bluuebunny/crossref_metadata_2025 huggingface dataset:
A single-institution and commercial laboratory database analysis of BRIP1-associated cancer risks.
Authors: Whitaker Kristen Danielle , Bernhisel Ryan , Kidd John , Hughes Elisha , Rosenthal Eric Thomas , Hall Michael J.
Published: May 2020

1538

Background: BRIP1/ FANCJ participates in DNA replication and repair via interactions with BRCA1 and possibly MLH1. Previous studies have reported that pathogenic variants (PV) in BRIP1 are associated with an ~2-fold increase in risk for ovarian cancer (OC) and triple-negative breast cancer (TNBC). Although multigene panel testing for hereditary cancer (CA) has identified BRIP1 PV and uncertain variants (VUS) in patients with diverse CAs including breast (BC), colorectal (CRC) and melanoma (Mel), association with these CA types has not been established. Methods: We examined BRIP1 risks in two independent populations: Fox Chase Cancer Center (FCCC) and Myriad Genetics (MGL). At FCCC, pedigrees of BRIP1 PV ( N= 10) and VUS families ( N= 47) were reviewed. The MGL population included patients referred for testing by multigene panel (9/2013-12/2019) ( N= 586,740). Multivariable logistic regression analysis estimated BRIP1 CA risks as odds ratios (ORs) and 95% confidence intervals (CIs). Models were adjusted for age, sex, ancestry, personal CA history (PHX), and family CA history. Results: In the FCCC cohort, BRIP1 PV carriers ( N= 12) reported PHX of early-onset ( < 50) BC, CRC, and bladder CA. BRIP1 VUS were also identified among several patients with striking PHX and negative panel testing: BC < 40 ( N= 3), bilateral BC ( N= 4), TNBC ( N= 2), CRC < 40 ( N= 3), and a patient with 3 CAs < 40 (CRC, BC, and Mel). All FCCC families with a BRIP1 PV and select VUS families ( N= 6) are seen in the Table. In the MGL population, 0.3% (1,678/586,740) carried a BRIP1 PV. Logistic regression analyses found that female BRIP1 PV carriers have significantly increased risk for OC (OR 2.40, 95% CI 1.93-2.98) and TNBC (OR 1.93, 95% CI 1.52-2.46). Data were insufficient for testing risk of bladder or prostate CA. Findings did not support associations of BRIP1 with CRC, melanoma, endometrial, pancreatic or gastric CA. Conclusions: BRIP1 PV and VUS may be identified in patients with diverse CA histories. These results confirm studies showing that BRIP1 PV are associated with an ~2-fold increased risk of OC and TNBC, but do not support increased risks of CRC, melanoma or endometrial CA in BRIP1 PV carriers. [Table: see text]
A comparison of patients' and physicians' expectations regarding precision oncology tests.
Authors: Dehar Navdeep , Abedin Tasnima , Tang Patricia A. , Bebb D. Gwyn , Cheung Winson Y.
Published: May 2020

1568

Background: With the increasing number and frequency of biomarker and genetic tests that are offered to patients with cancer, it is important to ensure that they fully understand the implications of these tests. In this survey study, we aimed to compare the attitudes and expectations of patients and cancer physicians about the role of biomarker and genetic testing in clinical decision-making. Methods: Two separate, complimentary, self-administered questionnaires for cancer patients and their physicians, respectively, were collected in Calgary, Alberta, Canada. Survey responses from patients were subsequently matched with those of their corresponding oncologists to form patient–oncologist dyads. We determined the concordance rates between responses of patients and those of their oncologists. Results: A total of 113 patients and 15 physicians participated in the study from July to September 2019. Patients demonstrated good understanding of general cancer biology (79%) and diagnostic processes (91%) associated with precision oncology. About 70% patients were willing to undergo minor procedures, and participate in research involving biomarker or genetic testing; however, this was over-estimated by their physicians in 82% of cases. Many patients felt that their tumor should be tested to guide treatment (70%) and were not bothered by potential delays in treatment due to testing (23%). These views from patients were largely shared by their oncologists (concordance 64%). While only 28% patients thought that they had enough knowledge to make informed decisions, majority (68%) said that they needed more information. Importantly, knowledge and expectations regarding the applications of biomarker or genetic test results on actual diagnosis and prognosis were grossly discrepant between patients and their oncologists (concordance 26% and 36%, respectively). Conclusions: Patients and cancer physicians tend to be aware of the advances in precision oncology and are willing to participate in biomarker and genetic testing and research. However, they do not consistently agree about the roles and applications of these tests, which may result in misplaced expectations. Strategies to improve education and communication are needed to align these expectations and improve the quality of clinical decision-making.
Population genetic screening for hereditary breast and ovarian cancer in at-risk patients: A novel testing and prevention model for community hospitals reveals high mutation rates rurally.
Authors: Shelton Charles Hendrix , Boehmer Leigh , Weldon Christine B. , Guenther William C. , Trosman Julia Rachel , Ruiz Antonio
Published: May 2020

1575

Background: Genetic testing for at risk non-cancer patients continues to increase (Guo F, et al Cancer 2020). We identified a high risk of familial breast and ovarian cancer in rural eastern North Carolina, and created a systematic approach for genetic screening, counseling and testing. Methods: A family history questionnaire was designed to assess for the risk for hereditary breast and ovarian cancer (HBOC) using NCCN guidelines, and used at key intake points within the unaffected population to determine eligibility for genetic testing. First it was offered at the time of all mammograms. Second, we offered it in the primary gynecology care setting to capture younger patients not participating in screening mammography. Patients meeting HBOC criteria were sent a letter and two phone calls to schedule genetic counseling. Analysis via descriptive statistics. Results: 3000 rural women screened using our systematic approach to genetic risk assessment. 22.4% (673/3000) of female patients met NCCN criteria for HBOC panel testing. All offered consultation and counseling. With a backlog to see patients due to higher than expected accrual, 217 patients have completed pre-test genetic counseling, 201 completed local 19-gene panel test, and 201 had post-test counseling. Germline mutations (=>1) that predict for genetic susceptibility to cancer(s) occur in 7.8% of our screened and tested population. Currently 1 in 400 patients screened in our unaffected population carry a BRCA mutation, and 1 in 200 carry some pathogenic mutation that increases risk for HBOC. Conclusions: This rural model of screening and prevention of at risk patients for HBOC is successful at detecting pathogenic mutations in unaffected patients before they are diagnosed with cancer. Interestingly, the rate of positivity in the unaffected population (meeting criteria) is as high as the known breast cancer population rate of germline mutations (5-10%), validating the use of testing guidelines with our model. Discovering this susceptibility before a cancer diagnosis resulted in appropriate high risk management with prevention and risk reduction strategies. We plan to expand this model to the male screening population in 2021, and streamline genetic assessment and testing for the larger population at risk by engaging more rural primary care clinics over time to increase testing compliance. We also plan to consider broader gene panels as newer mutations become linked to HBOC. Clinical trial information: UMCIRB 19-001052.
Implementation of systematic germline genetic testing (GT) for metastatic prostate cancer (mPC) patients at the Puget Sound VA prostate oncology clinic.
Authors: Sokolova Alexandra , Miyamoto Akemi N. , Pouv Darren L. , Cheng Heather H. , Montgomery Robert B.
Published: May 2020

1578

Background: There is increasing clinical relevance for GT in patients with mPC to evaluate the 2-fold possibilities of molecularly targeted therapies and implications for relatives. NCCN guidelines recommend GT for subsets of men, including those with mPC. While exciting, there are new logistical challenges around workflows for delivering GT services. We sought to address these challenges through a prospective pilot study designed to systematically deliver GT to all men with mPC receiving care at the Puget Sound VA prostate cancer (PUG-VA PC) Clinic. Our hypothesis was that systematic universal GT for men with mPC would identify similar prevalence rates of germline pathogenic/likely pathogenic variants (P/LPV) among veterans compared to previously reported cohorts. Methods: We conducted an IRB-approved, prospective trial testing feasibility of a systematic workflow to identify all veterans with mPC seen at PUG-VA PC Clinic between 11/2016-1/2020 to discuss and offer GT. A research coordinator pre-screened each clinic schedule to identify patients with mPC, notified the oncologist to discuss pretest education and GT with the patient at the appointment. Consenting patients provided a saliva sample same day in clinic for the CLIA-certified Color Genomics 30-gene cancer gene panel. Results were issued to patients and providers, and results were discussed by email and phone with a genetic counselor. Uptake of GT and prevalence of P/LPV was measured and compared to previously reported data from the retrospectively tested UW TAN cohort. χ2-test was performed. Results: 84% (190/227) of approached veterans with mPC consented and 80% (182/227) completed GT. 6.6% (12/182) of men were found to carry P/LPV in DNA repair genes: 3 in BRCA2, 2 in BRCA1, 4 in ATM, and 3 in CHEK2. Overall, 6.6% rate of P/LPV in DNA repair genes was comparable to the 8.8% previously reported in the UW TAN cohort (p = 0.69). Conclusions: Dedicated clinic-based strategies to offer and provide GT and services for veterans with mPC is feasible and results in high GT consent and uptake, especially with direct oncologist involvement. Proportion of consenting to proceed with GT was nearly identical to a referral-based specialty Prostate Cancer Genetics Clinic (Pouv, Sokolova, and Cheng, unpublished). The proportion of P/LPV in the PUG-VA PC population was comparable to a geographically similar retrospective cohort. Updated data, including detailed demographics and GT results, will be reported at final presentation.
Intervention combining nurse navigators (NNs) and a mobile application versus standard of care (SOC) in cancer patients (pts) treated with oral anticancer agents (OAA): Results of CapRI, a single-center, randomized phase III trial.
Authors: Mir Olivier , Ferrua Marie , Fourcade Aude , Mathivon Delphine , Duflot-Boukobza Adeline , Dumont Sarah Naomie , Baudin Eric , Delaloge Suzette , Malka David , Albiges Laurence , Pautier Patricia , Robert Caroline , Planchard David , de Botton Stéphane , Lemare François , Guillet Marilene , Puglisi Vanessa , Abbas May , Di Palma Mario , Minvielle Etienne
Published: May 2020

2000

Background: Various interventions aiming to improve a safe use of oral anti-cancer agents have previously been reported. These retrospective studies involved nurse-led follow-up and use of health technologies. However, the potential impact of these combined strategies is limited by a lack of rigorous methodology. Methods: We performed a randomized phase 3 trial comparing an intervention combining NNs and a mobile application vs. SOC in cancer pts treated with OAA (excluding hormonal therapy) in our tertiary cancer center. Pts initiating OAA (all types of cancer, PS < 3, life expectancy > 6 months), were randomized in a 1:1 basis. The intervention combined a nursing-led follow-up and a mobile application for patients. NNs provided regular phone follow-ups to manage symptoms and assess toxicities, adherence and supportive care needs. Pts had access to a mobile application to record tracking data, contact NNs via secure messaging or a dedicated phone line. The intervention lasted 6 months. The primary endpoint was the Relative Dose Intensity (RDI). Secondary endpoints included adherence, toxicity, response and survival, quality of life, pts experience (PACIC Score), end-of-life support, and economic estimation of the use of healthcare resources. Results: From October 2016 to May 2019, 609 pts (median age: 62 years, 20-92; PS2: 11.8%) were included. 39% were receiving oral chemotherapy, and 61% other OAA. The RDI was significantly higher in the CAPRI arm (93.4% ±0.26 vs. 89.4% ±0.19, p = 0.04). The CAPRI intervention also improved PACIC scores (mean: 2.94±0.83 vs. 2.67±0.89, p = 0.01), the number of unplanned hospitalizations (15.1% vs. 22.0%, p = 0.04), hospitalization duration (mean: 2.82±6.96 days vs. 4.44±9.60, p = 0.02), and treatment-related grade≥3 toxicities (27.6% vs. 36.9%, p = 0.02). Conclusions: Compared to SOC, the CAPRI intervention improved RDI, pts experience, hospitalizations and their duration, as well as the rate of treatment-related grade≥3 toxicities. This type of intervention should represent a new standard in pts receiving OAA. Clinical trial information: NCT02828462.
Survival impact of multidisciplinary thoracic oncology care in a regional healthcare system.
Authors: Osarogiagbon Raymond U. , Faris Nicholas Ryan , Smeltzer Matthew , Derrick Anna , Lammers Philip Edward , Satpute Shailesh R. , Walsh William , Sroufe Rameses , Robbins Todd , Tokin Keith , Optican Rob , Fulford Angela , McHugh Laura , Wright Jeffrey , Mehrotra Anurag , Callihan Thomas , Ray Meredith
Published: May 2020

2004

Background: Much-advocated, the value and impact of multidisciplinary care and planning (MDC) needs greater evidence. We compared non-small cell lung cancer (NSCLC) patient characteristics, treatment patterns and survival in a large community healthcare system spanning 3 US states with some of the highest lung cancer incidence and mortality rates. Methods: We identified MDC patients in the Tumor Registry NSCLC data from 2011-2017. Because the MDC program was located in metropolitan Memphis, we separated non-MDC patients by location of care resulting in 3 cohorts: MDC, non-MDC metropolitan care and non-MDC regional care. Using National Comprehensive Cancer Network guidelines, we categorized treatment by stage as ‘preferred’, ‘appropriate’ (allowable under certain circumstances). We compared demographic and clinical characteristics across cohorts using chi-squared tests and compared survival using Cox regression with Bonferroni adjustment. We repeated survival analysis with propensity matched cohorts. Results: Of 6259 patients, 14% received MDC, 56% metro care and 30% regional care; MDC had the highest rates of African Americans (34% v 28% v 22%), stage I-IIIB (63 v 40 v 50), urban residents (81 v 78 v 20), stage-preferred treatment rates (66 v 57 v 48), stage-appropriate treatment rates (78 v 70 v 63;), and lowest non-treatment rates (6 v 21 v 28). All p<0.001. Compared to MDC, the hazard for death was higher in metro (1.4, 95% confidence interval 1.3-1.6) and regional (1.7, 1.5-1.9); hazards were higher in regional care v metro (1.2, 1.1-1.3); all p<0.001 after adjustment. Results were similar for MDC comparisons after propensity matching with and without adjusting for preferred treatment. No differences in regional and metro cohorts. Conclusions: In this large community-based healthcare system, receipt of MDC for NSCLC was associated with significantly higher rates of guideline-concordant care and survival, providing strong evidence for recommending rigorous implementation of MDC. [Table: see text]
The BRCA founder outreach study: Initial results of a digital health model.
Authors: Morgan Kelly , Symecko Heather , Kamara Daniella , Jenkins Colby , Levin Jeffrey , Lester Jenny , Spielman Kelsey , Pace Lydia E. , Marcell Vanessa , Wildman Temima , Fesko Yuri Anthony , Heitler Jacob , Robson Mark E. , Nathanson Katherine , Tung Nadine M. , Karlan Beth Y. , Domchek Susan M. , Garber Judy Ellen , Hamilton Jada G. , Offit Kenneth
Published: May 2020

2007

Background: NCCN now endorses BRCA founder mutation genetic testing (GT) via longitudinal studies in all Ashkenazi Jewish (AJ) individuals. The BRCA Founder OutReach (BFOR) study offers pre-GT online education with posttest engagement of primary care providers (PCPs). Methods: The study in 4 US cities enrolls those age > 25 with > 1 AJ grandparent. Participants enroll online with chatbot and video education, have GT at local centers, receive results from their PCP or BFOR staff, and are surveyed 12 weeks post disclosure and annually for 5 years. Univariate analyses and multivariable (MV) logistic regression models were used to evaluate characteristics associated with not completing GT, selecting PCP to disclose GT, and positive GT. Results: As of January 2020, 4754 participants consented (77.5% female, median age 51); 37.7% never previously considered GT. Cancer family histories (FHx) were 56.4% low risk (LR), 36.4% high risk (HR), and 7.2% had a familial mutation (FM). To date, 3658 participants (76.9%) completed and 677 (14.2%) did not complete GT; the remainder are pending. Only 34.8% of participants selected PCP to disclose GT, and 42.6% of PCPs agreed. Of the 124 mutation carriers (3.4%) identified, 60.5% had a FM. At the 12-week survey, 65.4% of mutation carriers planned to proceed with recommended screening or scheduled risk reducing surgery; 3.5% of those with negative GT and HR FHx reported further GT. Satisfaction was high (mean 9.58/10, SD 1.12) and unrelated to result (p>.05). Conclusions: A digital model for founder mutation testing engaged those with LR FHx and no prior experience with GT. Older participants were more likely to complete the study. Males were less likely to enroll but more likely to carry mutations. The majority of those who tested positive had a FM. A minority of results were disclosed by PCPs. Continued follow up is needed to determine long term outcomes. [Table: see text]
Randomized trial of web-based genetic education versus usual care in advanced cancer patients undergoing tumor genetic testing: Results from the ECOG-ACRIN NCI Community Oncology Research Program (NCORP; EAQ152) COMET trial.
Authors: Bradbury Angela R. , Lee Ju-Whei , Gaieski Jill B , Li Shuli , Gareen Ilana F , Flaherty Keith , Herman Benjamin A. , DeMichele Angela , Domchek Susan M. , Maxwell Kara Noelle , Onitilo Adedayo A. , Virani Shamsuddin , Park Sujung , Faller Bryan A. , Grant Stefan C. , Ramaekers Ryan C. , Behrens Robert J. , Nambudiri Gopakumar S. , Carlos Ruth , Wagner Lynne I.
Published: May 2020

2008

Background: Enthusiasm for precision oncology may obscure the complex psychosocial and ethical considerations for tumor genetic testing. Low patient genetic knowledge has been documented and heightens the risk for adverse experiences. We developed a web-based intervention to increase genetic knowledge and decrease distress among advanced cancer patients undergoing tumor genetic testing. Methods: 594 patients (80% from NCORP Community Sites) were recruited and randomized to web-intervention (n = 293) or usual care (n = 301), prior to receipt of tumor genetic test results. Primary outcomes were genetic knowledge, anxiety, depression, and cancer-specific distress measured at T0 (prior to intervention), T1 (post-intervention), T2 (after receipt of tumor results) and T3 (3 months post receipt of tumor results). Secondary outcomes included satisfaction, regret and disappointment. The effect of web-intervention was evaluated using t-test, multiple linear regression and logistic regression, with an intent-to-treat approach. Results: Patients randomized to web-intervention had better knowledge improvement than those randomized to usual care (T1-T0, p < 0.0001; T2-T0, p = 0.003). No difference was observed in change scores for anxiety, depression or cancer-specific distress. To find the moderators of intervention effect (including sex, age, education, and literacy) two 2-way interactions were noted with statistical significance: higher depression among those in the intervention arm versus the control arm for patients with lower literacy (p = 0.03); and lower cancer-specific distress among women in the intervention arm than with usual care but no such effect noted in men (p = 0.01). 71% of patients reported receiving tumor test results and this did not differ by arm. Only 20% of patients reported regret and disappointment at T2, which was more likely for those without a mutation of interest (MOI) detected vs those with a MOI detected (OR = 2.08, 95% CI, 1.13 to 3.83, p = 0.02). Conclusions: Web-based education prior to receipt of tumor genetic test results increases patient understanding of tumor genetic testing. While the intervention did not significantly reduce distress, results suggest that women who received the intervention had lower cancer-specific distress than those with usual care. Future refinements to the web-intervention are needed to address low literacy groups, men and patients with no actionable results. Clinical trial information: NCT02823652.
Patient-reported care satisfaction and symptom burden in hospitalized patients with cancer.
Authors: Kaslow-Zieve Emilia R. , Qian Carolyn L. , Azoba Chinenye C. , Wang Irene , Van Seventer Emily E. , Newcomb Richard , Jackson Vicki A. , Ryan David P. , Greer Joseph A. , El-Jawahri Areej , Temel Jennifer S. , Nipp Ryan David
Published: May 2020

2013

Background: Hospitalized patients with cancer often experience high symptom burden, which may impact their care satisfaction and use of health care services. Yet, studies describing these patients’ care satisfaction, symptom burden, and health care utilization are lacking. Methods: We prospectively enrolled patients with cancer and unplanned hospitalizations from 9/2014-4/2017. Upon admission, patients self-reported their care satisfaction (FAMCARE items asking about satisfaction regarding speed with which symptoms are treated and coordination of care) and physical (Edmonton Symptom Assessment System [ESAS]) and psychological (Patient Health Questionnaire 4 [PHQ4]) symptom burden. We used regression models to identify patient factors associated with care satisfaction. We also explored associations between patients’ care satisfaction, symptom burden, and hospital length of stay (LOS) in models adjusted for age, sex, marital status, comorbidity score, cancer type, cancer documented as curable/incurable, time since cancer diagnosis, and admission to a dedicated oncology service. Results: We enrolled 1,576 of 1,749 (90.1%) consecutive patients (mean age = 63.19±13.39 years, 46.3% female). Most reported being very satisfied/satisfied with the speed with which symptoms are treated (89.0%) and coordination of care (90.1%). Older age (B = 0.01, P < .02 for both) and admission to a dedicated oncology service (B = 0.20, P < .01 for both) were each independently associated with higher satisfaction with the speed with which symptoms are treated and coordination of care. Higher satisfaction with the speed with which symptoms are treated was associated with lower PHQ4 depression (B = -0.14, P = .01), PHQ4 anxiety (B = -0.11, P < .01), ESAS physical (B = -1.30, P < .01), and ESAS total (B = -2.44, P < .01) symptoms. Higher satisfaction with coordination of care was associated with lower PHQ4 depression (B = -0.14, P = .02), PHQ4 anxiety (B = -0.16, P < .01), ESAS physical (B = -1.30, P < .01), and ESAS total (B = -2.75, P < .01) symptoms. Satisfaction with the speed with which symptoms are treated (B = -0.47, P = .03) and coordination of care (B = -0.50, P = .03) were both associated with shorter hospital LOS. Conclusions: Most hospitalized patients with cancer reported high care satisfaction, which was associated with older age and admission to a dedicated oncology service. We found relationships among higher care satisfaction, lower symptom burden, and shorter hospital LOS, underscoring the importance of efforts to enhance symptom management and care coordination in this population.
Cancer diagnoses and survival rise as 65-year-olds become Medicare eligible.
Authors: Patel Deven C. , He Hao , Berry Mark F. , Yang Chi-Fu Jeffrey , Trope Winston , Lui Natalie , Liou Douglas Z. , Backhus Leah Monique , Shrager Joseph B
Published: May 2020

2015

Background: A “Medicare effect” has been described to account for increased health care utilization occurring at the age of 65, when individuals become eligible for government-sponsored health care. The existence of such an effect in cancer care, where it would be most likely to reduce mortality, has been unclear. Methods: Patients aged 61-69 diagnosed with lung, breast, colon, or prostate cancer from 2004-2016 were identified using the Surveillance, Epidemiology, and End Results database and dichotomized based on eligibility for Medicare (age 61-64 vs 65-69). Using age-over-age percent change calculations, trends in cancer diagnosis, AJCC staging, and survival were characterized. Results: 134,991 patients were identified with lung cancer; 175,558 with breast; 62,721 with colon; and 238,823 with prostate. The age-over-age growth in the number of cancer diagnoses was highest at age 65 when compared to all other ages within the decade, for all four cancers (Table: p<0.01, p<0.001, p<0.01, p<0.001 respectively). Comparing age 65 diagnoses to the 61-64 year old cohort, the greatest difference for all four cancers was seen in stage I (lung p<0.001; breast p<0.002; colon p<0.001; prostate p<0.02). The older (65-69), Medicare-eligible cohort had higher cancer specific 5-year survival than the 61-64 aged cohort for lung (22.0% vs 21.0%, p<0.01) and colon cancer (66.2% vs 63.2%, p<0.01). Conclusions: The 65 age threshold for Medicare eligibility is associated with more cancer diagnoses, particularly in stage I, resulting in improved cancer-specific survival for some cancers. Near-elderly individuals may be delaying care until the age of 65. A Medicare-for-all system would thus be likely to reduce cancer mortality. [Table: see text]
Out-of-pocket cost of screening with breast MRI for women at high risk for breast cancer.
Authors: Pan I-Wen , Oeffinger Kevin C. , Shih Ya-Chen T.
Published: May 2020

2017

Background: The prevention provision of Affordable Care Act (ACA) mandates private insurance to waive cost sharing for preventive services with grade A or B recommendations from the US Preventive Services Task Force. Although several professional societies have recommended augmenting screening mammography with MRI for women at high risk for breast cancer, the ACA prevention provision does not apply to screening MRI. This study examined the proportion of high-risk women having zero cost sharing associated with breast MRI for screening purposes and estimated out of pocket (OOP) costs as well as sources of variations. Methods: We identified women who underwent MRI and mammography for breast cancer screening from Marketscan database, 2009-2017. We quantified OOP costs as the sum of copayment, coinsurance, and deductible and defined zero cost sharing as having no OOP cost. We calculated the proportion of zero cost sharing for mammography and that for MRI and compared the time trend of each before and after ACA (enacted in 2010). We used multivariable logistic regression to examine factors associated with zero cost sharing for MRI use. We estimated OOP costs of MRI and examined cost variations by geographic regions or whether a woman had high deductible plans. Results: 25,232 women were included in the analysis. For screening mammography, the rate of zero cost sharing increased from 81% in 2009 to 91% in 2011 (post ACA) then 97% in 2017. For MRI, the rate was 41%, 37%, and 25%, respectively. The odds ratio (OR) of zero cost sharing for MRI screening was significantly lower for women with high deductible plans (OR = 0.65, 95% CI: 0.59-0.72) and for those resided in South (vs. Northeast) region (OR = 0.50, 95% CI: 0.46-0.53), after controlling for age, MSA, family breast cancer history, and year. OOP costs of MRI varied by region and insurance plan (Table); the mean OOP cost for women with high deductible plan were more than twice the mean cost for those in other plan types. Conclusions: With the financial protection under the ACA prevention provision applying to only screening mammography, many women at high risk for breast cancer are subject to high OOP costs for MRI screening. Those enrolled in high deductible plans and resided in the South are especially vulnerable financially. [Table: see text]
Disparities in the treatment of brain metastases from breast cancer: Insights from the National Cancer Database.
Authors: Chahine Zena , Faisal Muhammad Salman , Jayakrishnan Thejus Thayyil , Abel Stephen , Wegner Rodney E.
Published: May 2020

2037

Background: Breast cancer is the most common malignancy in women accounting for over 300,000 cases per year. Unfortunately, brain metastases are found in a sub-group of patients with breast cancer even at presentation. Management of brain metastases typically includes radiotherapy with conventional whole brain radiation therapy (WBRT) or more focused stereotactic radiosurgery (SRS). We queried the National Cancer Database (NCDB) to analyze the incidence of brain metastases at diagnosis in breast cancer patients, as well as trends in radiation use/technique. Methods: The NCDB was queried for patients who were diagnosed with breast cancer between 2004-2015 and had brain metastasis at presentation (N = 4,491). We excluded patients without brain radiation and inadequate follow up. Odds ratios were calculated to identify factors associated with treatment. Multivariable cox regression was used to determine predictors of survival. Results: Using the eligibility criteria above 1,505 patients were identified in the NCDB. The cohort had a median age of 58 years. A small portion were uninsured (7%) population uninsured and 81% of radiation treatments were delivered in metropolitan areas. Two hundred sixty-one (17.3%) patients received SRS while 1,244 (82.7%) received WBRT. Those patients with private insurance, higher income, metro location, and having care delivered at an academic center were more likely to receive SRS. Conversely, the likelihood of receiving WBRT was significantly higher in those with luminal type cancer, African Americans, the uninsured, and those located in urban areas or treated at a community cancer center. On Cox regression, predictors of worse survival were age > 60 with Hazard Ratio (HR) 1.3 (95% CI 1.17-1.49), a comorbidity score > 2 with HR 1.45 (95% CI 1.1-1.9), and extra cranial metastatic disease with HR 1.33 (95% CI 1.15-1.54). Conclusions: This analysis of the NCDB demonstrates socioeconomic and demographic disparities in the treatment of patients with brain metastases from breast cancer. There is a continued need to reduce these disparities and improve access to care for at-risk populations affected by this highly prevalent malignancy.
Development and validation of natural language processing (NLP) algorithm for detection of distant versus local breast cancer recurrence and metastatic site.
Authors: Karimi Yasmin , Blayney Douglas W. , Kurian Allison W. , Rubin Daniel , Banerjee Imon
Published: May 2020

2043

Background: Electronic health records (EHR) are used for retrospective cancer outcomes analysis. Sites and timing of recurrence are not captured in structured EHR data. Novel computerized methods are necessary to use unstructured longitudinal EHR data for large scale studies. Methods: We previously developed a neural network-based NLP algorithm to identify no recurrence vs. metastatic recurrence cases by analyzing physician notes, pathology and radiology reports in Stanford’s breast cancer database, Oncoshare (Cohort A). To validate this algorithm for local vs. distant recurrence, we identified a distinct Oncoshare cohort (Cohort B). Cases were manually curated for longitudinal development of local or distant recurrence and metastatic sites. A two-sided t-test was used to compare mean probabilities between local and distant recurrence cases. Next, we combined cases in Cohorts A and B to train and validate a novel NLP classifier that identifies metastatic site. The combined cohort was randomly divided into training and validation sets. Sensitivity and specificity were calculated for the NLP algorithm’s ability to detect metastatic sites compared to manual curation. Results: In Cohort B: 350 metastatic cases were identified. Mean probability for local and distant recurrence was 0.43 and 0.79, respectively and differed significantly for patients with local vs. distant recurrence (p<0.01). In Cohorts A and B: 632 metastatic cases were used for determination of sites. Sensitivity and specificity were highest for detection of peritoneal metastasis followed by liver, lung, skin, bone and central nervous system (table). Conclusions: This NLP algorithm is a scalable tool that uses unstructured EHR data to capture breast cancer recurrence, distinguishing local from distant recurrence and identifying metastatic site. This method may facilitate analysis of large datasets and correlation of outcomes with metastatic site. [Table: see text]
Improved prognostication for lung cancer patients from computed tomography imaging using deep learning.
Authors: Torres Felipe , Akbar Shazia , Baldauf-Lenschen Felix , Leighl Natasha B.
Published: May 2020

2044

Background: Clinical TNM staging derived from computed tomography (CT) imaging is a key prognostic factor for lung cancer patients when making decisions about treatment, monitoring, and clinical trial eligibility. However, heterogeneity among patients, including by molecular subtypes, may result in variability of survival outcomes of patients with the same TNM stage that receive the same treatment. Artificial intelligence may offer additional, individualized prognostic information based on both known and unknown features present in CTs to facilitate more precise clinical decision making. We developed a novel deep learning-based technique to predict 2-year survival from pretreatment CTs of pathologically-confirmed lung cancer patients. Methods: A fully automated, end-to-end model was designed to localize the three-dimensional (3D) space comprising the lungs and heart, and to learn deep prognostic features using a 3D convolutional neural network (3DCNN). The 3DCNN was trained and validated using 1,841 CTs of 1,184 patients from five public datasets made available in The Cancer Imaging Archive. Spearman’s rank correlation (R) and concordance index (C-index) between the model output and survival status of each patient after 2-year follow-up from CT acquisition was assessed, in addition to sensitivity, specificity and accuracy stratified by staging. Results: 3DCNN showed an overall prediction accuracy of 75.0% (R = 0.32, C-index = 0.67, p < 0.0001), with higher performance achieved for stage I patients (Table) . 3DCNN showed better overall correlation with survival for 1,124 patients with available TNM staging, in comparison to TNM staging only (R = 0.19, C-index = 0.63, p < 0.0001); however, a weighted linear combination of both TNM staging and the 3DCNN yielded a superior correlation (R = 0.34, C-index = 0.73, p < 0.0001). Conclusions: Deep learning applied to pretreatment CT images provides personalized prognostic information that complements clinical staging and may help facilitate more precise prognostication of patients diagnosed with lung cancer. [Table: see text]
Semi-automated discovery of real-world patient pathway from U.S. electronic health records: Advanced non-small cell lung cancer (aNSCLC).
Authors: Yang Fei , Zhang Ju , O’Neill Tyler J. , Sharma Vishakha , Prime Matthew Stewart
Published: May 2020

2048

Background: A good understanding of cancer care continuum presents opportunities to uncover unmet medical needs and improve outcomes and clinical workflow efficiency. However, patient care is poorly understood in real-world clinical practice. This study aimed to discover real-world patient pathways for advanced non-small cell lung cancer (aNSCLC). Methods: This study included patients diagnosed with aNSCLC (stage IIIB and above) at their initial diagnoses between 2011-2018 from the Flatiron Health electronic health records (EHR)-derived deidentified database. Overall survival (OS) was calculated using the Kaplan-Meier method. We also explored the application of process mining analytics (Heuristics Miner & Directly-Follows Graphs) to describe and visualize real-world patient pathways, following patients from initial diagnosis, through any National Comprehensive Cancer Network guideline-recommended companion diagnostics (CDx; including EGFR, ALK, ROS1, KRAS, BRAF, or PD-L1) and treatment patterns, until death or end of the study. Results: A total of 39,156 eligible patients were included. During a median follow-up of 0.78 years (interquartile range [IQR] 1.27), 28,801 (73.6%) patients died (median OS 11.6 months [95% CI 11.4 -11.8]). We established a semi-automated process discovery pipeline that transforms high-dimensional EHR datasets in table format as input into real-world event logs and produces a series of patient pathway graphs as output. The patient pathway graphs showed 19,878 (50.8%) patients had CDx testing within a median 11 days (IQR 18) and 29,241 (74.7%) patients started first-line therapy within a median 1.2 months (IQR 1.2) after the initial diagnosis. When we stratified analysis by years of initial diagnosis (2011-2014 vs 2015-2018), 38.8% (6808 of 17546) vs. 60.5% (13070 of 21610) patients had their first CDx testing within median 12 days (IQR 21) vs. 10 days (IQR 17) respectively. Conclusions: This study suggested an uptake of 56% increase of CDx utilization over the last 8 years in real-world clinical setting and that patient pathways can be analyzed and visualized in a semi-automated fashion.
Concordance study of treatment guidance from an online patient assistance algorithm (OCPAP) and treatment recommendation of a multidisciplinary panel of oncologists in India.
Authors: Jotwani Amit Kumar , Jain Rashie , Goud Rakesh Shankar , Gururao Shashidhar , Poovaiah Thirtha , Rajan Rejil
Published: May 2020

2049

Background: OCPAP (online cancer patient assistance pathway) is an algorithm-based online platform for patients to help them understand their treatment options. It is based on basic inputs like cancer type, stage, patient’s performance status and treatment received. It is developed by a team of oncologists from onco.com based on standard guidelines. Till date, more than 30,000 users from 18 countries have used OCPAP platform to get directional treatment recommendations. Onco.com also provides onco tumour board (OTB) services to help patients to get a detailed opinion from a multidisciplinary panel of oncologists. We presented initial data on development of OCPAP™ at the ASCO Breakthrough Summit 2019 ( OCPAP Breakthrough Abstract ). Here we present a concordance analysis of treatment recommendations from OCPAP platform against opinion of OTB panel. Methods: We analysed data from 448 eligible cases (those with 15 types of solid cancers) where an OTB opinion was provided and compared it with OCPAP treatment recommendation. We entered data from 448 anonymised OTB case records in to the OCPAP platform and recorded the output in terms of treatment recommendations. The study was blinded by its very design as we took data of cases from the time when the platform was non-existent. Results: We compared and analysed the recommendation provided by OCPAP in terms of surgery, chemotherapy, targeted therapy, radiation, clinical trials, palliative care or best supportive care against the opinion of OTB panel. Overall the concordance rate was found to be 93% for all cases and it was above 90% for all types of cancers included, except for brain tumors where it was 78% mainly due to variation in surgical operability and imaging findings influencing the treatment recommendation. The concordance rate was above 90% for all stages of disease and was highest for metastatic disease where it was 95%. The reasons for discordance were mostly related to availability of more detailed insights about the disease for OTB, like clinical details, performance status, imaging findings, molecular data and oligometastasis. Conclusions: The treatment direction recommended by OCPAP was found to be consistent with the one provided by OTB panel for most solid cancers. This indicates that OCPAP is an effective and simple online tool for patients to understand their treatment options, validate their ongoing treatment and be able to actively participate in their treatment decisions.
An automated EHR-based tool for identification of patients (pts) with metastatic disease to facilitate clinical trial pt ascertainment.
Authors: Kirshner Jeffrey J. , Cohn Kelly , Dunder Steven , Donahue Karri , Richey Madeline , Larson Peter , Sutton Lauren , Siu Evelyn , Donegan Janet , Chen Zexi , Nightingale Caroline , Hamrick James
Published: May 2020

2051

Background: Efforts to facilitate patient identification for clinical trials in routine practice, such as automating electronic health record (EHR) data reviews, are hindered by the lack of information on metastatic status in structured format. We developed a machine learning tool that infers metastatic status from unstructured EHR data, and we describe its real-world implementation. Methods: This machine learning model scans EHR documents, extracting features from text snippets surrounding key words (ie, ‘Metastatic’ ‘Progression’ ‘Local’). A regularized logistic regression model was trained, and used to classify patients across 5 metastatic status inference categories: highly-likely and likely positive, highly-likely and likely negative, and unknown. The model accuracy was characterized using the Flatiron Health EHR-derived de-identified database of patients with solid tumors, where manually abstracted information served as standard accurate reference. We assessed model accuracy using sensitivity and specificity (patients in the ‘unknown’ category omitted from numerator), negative and positive predictive values (NPV, PPV; patients ‘unknown’ included in denominator), and its performance in a real-world dataset. In a separate validation, we evaluated the accuracy gained upon additional user review of the model outputs after integration of this tool into workflows. Results: This metastatic status inference model was characterized using a sample of 66,532 patients. The model sensitivity and specificity (95%CI) were 82.% (82, 83) and 95% (95, 96), respectively; PPV was 89% (89, 90) and NPV was 94% (94, 94). In the validation sample (N = 200 originated from 5 distinct care sites), and after user review of model outputs, values increased to 97% (85, 100) for sensitivity, 98% (95, 100) for specificity, 92 (78, 98) for PPV and 99% (97, 100) for NPV. The model assigned 163/200 patients to the highly-likely categories, which were deemed not to require further EHR review by users. The prevalence of errors was 4% without user review, and 2% after user review. Conclusions: This machine learning model infers metastatic status from unstructured EHR data with high accuracy. The tool assigns metastatic status with high confidence in more than 75% of cases without requiring additional manual review, allowing more efficient identification of clinical trial candidates and clinical trial matching, thus mitigating a key barrier for clinical trial participation in community clinics.
Novel evidence synthesis system to support living systematic reviews and living guidelines for cancer immunotherapy.
Authors: Riaz Irbaz Bin , Rawal Samarth C , Siddiqi Rabbia , Asghar Noureen , Islam Mahnoor , Gajic Ognjen , Wang Zhen , Montori Victor , Herasevich Vitaly , Go Ronald S. , Baral Chitta , Liu Hongfang , Vandvik Per Olav , Haddad Tufia C. , Bryce Alan Haruo , Rajkumar S. Vincent , Murad M. Hassan
Published: May 2020

2054

Background: Systematic reviews that summarize the toxicity of Immune checkpoint inhibitors (ICIs) become outdated very soon after publication. Therefore, we reported results of a toxicity meta-analysis at 2019 ASCO meeting and informed the intent to create a living systematic review (LSR). LSRs combine human and machine effort and support rapid evidence synthesis and living clinical practice guidelines. Now, we report our experience maintaining a LSR on toxicity of ICIs. Methods: Steps include quarterly literature searches to identify new clinical trials reporting ICI-associated adverse events (AEs), AI-enabled screening of new citations which meet the inclusion criteria, automated cumulative meta-analysis and an online reporting platform. Standard data formats and protocols were designed for inputting text, tables and graphics. Software was written to interpret these data and output the information in the appropriate format, such as a forest plot and summary tables. Finally, a dynamic interface that enables user inputs and displays the associated output was designed. Results: The LSR is continuously updated incorporating toxicity data from new clinical trials as it becomes available. We have screened 8000 relevant citations and summarized the odds of Grade 3 or higher AEs and AEs of special interest in patient receiving ICIs. The results are updated on quarterly basis and are available online. The results are updated on quarterly basis and will be available on a website at the time of publication. Prototype with dummy data is available at this link . This interface can also be manipulated via user input to organize and sort data tables and forest plots by type of cancer, name or mechanism (PD-1 or PD-L1) of ICI agent, single agent or combination, type of control arm, line of treatment and several other clinically relevant filters. For example, a user can instantaneously generate a meta-analysis summarizing the risk of colitis or pneumonitis in metastatic lung cancer trials with pembrolizmuab. Conclusions: This LSR engine can prospectively synthesize toxicity data from ICI trials in an efficient manner providing accurate and timely information for advanced clinical decision support at point-of-care. Efforts are ongoing to improve efficiency of screening, improve AI-enabled processes for automated screening and data abstraction, and test across multiple clinical questions.