bluuebunny/crossref_metadata_2025 huggingface dataset:
Profile and outcomes of patients with subsequent ovarian cancer diagnosis following a prior malignancy in the United States.
Authors: Akinyemi Oluwasegun , Abodunrin Faith , Andine Tsion F , Akinwumi Bolarinwa , Akinyemi Irene , Ojo Ademola , Lipscombe Christina , Silberstein Peter T.
Published: June 2022

e18541

Background: The relationship between a subsequent ovarian cancer and a prior malignancy is complex with possible etiological, genetic, and therapeutic implications. Little is known about the epidemiological and clinical profile of this category of patients. The aim of the present study is to determine the factors associated with the development of ovarian cancer as a subsequent malignancy after a prior malignancy from another organ and determinants of improved survival in these women. Methods: We utilized the SEER 18 Registry 1975-2016 to conduct a retrospective analysis of women who developed a second primary ovarian malignancy following a prior cancer diagnosis. The outcome of interest was the latency interval between the initial primary malignancy diagnosis and a subsequent ovarian cancer diagnosis. Utilizing the cox regression model, we determined the factors associated with the overall survival of these women. Results: There were 10, 800 women who subsequently developed ovarian cancers following a prior malignancy. The commonest prior malignancies were breast cancers (38.2%), endometrial cancers (23.7%), and colorectal cancers (9.5%). The latency interval from developing a subsequent ovarian malignancy was 6.8±6.3 yrs. (Breast cancers) and 0.6 ± 2.5 yrs. (Endometrial cancers). A prior surgical treatment (OR = 1.19; 95% CI 1.02-1.40) or radiotherapy (OR = 1.34, 95% CI 1.21-1.49) in the initial primary malignancy is associated with a > 5years development of a subsequent ovarian malignancy. Black patients (OR = 1.63, 95% CI 1.39-1.92) have the worst survival even after controlling for disease stage and treatment modalities. Determinants of improved overall survival include White race, private insurance, age < 45 years at first primary malignancy diagnosis, prior surgical therapy, and increased latency interval. A prolonged latency interval is associated with a 74% increase in survival (OR = 0.26; 95%CI 0.23-0.30). Conclusions: Determinants of improved survival among patients with subsequent ovarian cancers following a prior primary malignancy include White race, private insurance, and a prolonged latency interval of progression from an initial primary malignancy to a subsequent ovarian cancer.
A mixed-methods study of healthcare provider perspectives on the barriers to enrollment of minority patients on cancer clinical trials.
Authors: Kim Yonghun , O'Shea Mary , Asiedu Gladys , Price Katharine Andress Rowe , Warsame Rahma M.
Published: June 2022

e18544

Background: Underrepresented minority (URM) patients continue to make up a small percentage of patients treated on cancer clinical trials (CCTs), thus perpetuating health care disparities. Research indicates that engagement of healthcare staff is critical for successful recruitment. Our study sought to better define barriers to minority recruitment to CCT from the research staff perspective. Methods: Semi-structured qualitative interviews were conducted of key stakeholders for CCT enrollment, including clinical research coordinators (CRCs), principal investigators (PIs), and treating clinicians. Questions for the healthcare team explored their experiences caring for URM patients with specific inquiry into the barriers of enrollment/retention and the processes or resources required to better meet patient needs. Results: All hematology and oncology staff at Mayo Clinic Cancer Center were invited to participate via email. Of the 28 who consented, 13 were male (46%), 15 female (54%), and 21% non-white (3 Asian, 2 Hispanic, 1 Black). Of the 19 PIs, 9 were Professors (47%), 5 Associate professors (26%), and 5 Assistant professors (26%). The additional 9 interviewees were CRCs. Select themes with representative quotes and proposed actions can be seen in Table. Conclusions: Recommendations for CCT accrual include accelerating efforts to address workforce diversity gaps, engaging in community outreach, optimization of CCT participation through collaborative care, incentivizing trial participation, and creating flexibility in eligibility criteria.[Table: see text]
Proposing a social determinants of health (SDOH) EMR dashboard to improve heath equity in cancer care.
Authors: Raez Luis E. , Puga Monica E , Thompson Terri , Feinberg, Meredith , Guerrier Vedner , King Kelly , Hunis Brian , Blandon Kimberly
Published: June 2022

e18548

Background: There are biological differences in the clinical outcomes of Black or Hispanic cancer patients compared with non-Hispanic Whites (NHWs); however minorities have disadvantages in social determinants of health (SDOH) that influence cancer outcomes too. The World Health Organization defines SODH as the conditions in which people are born, grow, live, work, age, and maintains that they are largely responsible for health inequities . Most the oncology professionals do not consider that this issue is necessarily part of their scope of practice and they rely on social workers and others to address these issues, and they are not aware that SDOH can impact clinical outcomes of cancer patients. Methods: Memorial Cancer Institute (MCI) part of the Memorial Healthcare System (MHS) is the 3rd largest Public Health Care System in the country. We found important disparities in immunotherapy outcomes in our MCI minority lung cancer patients ( Raez LE. Research Trends. 2021 Feb (20) 63–74 and Dickson F. JTO Vol. 16 (10) S904–5), some of these are related to SDOH. In order to increase awareness of SDOH and identify the impact of SDOH on cancer outcomes, our MHS value-based care team has been working to incorporate SDOH screening and follow-up as an important part of treatment plan development since 2018. At that time, MHS implemented an SDOH dashboard in our EPIC EMR to show the SDOH areas of risk. In 2021, MHS built a best practice alert in Epic to notify health care providers about SDOH issues that might impact treatment outcomes. Results: MHS has implemented a SDOH dashboard in the EPIC EMR that is accessible and easily noticed by the providers and updated constantly by our social workers and other health professionals screening for SDOH. Providers do not need to do extra work other than to be aware that the best cancer treatment that they are recommending for a patient might not have the desired outcome if some of these 13 SDOH are not considered during the planning phase of treatment. The SDOH dashboard uses color coding to indicate if any SDOH is at risk (red) or not at risk or low risk (green) allowing the provider to easily focus in on areas of concern when SDOH is reviewed. Conclusions: Using an easy to access and easy to read SDOH dashboard in the EMR allows oncology providers to address SDOH in the development of oncology treatment plans which we believe will lead to improved health care outcomes.[Table: see text]
The impact of COVID-19 and armed conflict on cancer care in Armenia: A cross-sectional study.
Authors: Margaryan Yeva , Hambardzumyan Liana , Aghabekyan Tigran , Kalemkerian Gregory Peter , Danielyan Samvel , Muradyan Armen , Tamamyan Gevorg , Arakelyan Stella
Published: June 2022

e18551

Background: The COVID-19 pandemic has interrupted the spectrum of cancer services, exposing vulnerable cancer patients to significant risks. In Armenia, the negative effect of the pandemic was amplified by the Nagorno-Karabakh war in September-November 2020. We explored the combined impact of the COVID-19 pandemic and armed conflict on cancer care provision in Yerevan, Armenia. Methods: We carried out a cross-sectional survey among all oncologists, nurses, and clinical residents (n = 123) actively providing cancer care to adults and children since 2019 at three publicly-funded institutions in Yerevan, Armenia, namely the National Center of Oncology, Hematology center after prof. R.H.Yeolyan, and Mikaelyan Institute of Surgery. Data collection was conducted between November 1 and December 27, 2021. The survey included 71 items assessing institutional characteristics, COVID-19 diagnoses, disruptions to care, adaptations of care, and availability of human and material resources. Descriptive statistics were used to analyze responses from 89 participants (72%). Results: Disruptions to cancer care during the COVID-19 pandemic were reported due to staff absenteeism (16%) and lack of access to cancer treatment [chemotherapy (14%), radiotherapy (7%), surgery (7%)], elective surgery (27%), intensive care services (10%), diagnostic examinations (3%), and inpatient beds (6%). Shortages of clinical staff for pediatric cancer care were noted by 40% of respondents and were mainly attributed to COVID-19 infection (53%) or self-isolation due to testing positive for COVID-19 (25%). Half of the respondents reported suboptimal cancer patient care and outcomes (e.g. delayed diagnosis and treatment, complications of treatment, elevated mortality rates) caused primarily by the de-prioritization of cancer services during the COVID-19 pandemic. The main issues reported by the respondents during the armed conflict were delays in elective surgery (36%) and staff shortages (17%). Confirmed cases of COVID-19 among patients were reported by respondents as: < 10 (by 6% of respondents), 11-50 (36%), 51-100 (27%) and > 100 (7%). Ten respondents (11%) reported that colleagues had died after contracting COVID-19. Twenty-six percent of respondents reported that the overall rate of hospitalizations decreased during the pandemic and 12% reported increased use of telemedicine. Reductions in material resources were reported by 18% of respondents, while 15% reported funding cuts to their unit by the institution. Conclusions: The COVID-19 pandemic and concurrent armed conflict led to disruptions in cancer care in Armenia, resulting in suboptimal care and outcomes for cancer patients. These findings emphasize the need for proactive planning to maintain standards of cancer care delivery in times of societal crises.
Geographical distribution of prostate cancer clinical trials across the United States.
Authors: Amisha Fnu , Singh Sunny R K , Malik Paras , Kumar Amudha , Konda Manojna , Kakadia SunilKumar , Malapati Sindhu Janarthanam
Published: June 2022

e18561

Background: Prostate cancer is the second leading cause of cancer-related mortality among males in the United States after lung cancer. Among other factors, physical access to clinical trial site plays a pivotal role in the recruitment process and hence impact outcomes. We aim to study the geographical distribution of phase III and IV prostate cancer clinical trials in the United States. Methods: The United States Cancer Statistics Data Visualisation Tool was utilised to estimate the number of new cases of prostate cancer for the latest available years i.e., 2014-2018. An extensive search was carried out at ClinicalTrials.gov registry using advanced search fields – disease (prostate cancer), sex (male), study type (clinical trial), phase (III and IV), country (United States) and study start (from 01/01/2014 to12/31/2018). The trials which were terminated, withdrawn, or suspended were excluded from the study. Both these tools were further explored to provide state-wise distribution of new trials and cases. Results: Between 2014-2018 in the United States, 997, 454 new prostate cancer cases were reported and 59 phase III & IV clinical trials were made available across 51 states. The average number of new prostate cancer cases and trials per state was 19,558 and 17 (range 45-0) respectively. The states with maximum reported number of new cases were California, New York, Florida, and Texas. These accounted for 30.2% of total cases and only 15.5% of total trials. The states with least reported new cases were Alaska, Vermont, Wyoming, and North Dakota. These accounted for 0.84 % of total cases and 2% of total trials [Table]. The states with the minimum number of trials per case were Mississippi (0.00035), Texas (0.00041), Florida (0.00042), New York (0.00045) and California (0.00047) whereas the states with maximum number of trials per case were Alabama (0.2352), District of Colombia (0.0061), Alaska (0.0054) and Vermont (0.0024). Conclusions: Variation in the availability of phase III and IV clinical trials for newly diagnosed prostate cancer cases was noted across 51 states of the US during the study period from 2014-2018. The states with higher disease burden had a much lower ratio of trials available per case despite higher absolute number of clinical trials in comparison to the states with lower disease burden. This highlights the need for better geographical allocation of clinical trials in the future based on the cancer burden for efficient resource utilisation and improved healthcare delivery.[Table: see text]
Characterization of remote second-opinion oncology patients and associated changes in management.
Authors: Shah Aadit P , Shi Siyu , Shah Sumit
Published: June 2022

e18563

Background: The utilization of virtual second opinions in oncology has increased considerably in the last decade, driven by the increased complexity of care and desire for expert opinion, improved technologies in telemedicine, and the acceleration of virtual services due to the Covid-19 pandemic. Therefore, it is important to further understand the patient populations that currently use virtual second opinion programs and to measure their effectiveness. Virtual second opinion programs provide a platform for patients to submit their medical history and questions regarding their condition to remote specialists who then render their opinions on diagnosis and management. Currently there is a paucity of research on the types of patient populations that seek second opinions and the outcomes of these rendered opinions. Here we describe the patient characteristics and changes in management associated with utilization of a virtual second opinion service at an academic medical center. Methods: In this IRB-approved retrospective review, we identified 657 cancer patients that utilized a virtual digital health platform to engage in second opinions at Stanford Healthcare. Patient demographics, cancer staging, site of origin, and prior therapeutic and surgical history were collected. Physician opinions rendered were self-classified into “major change in treatment”, “minor change in treatment”, or “no change in treatment.”. Results: The majority of patients who utilized the virtual second-opinion platform had a diagnosis late-stage cancer (with 77.2% at Stage III or IV). Breast cancer was the most common primary tumor site (24.7% of patients) followed by GI (21.9%) and GU malignancies (14.0%). Patients diagnosed with dermatological (4.4%), head and neck (3.3%), and neurological (3.2%) malignancies were least common. Physicians providing the virtual second-opinion were primarily medical oncologists (67.6%), followed by gynecologists (6.8%), urologists (5.2%), radiation oncologists (5.0%), and surgical oncologists (4.4%). Physicians self-reported that in more than half of cases reviewed (53.8%) a minor or major treatment change was recommended. Conclusions: This study showed that patients access second opinion platforms at late stage of cancer disease progression. With treatment changes recommended for more than half of the cases, virtual second opinion programs can potentially have a significant impact on cancer care. Patient satisfaction and clinical outcomes from virtual second opinion programs is an area of on-going research.[Table: see text]
Telephone medical consultation during the COVID-19 pandemic in Mexico.
Authors: Torres-Cisneros Eduardo Rey , Bruni-Guerrero Carla Renata , Martínez-Valenciano Juan Manuel , Najera Rubi Janday , Reyes Mondragon Alan Ledif , Rodríguez-Rodríguez Yuridia Evangelina , Guerra Cepeda Abraham , González-Gutiérrez Adriana , Martinez-Granados Rolando Jacob , Rodríguez-Moreno Catalina , Hernández-Barajas David , Vidal-Gutiérrez Oscar , Salazar-Mejía Carlos Eduardo
Published: June 2022

e18564

Background: Telephone consultation has emerged as an alternative method for outpatient medical follow-up during the COVID-19 pandemic, reinforcing the necessary distancing measures. However, there are multiple factors that the medical team must contend with, which could limit the monitoring of patients. Methods: We retrospectively analyzed the remote medical consultation database of a university-based oncology referral center in northeast Mexico. The telephone calls were made from the medical center by specialized health personnel. The data obtained correspond to the monitoring conducted over six months. Results: We included 1,140 patients in the analysis, of which 79% were women and 21% were men; the median age was 55 years. All individuals had a pathology-confirmed diagnosis of cancer. The main oncological diagnoses were breast, cervix, and prostate cancer which corresponded to 46, 13, and 7% of the cases, respectively. Ninety-four percent of cases corresponded to cancer surveillance, while the remaining 6% were receiving active oncological treatment, administered orally. Ninety-three percent of the patients were from the city of Monterrey and its metropolitan area, 6% came from the rest of the municipalities of the state of Nuevo Leon, and 1% were from other states of the Mexican Republic. Ninety-eight percent of the patients had a public health insurance as a method of coverage for health services, while 2% received care through private health insurance. At remote follow-up, only 53% of the patients responded to the telephone calls, none of them reported a diagnosis or any symptom of SARS-CoV-2 infection. Among the 536 patients who had a telephone communication failure, 68% did not respond to the call after 4 attempts, while in 32% of these cases the number provided by the patient was incorrect or non-existent. Conclusions: The high rates of failure to establish telephone communication documented in our population of patients with cancer is a worrying phenomenon. As the COVID-19 pandemic progresses worldwide, we must seek to establish measures to optimize logistics for more effective remote communication, to achieve the best possible outcomes.
Increasing colorectal screenings with navigation at federally qualified health centers.
Authors: Anderson NaSheema
Published: June 2022

e18566

Background: From 2017 to 2019 there were a total of 423 federally qualified health center colonoscopy referrals (FQHC's) and only 81 (19%) patients followed through and had colonoscopies completed, identifying a significant gap in cancer care within an at risk populations. Methods: The Community Outreach team used a team based problem solving tools and data analytics to increase the number of patients who received colon screenings from FQHC’s. The team held brief, weekly huddles using a variety of continuous improvement tools to identify possible causes of the problem. The team identified 14 potential causes of the 19% gap in FQHC referrals to colonoscopy screenings. The potential causes were analyzed and 4 were identified as the root cause and grouped by common themes into the following opportunities for improvement: Poor engagement with FQHC's. Lack of knowledge on FQHC healthcare effectiveness data and information sets. No standardized workflow for FQHC referrals within the navigation process. Inefficient process for filling the number of screening appointment slots. After identifying the key potential causes, the team developed a task list with countermeasures for improvement and met weekly until the tasks were completed. Through root cause analysis the following key countermeasures were identified: Countermeasure 1: Increased engagement through weekly calls and monthly in person meetings at FQHC's. Countermeasure 2: Developed a quarterly newsletter for FQHC's to review colonoscopy referrals and completed screenings. Countermeasure 3: Developed and implemented a standardized process flow for receiving referrals from FQHC's. Countermeasure 4: Worked with the analytics team to create a dashboard to analyze the real time referrals and completed screenings along with sending e-mail notifications to the navigation program manager providing daily visual management of the number of new patient referrals from FQHC's. Results: After implementing the countermeasures, the community outreach team improved the number of FQHC referrals, from 423 in January of 2017 thru January 2019 to 1399 from January 2020 of December 2021.This was a 160% improvement. They also increased the number of completed colonoscopies from FQHC's from 81 in January of 2017 thru January of 2019 to 328 in January of 2020 thru December of 2021. This was a 200% improvement. The completed screening rate is 23% up from 18%. Conclusions: This project demonstrates the value of utilizing problem solving, visual management and data analytics for continuous quality improvement projects related to patient care. Cross-disciplinary collaboration should be explored with the use of visual tools and other resources to facilitate communication that is understood by all disciplines. The use of patient navigation to schedule patient screening appointments, reminders calls and resolved barriers improved no show rates.
National and local racial disparities in triple-negative breast cancer (TNBC) survival: Local outcomes counter the myth of national averages.
Authors: Abbass Ibrahim M. , Roth Joshua A. , Jinnett Kimberly , Zimmerman Veronica , Cassoli Lourenia
Published: June 2022

e18588

Background: Real-world studies comparing racial differences in overall survival (OS) outcomes between African American (AA) and White (W) patients (pts) with TNBC have yielded mixed findings. This exploratory study assessed differences between national and county-level OS estimates-comparing AA vs. W pts, and identifying counties with greater racial disparities for future research. Methods: This retrospective cohort study used the Surveillance Epidemiology and End Result (SEER) cancer registry to assess county-level OS among non-hispanic AA and W pts ≥18 years of age who were diagnosed with TNBC 2011-2016. Counties with low levels of racial diversity (< 30 AA or W TNBC pts) were excluded. Five-year OS was evaluated using Kaplan-Meier and multilevel parametric OS models with a Weibull distribution. By county, OS differences between AA and W pts were tested using linear hypothesis tests after model estimation. OS models were adjusted for age at diagnosis, year of diagnosis, marital status, insurance type, surgery type, stage, grade and metastasis at brain, bone, liver and lung. Results: Among 46,125 TNBC pts in SEER, 15,723 pts (33.4% AA, 66.6% W) residing in 8 States and 47 Counties met inclusion criteria. W pts were older (mean 60; ∓14 vs 57∓13 for AA) and more likely to be married (57% vs 33%), insured (49% vs 45%) and diagnosed at an earlier stage (stage I 37% vs 29%). Controlling for potential confounders, AA pts were more likely to experience 5-year mortality compared to W pts (Hazard Ratio [HR] = 1.16; 95%CI = 1.07, 1.26). Among 47 included counties, only 4 counties demonstrated a statistically significant 5-year OS racial disparities after adjusting for confounders. The difference in HRs between AA and W pts in these 4 counties ranged from 1.49 to 2.26 as depicted in the result table (p value < 0.05). Removing these 4 counties (n = 2,929) from the final analytic cohort yielded statistically non-significant estimates (HR = 1.06; 0.97,1.16). Conclusions: There is clinically meaningful OS variation between AA and W pts with TNBC across U.S. counties included in SEER. Measuring disparities at the national or state level may mask important OS disparities at the county level. Using a county-level analytic approach, we were able to identify localities that disproportionately contribute to OS disparities at the national level. Our findings will facilitate better targeting of local interventions to address TNBC racial disparities. Future analyses should also assess counties excluded (n = 13,032) for small population sizes and/or low levels of racial diversity, as well as states not represented in SEER.[Table: see text]
Disparities in clinical trial participation in ovarian cancer.
Authors: Smith Anna Jo Bodurtha , Alvarez Rafael , Heintz Jonathan , Simpkins Fiona , Ko Emily Meichun
Published: June 2022

e18597

Background: Across cancers, significant racial disparities exist in clinical trial enrollment. Our objective was to examine the association of trial enrollment with sociodemographic and health system factors in ovarian cancer. Methods: We conducted a retrospective cohort study of patients with ovarian cancer diagnosed from 2013-2021 using the nationwide de-identified electronic health record-derived Flatiron Health database. We used multi-level regression modeling to analyze the association of clinical trial participation (receipt of a clinical trial drug) with patient, sociodemographic, health system, and cancer factors. Results: Of 8,022 patients with ovarian cancer, 5.0% (95%CI 4.5-5.5) received a clinical drug trial. Medicaid insurance, Hispanic or Latino ethnicity, non-white race, and advanced age were associated with lower trial participation, while residence in the Southeast, advanced-stage, and recurrence were associated with higher participation. Race and insurance disparities persisted in both academic and community settings. Conclusions: In this large cohort study of ovarian cancer, Hispanic/Latino patients and those on Medicaid were significantly less likely to participate in clinical trials. Efforts to increase clinical trial diversity are needed.[Table: see text]
The association of social and demographic factors on the time interval between a suspected diagnosis of cancer, diagnosis, treatment, and outcomes in a lung cancer patient population.
Authors: Ajrouch Ali , Jennewein Laura , Li Yang , Pike Francis , Hanna Nasser H.
Published: June 2022

e18598

Background: Delays in lung cancer (LC) diagnosis and treatment adversely affect patient outcomes. Prior studies report mixed results on the association between delays in diagnosis and various demographic factors. Methods: A retrospective cohort analysis was conducted utilizing a randomly selected subset of LC patients treated at the IU Simon Comprehensive Cancer Center between 1/1/18 and 12/31/20. Chart search identified the dates of first suspected cancer finding (SCF; imaging or high-risk presentation), diagnosis, first treating physician contact, and treatment initiation. Patient characteristics (sex, age, race, marital status, insurance status/type, employment status, smoking status, LC stage, LC type) and healthcare utilization (setting of SCF, modality used to discover SCF) were also collected. Asymptomatic patients with SCF at routine screening were excluded. Multivariable Cox proportional hazards and logistic regression models were utilized with significance defined as p < 0.05. Results: Patient characteristics (n = 203): white 86.7%; ever smokers 86.0%; Medicare 61.3%; NSCLC 87.7%; stage IV 44.3%. SCF was primarily identified in an ambulatory setting (57.4%) by CT imaging (62.1%). Median time from SCF to diagnosis, treating physician contact, and treatment were 24d (IQR: 8-67), 24.5d (IQR: 9-54), and 57d (IQR: 28-98), respectively. Median time from diagnosis to treatment was 22d (IQR: 7-41). Time from SCF to LC care was significantly associated with cancer type (median times - diagnosis: NSCLC = 27d, SCLC = 9d, p = 0.001; treating physician contact: NSCLC = 27d, SCLC = 6d, p = 0.002; treatment: NSCLC = 66.5d, SCLC = 23d, p < 0.001), stage (median times - diagnosis: stage I = 52d, stage IV = 9d, p < 0.001; treating physician contact: stage I = 32.5d, stage IV = 13.5d, p = 0.008; treatment: stage I = 97d, stage IV = 23d, p < 0.001), and setting of SCF (median times - diagnosis: ambulatory = 30d, emergency = 7d, p < 0.001; treating physician contact: ambulatory = 31d, emergency = 9d, p < 0.001; treatment: ambulatory = 74.5d, emergency = 28d, p < 0.001). Risk of delays were highest among those with Stage I NSCLC and when SCF occurred in the ambulatory setting. Adjusted by cancer types and modality, patients presenting to the ER were 2.15 times more likely to be diagnosed with stage IV disease than those presenting in the ambulatory setting (p < 0.001). Conclusions: Streamlined transitions of care are needed in the ambulatory setting to reduce delays in LC diagnosis and treatment to optimize patient outcomes. The extended delays experienced by early vs late-stage LC patients may be explained by access to care. However, no demographic factors (insurance, age, race) were significantly associated with delays in this dataset. Further studies are needed to assess the timeliness of cancer diagnosis and treatment in large, diverse populations.
Assessing feasibility and utility of an implicit bias training program for addressing disparities in cancer clinical trial participation.
Authors: Barrett Nadine , Boehmer Leigh , Schrag Janelle , Benson Al Bowen , Green Sybil , Hamroun Leila , Howson Alexandra , Matin Khalid , Oyer Randall A. , Pierce Lori J. , Jeames Sanford Earl , Winkfield Karen Marie , Yang Eddy Shih-Hsin , Zwicker Victoria , Bruinooge Suanna Steeby , Hurley Patricia A. , Hanley Williams Jen Hanley , Guerra Carmen
Published: June 2022

e18599

Background: Low participation of Black, Hispanic, Latinx and other underrepresented racial/ethnic groups in clinical research remains a problem across the U.S. Recent studies have highlighted that stereotypes, assumptions, and bias play a role in lack of diversity in cancer trial participation. To help address this, the Association of Community Cancer Centers (ACCC) and American Society of Clinical Oncology (ASCO) piloted an implicit bias training program for clinical research teams. Methods: Adapted from the Duke University Just Ask™ program, the pilot program is comprised of eLearning modules which can be completed in about 60 minutes. Features include education on diversity, equity, and bias in clinical trial participation, case vignettes, and strategies to mitigate disparities. A call was issued to members of both organizations. After completing the training, all individual participants were asked to complete a retrospective pre/post survey to assess change in knowledge and attitude. Focus groups explored participants’ experience with the training. Another survey was administered 6 weeks later to assess sustainability of changes. Results: Research teams from 50 programs were selected for the pilot. 129 individuals consented, and 126 completed the training and evaluations (98% response rate). 48% of participants reported that they had completed training on implicit bias and/or related topics prior to the pilot. Increased levels of knowledge were reported across all key training concepts, with an average % increase from 19% to 45%. Similar increases were observed for strategies for addressing implicit bias, with an average % increase from 10% to 31%. At 6 weeks post-training, there was a slight decrease in knowledge across most items, from -1% to -8%. Most (92%) participants reported satisfaction with the course, and most (92%) indicated they would recommend it to a colleague and would recommend implementing it at their program. Suggestions to improve the course included streamlining content and providing additional tools and resources. Conclusions: Pilot findings support the feasibility and utility of the training, which can help cancer programs to address disparities in clinical research. Next steps include modifying the course based on participant feedback, disseminating the training and supplementary resources, and exploring options for assessing the impact on upstream outcomes such as diversity in trial participation.[Table: see text]
Predictive factors for cancer treatment delay in an underserved urban population.
Authors: Sheni Risha , Qin Jiyue , Viswanathan Shankar , Castellucci Enrico , Mehta Vikas
Published: June 2022

e18608

Background: Incremental delays in cancer time to treatment initiation (TTI) have been shown to cause a proportional, independent increased risk of disease specific mortality for breast cancer, colorectal cancer (CRC), head and neck (HNC), non-small cell lung cancer (NSCLC) and pancreatic cancer. A portion of delays can be attributed to increasingly complex workup with modern imaging, genomic, and multidisciplinary/multimodality treatment paradigms. However, studies suggest delays are associated with racial and socioeconomic disparities, implicating a target for addressing inequitable care. Given Montefiore Medical Center (MMC) serves a racially diverse, socioeconomically challenged population, we sought to evaluate the association between patient factors and TTI to identify factors associated with TTI delay. Methods: Retrospective cohort study at an urban community-based academic center of patients diagnosed with or referred for curative intent treatment of breast cancer, CRC, HNC, NSCLC, and pancreatic cancer at MMC from January 2019 to December 2021. Variables of interest included tumor staging, primary treatment modality, marital status, Charlson Comorbidity Index (CCI) score, tobacco use, zip code, insurance type, language preference, primary care provider status, and inpatient (IP) admission or emergency room visit 30 days prior to diagnosis. Results: A total of 3430 patients (F=2376, M=1054) were identified (mean age 64.2 ± 13.3). Demographics are summarized in Table. The Median TTI was 21 days (7, 41 IQR). In assessing factors associated with TTI delay, patients who were IP 30 days before diagnosis were significantly more likely to have timely TTI for breast cancer (p<0.003), CRC (p<0.001), HNC (p<0.006), and NSCLC (p<0.001). For CRC, a higher CCI score was associated with TTI greater than 30 days (p<0.019). For lung cancer, older age (p<0.015) and having public insurance (p<0.001) were associated with TTI delay. Conclusions: IP admission 30 days before diagnosis was associated with timely TTI for breast cancer, CRC, HNC, and NSCLC. Other factors predictive of delay included CCI score in CRC, and advanced age at diagnosis and insurance type for NSCLC. This study identifies factors predicting delay and opportunities for addressing delay, thereby improving survival outcomes in our population.[Table: see text]
Using a clinical trial schedule of assessments (SOA) as a quality improvement tool.
Authors: Paul Varun , Ferranti Lori , Dilts David M.
Published: June 2022

e18638

Background: The SOA is a key part of any clinical trial as it highlights activities to be performed during trial execution. Such a schedule provides a roadmap and calendar of tests, measurements, and evaluations. Normally, such a schedule is created after a protocol has been mostly created. Our aim is to demonstrate that the SOA can have a broader usage: that of a quality improvement (QI) tool used during protocol creation, thus helping to ensure a high-quality protocol at the design. When creating a protocol conflicting uses of the Protocol contribute to operational tension. For example, Trial Operations, which wishes to minimize the complexity of the trial, may debate with Clinical Science, who wish to collect the greatest amount of scientific tests and data. The more complex a set of requirements in the protocol, there is a corresponding drop in available sites able to meet those needs. Additionally potential sites may comment about being burdened with tests that are unnecessary to the core protocol aims, thus creating unnecessary delays in the trial. All these issues may be addressed by using the SOA as a QI tool. Methods: This research was completed at a major, international pharmaceutical organization for a Phase III oncology clinical trial. A team was created composed of: Clinical Scientist Lead , Stats/Data Lead, Trial Operations Led, Medical Monitor, Medical Leader, and Lean Expert. Methodologically, this was led by the Lean Expert and each team member was sent an electronic version of a draft SOA for review. They inserted questions and comments that were visible to the entire team. After this, an SOA issues log was created in an SOA tracking system. This system categorized and ranked issues for discussion by the entire team during the creation process of both the SOA and the protocol. The process used a “House of Quality” framework, allowing for the aggregation of protocol requirements so that they could be addressed in total, rather than individually. Results: The process was successful in 3 critical dimensions. From a time metric, the SOA was produced 3 to 6 months faster, enabling numerous efficiencies such as providing the development team with information both faster and at the time the team was creating the final protocol. Second, from an economic standpoint, the labor efficiency of the trial was improved as it required 33% less individuals to produce the SOA and protocol resulting in a protocol at record speed. Finally, protocol quality was increased as in this method the team worked jointly together, nearly simultaneously, to complete both the SOA and the protocol. This reduced the number of Protocol Amendments by 50%. Conclusions: Using this method, there was an increase in quality, a reduction in cost, and a faster time to the sites. This reduced the commercialization timeline by 3-6 months which is a significant cost savings. But most importantly, this allows for better treatment faster to be in the hands of oncologists to treat patients.
Regional block pilot for microvascular free-flap breast reconstruction.
Authors: Kim Leah , Long Anne , Miller Jared , Zurich Holly , Golshan Mehra , Li Jinlei
Published: June 2022

e18646

Background: With increasing focus on improving patient outcomes and decreasing narcotic use, healthcare has prioritized the use of multidisciplinary, multimodal, and evidence-based approaches to perioperative management through enhanced recovery after surgery (ERAS) pathways. Currently, microsurgical breast reconstruction with or without concurrent mastectomy commonly may employ regional anesthesia in the preoperative and intraoperative techniques. To optimize perioperative analgesia, an ERAS protocol was piloted at a quaternary care academic center implementing a pre-operative anesthesia placed regional block with preference for anterior quadratum lumborum blocks. Methods: A total of 161 patients were enrolled in this single center Continuous Quality Improvement (CQI) project. The project consisted of 72 baseline, 20 pilot, and 69 after pilot patients who underwent unilateral (n = 65) or bilateral (n = 96) deep inferior epigastric perforator (DIEP) flap reconstruction either immediately (n = 87) or delayed (n = 74) after mastectomy. In the 20 CQI pilot group, anesthesiologists pre-operatively placed bilateral anterior quadratus lumborum blocks (aQLB) under direct ultrasound guidance. After positively observed metrics, the official ERAS pathway was implemented into clinical practice, allowing for subsequent accrual of 69 additional patients. We compared this after pilot group to 72 baseline patients who underwent a surgeon-placed intraoperative transversus abdominus plane (TAP) block using liposomal bupivacaine. Statistics data was tracked using a dedicated clinical EMR dashboard. Baseline patients were matched to the after pilot cohort based on laterality and timing of DIEP flap reconstruction. Results: The ERAS pathway with anesthesia-placed aQLB was associated with lower post-operative daily opioid consumption from 27.2 MME to 10.2 MME. Average pain scores, post-anesthesia care unit (PACU) length of stay, hospital length of stay, as well as re-admissions and complications were not statistically different before and after the implementation of the ERAS pathway. Conclusions: Anesthesia placed pre-operative aQLB is a safe and effective opioid-reducing pain control modality for DIEP flap reconstruction with or without mastectomy. Prospective and controlled studies will be important for the precise impacts of aQLB in DIEP procedures in an ERAS protocol.[Table: see text]
LUNG cancer: Supportive oncology program development for patients and care partners: A qualitative study.
Authors: Beeler Dori Michelle , Mileham Kathryn Finch , York Beth , Szafranski Michele , Walsh Declan
Published: June 2022

e18652

Background: Lung cancer patients (LCP) have various unmet needs. Evidence supports tailored services to provide individuals information and interaction with healthcare professionals (HCP). We conducted a qualitative study of the ideal supportive care services and structure for LCP and care partners (CP) within Levine Cancer Institute, a regional, multi-site cancer system. Methods: Methods included Focus Groups (FG) and a paper-based survey (PBS) in the Section of Thoracic Oncology. FG included HCP, local Lung Cancer Support Group leadership, LCP, and their CP. FG identified important topics for LCP, CP, and HCP. FG recordings were transcribed, analyzed, and incorporated with the evidence base to inform PBS development. LCP and CP participated in the PBS and responses analyzed with REDCap (v11.1 11, ©2022 Vanderbilt). FG and PBS data were compared for overlap and discordance. Results: FG (total N = 18) identified four Themes: 1) unmet needs 2) program structure 3) barriers to care 4) program content; each analyzed further into three codes (Table). FG Themes are presented in order of frequency (FQ) of unique comments. Unmet needs (FQ=25) included: loneliness, care for the CP, onboarding burden. Structure (FQ=24) included: innovation, variability, virtual. Barriers to care (FQ=20) included: seeking/needing knowledge, transportation, psychosocial. Content (FQ=18) included: combined content and services, financial, educational. Among the responses (total n = 44), strong overlap existed in six PBS areas. Most agreed on seeking/needing knowledge and psychosocial barriers. The majority agreed with combined content and services and the importance of financial and educational content. Variability was specified by agreement on printed and patient portal digital materials with a moderate preference for virtual meetings. Discordance was found across loneliness and transportation while care for the CP, onboarding burden, and innovation were neutral or irrelevant. Conclusions: FG findings confirmed unmet needs, program structure, barriers to care, and program content as integral LCP and CP program concerns. Identified overlap between these Themes and PBS responses are addressed in the ideal LCP and CP support program. This methodology can be generalized to guide future program development to serve other populations and cancer institutes. [Table: see text]
Visualizing meaningful change in small sample sizes.
Authors: Iaconangelo Charles , Serrano Daniel , McManus Shauna
Published: June 2022

e18656

Background: Patient Reported Outcomes (PROs) are included in trials to incorporate patient voice into the drug development process. In oncology, PROs typically evaluate patient physical function and/or symptom burden. Clinicians need to be able to describe expected patient outcomes in terms of meaningful change in conversations with patients. FDA guidances outline analysis methods for measuring meaningful change, and the results are increasingly used to inform regulatory decisions and in drug packaging. Improving best practices in measuring meaningful change is crucial for regulatory review and to help clinicians communicate effectively with patients. Current best practice under FDA guidance is to compute meaningful within-patient change (MWPC) using an anchor-based approach. The relationship between change scores and anchor groups is visualized via empirical cumulative distribution functions (eCDFs). However, when sample sizes within anchor groups are small, it may be difficult to compute the distribution function. In contrast, a scatterplot approach does not require any computation. The objective was to evaluate under what study conditions (i.e., sample sizes and magnitude of meaningful change) would it be advantageous to interpret meaningful change with a scatterplot approach. Methods: Data simulated to emulate real PRO data from a trial, including attrition due to death, were used to highlight shortcomings in current practice and propose a robust alternative. A simulation study permitted a variety sample sizes and magnitudes of meaningful change to be evaluated. The eCDF was implemented in accordance with current guidance and compared to scatterplots. The scatterplot approach was operationalized as follows: the subject scores were plotted with the baseline scores on the x-axis and the follow-up scores on the y-axis. The scatterplot was stratified by color to represent anchor group-specific scores. Subjects who did not respond at follow-up due to progression or death were plotted in a separate color, using the baseline response and an assigned follow-up score reflecting maximum severity. A 45-degree line represented No Change. The vertical distance between the subject score and the 45-degree line represented the observed change. Results: When sample size was below n = 10 subjects per anchor group, the eCDF yielded uninterpretable visualizations. At sample sizes n = 1-20 per anchor group, the scatterplot approach consistently yielded interpretable visualizations of meaningful change. Conclusions: The scatterplot approach avoids methodological complications and thus ensures transparency in the evaluation of meaningful change. Recommendations to supplement current best practice with the scatterplot approach described above should be considered.
Development of a predictive model for emergency room utilization and unanticipated hospital admission in patients receiving cancer treatment for solid tumor malignancies.
Authors: Watson Catherine , Alhanti Brooke , Zhao Congwen , Havrilesky Laura J , Davidson Brittany Anne
Published: June 2022

e18674

Background: Unanticipated healthcare resource utilization, in the form of either emergency department utilization (EDUs) or hospital admission (HA), is an indicator of lower quality of cancer care. The objective of this study was to develop a comprehensive predictive model for emergency department utilization and hospital admission (HA) for patients with solid tumors who received chemotherapy within 30 days. Methods: We abstracted electronic health data on oncology encounters from all patients receiving systemic therapy chemotherapy for solid tumors from March 01, 2015 to August 21, 2020. Patients included in the cohort met the following criteria:1) Ages > = 18 years old 2) Diagnosed with any solid tumor (3) Had any oncology treatment plan related to their solid tumor diagnosis; 4) Received at least one chemotherapy during March 01, 2015 through August 21, 2020. We defined a primary composite outcome of emergency visit or unanticipated hospitalization within 30 days after the encounter. Patient information was abstracted. We developed a predictive model for the primary outcome using LASSO logistic regression modeling. To evaluate the model, we calculated the Area Under the Receiver Operator Characteristic (AUROC) and the calibration slope. Results: 12,917 unique patients with 134,641 encounters were included. Of these, 9100 (6.7%) of encounters were ED visits or hospitalizations. 714 patients (5.5%) had at least one ED visit or hospitalization within 30 days of treatment; patients at highest risk for this outcome included those with pancreatic cancer, lung cancer and ovarian/endometrial cancer (9.1%, 7.4% and 6.8% respectively). 38 variables were identified as contributing to the LASSO model. The top predictors, in order of importance, were fever, hypernatremia, hypotension and low albumin. The model’s AUC was 0.83, indicating good model sensitivity to outcome. Conclusions: Approximately 7% of healthcare encounters in patients undergoing treatment for solid malignancies were ED visits or hospitalizations. Identifying patients at highest risk for this outcome may prevent unnecessary resource utilization and optimize patient care during cancer treatment. The model developed in this study demonstrated good sensitivity and could be implemented in clinical practice to allow for preventive outpatient interventions. Work is ongoing to integrate this model into clinical care at our institution.[Table: see text]