs approved 2012-2016, most pivotal trials adequately represented female participants (78% of trials) and participants identifying as White (87%), but few pivotal trials adequately represented older adults (7%), participants identifying as Black (11%), American Indian or Alaskan Native (0%), Asian (18%) or Hispanic (5%). Representation in pivotal trials did not significantly improve for any demographic for drugs approved 2017-2021 (p>0.05). Conclusions: This study found that the last decade’s efforts to improve demographic data transparency and representation in clinical trials have not yet borne fruit for novel cancer therapeutics. More consequential FDA regulations may be necessary. Beyond the FDA, demographic data transparency and adequate minority representation in oncology clinical trials is an all-stakeholder responsibility. A more just clinical trial infrastructure requires greater collaboration between the FDA, sponsors, enrollers, contract research organizations and cooperative groups.
Is Medicare Advantage associated with more favorable health care access, acute care utilization, and affordability among beneficiaries with cancer?
Authors: Patel Vishal R. , Jafri Faraz , Gupta Arjun , Hussaini S. M. Qasim
Published: June 2023

1597

Background: The Medicare Advantage (MA) program provides care to nearly half of Medicare beneficiaries, including a rapidly growing population of cancer survivors. Although MA was designed to optimize healthcare access, outcomes, and affordability, it is unknown whether these effects have been achieved in cancer survivors. Methods: We performed a cross-sectional study of Medicare beneficiaries ≥65 years with a self-reported history of cancer in the 2019 National Health Interview Survey. We used multivariable logistic regression to evaluate the association between Medicare program type (MA vs traditional Medicare, TM) and measures of healthcare access, acute care utilization, and affordability. Results: We identified 4,451 beneficiaries with a history of cancer, corresponding to 26.6 million weighted cancer survivors in 2019. Of beneficiaries, 35.8% were enrolled in MA while 64.2% were enrolled in TM. The age, sex, racial and ethnic composition, household income, primary site of cancer, and co-morbidity burden of MA and TM beneficiaries were similar. In adjusted analysis, there were no differences in health care access or acute care utilization between TM and MA beneficiaries. However, survivors enrolled in MA were more likely to worry about (34.3% vs 29.4%; aOR, 1.3 [95% CI, 1.1-1.5]) or have problems paying (13.6% vs 11.1%; aOR, 1.4 [95% CI, 1.1-1.8]) medical bills. Conclusions: MA beneficiaries with a previous cancer diagnosis more often struggle paying medical bills despite similar healthcare access and preventive care as TM. Despite generous benefits and attractive incentives for care coordination and health management, privately run MA plans may not be more cost-effective than TM for cancer survivors. Our study informs ongoing congressional deliberations to re-evaluate the role of MA in promoting equity among beneficiaries.[Table: see text]
System-wide approach on biosimilars adoption in oncology: Strategic plan on switching and cost savings.
Authors: Limvorasak Suwicha , Kim Kyung , Dobbs Crystal Leung , Posadas Edwin Melencio , Scher Kevin , Chang Johnny , Chiu Vi Kien , Diniz Marcio A. , Rogatko Andre , Teaford Hilary , Sakamoto Leanne , Vinson Bruce , Patel Vipul , Figlin Robert A. , Shane Rita , Reckamp Karen L.
Published: June 2023

1600

Background: Biosimilars provide competitive, lower-cost alternatives to biologic drugs in cancer treatment. As more agents become available in the US, institutions have to implement a strategy for successful adoption that is feasible, safe and provide price competition among biosimilar manufacturers. Methods: We aimed to standardize biosimilar utilization across the Cedars-Sinai Health System (CSHS) by integrating institutionally developed clinical pathways and insurance prior-authorization into the existing electronic health record (EHR). The initial study was limited to bevacizumab, rituximab and trastuzumab. To align with CSHS guideline recommendations, biosimilar indications for use were reviewed by each disease related group (DRG). Biosimilar brands for each drug were selected through a formulary process vetted by the Pharmacy & Therapeutics Committee. Physicians were permitted to opt-out of switching via an option provided within the electronic order set. To test feasibility of this approach, patients were divided into two groups as 1) main medical center (Cedars Sinai Medical Center) and 2) Cedars-Sinai Cancer affiliated sites. Feasibility was defined as a compliance rate of 80% or greater at the main medical center and 75% or greater at the affiliated sites. This study was powered to detect a minimum difference at 5.7% and 8.9%, respectively. Results: Between January 2021 to September 2022, a total of 1,139 cancer patients who initiated treatment with bevacizumab, rituximab or trastuzumab were identified through the EHR, of whom 650 were eligible (age 18-96; 61% female, 39% male). Using our approach, the compliance rate was 86% at the main site (p<0.001, 95%CI: 82.5-89.1) and 88% (p<0.001, 95%CI: 82.1-91.7) at the affiliated sites, resulting in a 56% improvement from baseline (86% vs. 55%, p<0.001). Among 14% of patients who did not switch to institutional-preferred biosimilar brands, the most common reasons for this were payer mandated use of an alternate brand (5%), off-label indication (4%), enrolled in patient assistance program (3%) and physician preference (2%). Five patients (<1%) did not switch to biosimilars due to history of infusion reactions. Insurance type (HMO, PPO, Medicare, others) was not associated with non-compliance (p=0.876). Cost savings were projected to be over $4 million over a duration of two years. Conclusions: Enterprise-wide switching to one specific biosimilar brand is feasible and facilitated through leveraging of the EHR. This approach optimized exiting organizational infrastructure to standardize biosimilar utilization and promote substantial cost savings.[Table: see text]
Correlation between Oncotype DX, Predict, and Nottingham Prognostic Index on HR+, HER2- early breast cancer treatment: The current value of molecular testing.
Authors: Campoverde Leticia , Camacho Felipe , Sanchez Adriana , Lugo Paulina
Published: June 2023

1601

Background: The Oncotype DX Breast Recurrence Score (ODX) assay is a 21-gene assay validated in hormone receptor-positive, HER2 negative invasive breast cancer (BC) to predict chemotherapy benefit and risk of distant recurrence at 10 years regardless of node status and is also a strong predictor of mortality. ODX can minimize the misuse of chemotherapy, financial burden, and improve clinical outcomes. ODX is not widely used in Ecuador due to socioeconomic and healthcare access disparities; instead, many physicians stratify patients' risk according to clinicopathological and immunohistochemical features. We aim to compare the differences between ODX and two of the most common stratification clinical tools: Predict Score (PS) and Nottingham prognostic index (NPI). Methods: Retrospective analysis of women with early BC who underwent ODX testing in Ecuador from May 2020 to January 2023. Inclusion criteria: early BC (T1-T3 / N0-N1a); estrogen receptor (ER) positive; HER2 negative by immunohistochemistry; and available data of tumor size, grade, lymph node status, and Ki67 proliferation index. Exclusion criteria: patients with recurrent BC, incomplete pathology, or immunohistochemistry data. PS and NPI were calculated using online tools. The correlation between PS, NPI, and ODX scores was analyzed using Spearman's correlation coefficient in SPSS. Results: 77 patients underwent ODX testing, of which 58 patients (mean age 55 years old) met the inclusion criteria. Invasive breast carcinoma not otherwise specified was the most common type (48 patients (82%). Risk scores generated by PS correlated strongly with NPI for all patients (r=0.47; p ≤ 0.001). A strong correlation was also found between ODX and NPI (0.79, p<0.027). Risk scores were then stratified by patient risk category. For low-risk patients, 68% of correspondence between ODX and PS was found, and 98% between ODX and NPI. Intermediate-risk patients showed a correspondence between ODX and PS of 5% and 9% for ODX and NPI. High-risk patients showed a correspondence of 50% between ODX and PS and 17% between ODX and NPI. Conclusions: ODX risk recurrence for low-risk patients is highly correlated with PS and NPI. For Intermediate and high-risk patients determined by PS and NPI, ODX testing provided valuable and prognostic information and should be considered to guide adjuvant treatment. [Table: see text]
RANO 2.0: Proposal for an update to the Response Assessment in Neuro-Oncology (RANO) criteria for high- and low-grade gliomas in adults.
Authors: Wen Patrick Y. , Van Den Bent Martin J. , Youssef Gilbert , Cloughesy Timothy Francis , Ellingson Benjamin M. , Weller Michael , Galanis Evanthia , Barboriak Daniel , de Groot John Frederick , Gilbert Mark R. , Huang Raymond Yi-kun , Lassman Andrew B. , Mehta Minesh P. , Molinaro Annette , Preusser Matthias , Shankar Lalitha Krishna , Wick Wolfgang , Reardon David A. , Vogelbaum Michael A. , Chang Susan Marina
Published: June 2023

2017

Background: Response Assessment in Neuro-Oncology (RANO) criteria for high-grade and low-grade glioma (HGG and LGG) were developed to improve reliability of response assessment in glioma trials. Several limitations of the original RANO criteria have been reported. Methods: To address limitations of the original RANO criteria, a large cohort of patients with newly diagnosed and recurrent glioblastoma were evaluated comparing RANO-HGG with modified RANO (mRANO) and immunotherapy RANO (iRANO) criteria to inform the following proposed updates (RANO 2.0). Results: Based on the 2021 WHO classification of glioma, we recommend a single common set of criteria for all gliomas regardless of WHO grade and IDH mutational status. These criteria will be used for all trials regardless of the treatment modalities being evaluated. In newly diagnosed glioblastoma, the post-radiotherapy MRI, usually obtained approximately 4 weeks after completion of radiotherapy, rather than the post-surgical MRI as proposed in original RANO criteria, will be used as the baseline for comparison of subsequent scans. Since the incidence of pseudoprogression is high in the first 3 months following radiotherapy, confirmation of progression during this period with a repeat MRI (in 4-8 weeks) will be required for determining radiographic progression of disease (PD) if the patient is clinically stable. However, confirmation scans are not mandatory after this period nor for recurrent tumors since these scans do not appear to improve reliability in determining progression. For agents with a high likelihood of producing pseudoprogression such as viral therapies and some other immunotherapies, mandatory confirmation of progression with a repeat MRI is an option. The primary measurement will remain the 2-dimensional maximum cross-sectional area of tumor as the simplest method, but where resources are available, volumetric measurements are an option. For IDH wild-type tumors with contrast enhancement, non-enhancing tumor will no longer be evaluated with the possible exception of patients receiving antiangiogenic therapies. However, in tumors with a significant non-enhancing component, both the contrast enhancing and non-enhancing components will be evaluated as target lesions. Conclusions: We hope that these and other proposed changes by the RANO working group will improve response assessment in glioma clinical trials and help the development of more effective therapy for patients.
EO2401 (E) peptide immunotherapy + nivolumab (N) +/- bevacizumab (B) in recurrent glioblastoma (GB): EOGBM1-18/ROSALIE.
Authors: Wick Wolfgang , Idbaih Ahmed , Vieito Maria , Ghiringhelli François , Stradella Agostina , Tabatabai Ghazaleh , Burger Michael C. , Mildenberger Iris , Herrlinger Ulrich , Wen Patrick Y. , Touat Mehdi , Wick Antje , González Macarena , Hervieu Alice , Gil-Martin Marta , Renovanz Mirjam , Maia Ana , Bonny Christophe , Fagerberg Jan , Reardon David A.
Published: June 2023

2020

Background: EO2401 was designed to activate/expand existing memory T cells recognizing specific protein sequences from gut bacteria, which cross-react with tumor associated antigens (TAAs). E contains 3 CD8 HLA-A2 epitopes with mimicry to GB-TAAs (IL13Rα2, BIRC5, and FOXM1) and the CD4 epitope UCP2. Methods: Patients (pt) at 1st progression GB received E (300 µg/peptide, q2w x4 then q4w) with N (3 mg/kg q2w) in cohorts: 1a E x2 → EN; 2a/1, 2a/2 and 2b EN from start; 2c EN x2 → surgery → EN; 3/1 and 3/2 EN + B (10mg/kg q2w) (Table). Results: Among 100 treated pt EN+/-B was well tolerated, with E associated events limited to local skin reactions (45% of pt; 96% Grades 1/2, and 4% Grade 3) and N-/B-tox consistent with historical data. EN induced immune response against all 3 mimics in 94% of 35 tested pt (all pt responded against at least 2 mimics), detectable as early as 2 weeks after first EN, and with durations beyond 10 months. Cross-reactivity against human peptides found in 89%. Conclusions: EN +/- B was well tolerated and generated fast and durable immune responses. EN survival like current standards. Delayed N was not advantageous for outcome. sLDB increased trt duration of EN, and improved efficacy. Continuous B plus EN further improved efficacy. Neo-/adjuvant EN was clinically feasible. Updated data, including C3/2 to confirm C3/1, to be presented. Clinical trial information: NCT04116658 . [Table: see text]
Association of CDK4 amplification with duration of response to bevacizumab in glioblastoma.
Authors: Villano John L. , Morgan Rachael M , Zhang Shulin , Kolesar Jill , Xiu Joanne , Seifert Hilary , Nicolaides Theodore , Rock Stephanie , Kesari Santosh , Aulakh Sonikpreet , Wong Eric T. , Glantz Michael J.
Published: June 2023

2026

Background: Bevacizumab remains the standard second line therapy in glioblastoma (GBM) with reported improved progression free survival, but not overall survival. We investigated a large clinico-genomic database of GBM patients treated with bevacizumab for molecular alterations associated with treatment outcome. Methods: Molecular profiles of GBM were tested by next-generation sequencing (NGS) of DNA (592 genes, NextSeq or whole-exome sequencing, Novaseq) and RNA (whole transcriptome sequencing, NovaSeq) at Caris Life Sciences (Phoenix, AZ). Gene amplification was determined by NGS with a threshold of > = 6 copies. Real-world survival information was obtained from insurance claims data. Time-on-treatment (TOT) of bevacizumab was calculated from start to finish of treatment while post-bevacizumab overall survival (bevOS) from start of bevacizumab to last day of contact. Short-term (ST) and long-term (LT) responders were defined as those with TOT ≤6 months and ≥1 year, respectively. Kaplan-Meier estimates were calculated and significance was determined as p values of < 0.05. For molecular comparisons, Fisher’s exact tests and Mann-Whiney U were used when appropriate. Results: Among the total of 383 ST and 107 LT patients identified, no significant difference in gender or age were seen. The LT cohort had significantly longer bevOS compared to the ST cohort (HR 0.27, [95% CI: 0.28-0.35], p < 0.0001). Interestingly, CDK4 amplification was seen in 23% (18/78) of LT patients but only 7% (21/300, p = 0.0002) of ST. When investigating the total cohort of 498 GBM treated with bevacizumab, CDK4 amplified patients demonstrated significantly improved TOT compared to non-amplified (HR: 0.639, [0.48-0.85, p = 0.002]). Conversely, the ST cohort had significantly more EGFR amplifications than the LT cohort (43%, 130/300 vs. 19%, 15/79, p < 0.0001). In the total bevacizumab-treated cohort, EGFR-amplified GBM had significantly worse TOT on bevacizumab than non-EGFR amplified GBM (HR 1.387, [1.15-1.67], p < 0.001). No associations were seen in other alterations explored including PIK3CA mutation (HR = 0.81 [0.587-1.113], p = 0.2), EGFR mutation (HR: 1.209, [0.977-1.495], p = 0.1) or RAF1 (HR: 0.647, [0.318-1.317], p = 0.2). Conclusions: Using a large clinical genomic database with GBM subjected to comprehensive molecular profiling, we demonstrated that amplification of CDK4 and EGFR were associated with long-term and short-term responses to bevacizumab, respectively. This warrants further investigation in independent cohorts controlled for age and other prognostic factors. If confirmed, a genetic basis for treatment optimization may provide meaningful clinical outcomes.