bluuebunny/crossref_metadata_2025 huggingface dataset:
CTNND1 to mediate bone metastasis of triple-negative breast cancer via regulating CXCR4.
Authors: Gong Chang , Lin Qun , Fang Xiaolin , Jiang Wenguo , Li Jun , Li Juanmei , Shi Yu , Luo Qing , Liu Zihao , Cen Yinghuan
Published: June 2021

e13045

Background: Compared to lumial breast cancer, the proporation of triple-negative breast cancer (TNBC) with bone metastases (BMs) is relatively low and few data focusing on the mechanism of the BMs in TNBC are available, Here, we screened that CTNND1 was associated with BMs of TNBC by integrating high-throughput sequencing, and further investigated the role of CTNND1 in BMs of TNBC in vitro. Methods: TNBC tissue samples with only BMs (n = 6) and without any metastasis (n = 10) were tested using high-throughput sequencing and 11 differentially expressed relative genes were identified. We then quantified these 11 genes in normal breast tissue samples (n = 26), TNBC tissue samples with only BMs (n = 10), TNBC tissue samples without any metastasis (n = 88) as well as luminal tissue samples with BMs（n = 10）through qPCR and immunohistochemical staining (IHC). The effects of knocking down CTNND1 on the interaction between TNBC cells and osteoblasts were examined by cell adhesion, transwell migration and matrigel invasion assays. To explorethe role of CTNND1 in mediating bone metastasis in TNBC, we used RNA-sequencing to find out the relative downstream gene CXCR4 and PI3K-AKT-mTOR pathway and verified it in vitro by Western Blotting. Results: Combining our high-throughput sequencing data, qPCR and IHC in clinical tissue samples, we verified that CTNND1 was decreased in TNBC patients with bone metastasis compared to normal tissue and luminal tissue with BMs. Knocking down of CTNND1 in TNBC cells including MDA-MB-231, MDA-MB-468 and BT549 weakened cells adhesion, but facilitated cells migration and invasion. Mechanically, knocking down of CTNND1 upregulated CXCR4 via activating PI3K-AKT-mTOR pathway in TNBC but not luminal and HER2- positive breast cancer cells lines. Conclusions: CTNND1 mediates bone metastasis in triple-negative breast cancer via regulating CXCR4.CTNND1 may serve as a potential predictor of bone metastasis for TNBC patients.
Association of pathological clinical characteristics, PD L 1 receptor expression (sp 142), with tumor lymphocytic infiltration cells (TILs) in patients (pts) with triple negative breast cancer (TNBC) in Tucumán, Argentina.
Authors: Zarba Juan Jose , Vinuales Ana , Holgado Silvia Victoria , Stagmeyer Erika
Published: June 2021

e13049

Background: Breast cancer (BC) is the most prevalent tumor in women and the leading cause of cancer death in women. TNBC has the worst prognosis among BC subtypes and limited treatment options, mainly including chemotherapy. The efficacy of immunotherapy is clear for immunogenic tumors, such as melanoma, kidney cancer, non-lung cancer small cell, among others. BC seems to be less immunogenic. Basal-type TNBC present a prominent infiltration of inflammatory cells, suggesting that an immune pathway plays a role in tumorogenesis. The development of immunotherapy (IO)has reached an important turning point in the history of cancer treatment based on the use of the immune system itself to fight tumor cells. PD-L1 overexpression is the only predictive response biomarker for anti-PD-1 / PD-L1 therapy that is accepted in TNBM. Methods: Retrospectively, 68 cases of TNBC from the Pathological Anatomy Service of the Ntra. Sra. De las Mercedes Maternity Institute, of Tucumán, between 2010 and 2016 were analyzed. VENTANA anti PDL1 sp142 assay platform was used. Tumor-infiltrating immune cells (IC) are scored as the proportion of tumor area that is occupied by PD-L1 staining IC of any intensity. A specimen should be considered to have PD-L1 expression if the specimen exhibits ≥ 1% IC. In addition, carcinomas with a proportion greater than 50% of lymphocytic infiltration and its association with the expression of PD L1 were studied according to the recommendations of the International TILs Working group. Results: The median age of the patients was 56 years (21-80). The predominant histological type was non-specific type ductal carcinoma, reported in 45/68 cases (66%), following the medullar 9 / 68 (13%) lobular in 8/68 (11%), metaplastic 3/68 (4%) and other 4%. The tumor grade (G), half of the cases were G 3 with 34/68 (50%), G 2 with 42%. The largest proportion of pts, 42%, had no lymph node (LN) involvement, 33% had between 1 to 3 positive LN and 25% showed 4 or more LN. Stage II 39/68 patients (58%) in stage III 20/68 (30%), I (9%, 6) and IV (3%, 2). 16% (11/68) of the patients were PD-L1 positive. Tumors with lymphocytic infiltration between 0% and 10% expressed 24% (2/37), no expression was observed in tumors with TIls between 10 and 50% and in cases with lymphocytic infiltration greater than 50% expression of PD L was observed 1 in 9/18 cases (50%) (Fisher's exact test, p < 0.0001). Conclusions: It was demonstrated that there is an association between the stromal lymphocytic infiltrate (TILs) and the expression of PD-L1 in tumor cells, in this population of women from Tucumán, which would help to select patients as candidates for anti PD L1 therapies.
Survival outcomes in patients with IDC and ILC breast cancer: A well matched single institution study.
Authors: Grimm Michael , Ramaswamy Bhuvaneswari , Lustberg Maryam B. , Wesolowski Robert , Sardesai Sagar D. , VanDeusen Jeffrey Bryan , Cherian Mathew Amprayil , Stover Daniel G. , Gatti-Mays Margaret Elena , Pariser Ashley , Kassem Mahmoud , Stephens Julie , Palettas Marilly , Williams Nicole Olivia
Published: June 2021

e13056

Background: Invasive lobular carcinoma (ILC) accounts for only 10-15% of all invasive breast cancers but has distinct clinicopathologic characteristics and genomic profiles. In particular, metastatic lobular cancers (mILC) have unique sites of metastasis and it is unclear if the response to initial endocrine therapy differs from metastatic ductal cancers (mIDC). Therefore we have undertaken a single-institution, retrospective analysis to compare overall outcomes and response to initial endocrine therapy (ET) in patients (pts) with metastatic ILC and IDC. Methods: An IRB approved retrospective review of medical records was conducted evaluating pts treated for metastatic IDC and ILC at The Ohio State University Comprehensive Cancer Center from January 1, 2004 to December 31, 2014. Pts diagnosed with mIDC were matched on age, year of diagnosis, estrogen receptor/progesterone receptor and HER2 status and site of metastasis 2:1 to patients diagnosed with mILC. Overall survival (OS) was defined as the time from metastasis to death or last known follow-up. Progression-free survival (PFS) was defined as time from metastasis to progression on first-line ET. Time to chemotherapy (TTC) was defined as time from starting ET for metastasis to initiation of chemotherapy. Kaplan Meier (KM) methods were used to calculate median OS, PFS and TTC. Results: A total of one hundred sixty one pts with metastatic breast cancer were included in this analysis. The demographic features between the two groups were well balanced and included in the table below. The median OS was 2.6 yrs (95% CI: 1.55, 3.22) for mILC and 2.2 yrs (95% CI: 1.95, 2.62) for mIDC. A subset of 111 patients who started on endocrine therapy were used in the PFS and TTC analyses. The median PFS following first-line ET was 2.2 yrs (95% CI: 0.1.0, 2.7) for mILC and 1.4 yrs (95% CI: 0.91, 1.90) for mIDC. Median TTC was 2.1 yrs (95% CI: 1.71, 4.92) for mILC and 2.4 yrs (95% CI: 1.90, 4.77) for mIDC. There was no statistically significant difference in outcomes between the two groups. Conclusions: Outcomes in patients with ILC and IDC have been varied, with several studies reporting that patients with ILC have worse outcomes and response to chemotherapy. Our retrospective study examining outcomes in mILC in comparison with mIDC showed no difference in OS. Given the concern of resistance to conventional therapies in patients with lobular cancers, it is reassuring to see that the median PFS on first line ET and TTC was similar to metastatic ductal cancers.[Table: see text]
Real-world effectiveness of eribulin in heavily pretreated patients with metastatic breast cancer in China: A multicenter retrospective study.
Authors: Zhao Yannan , Xie Ning , Li Wei , Chen Wenyan , Lv Zheng , Zheng Yabing , Sun Tao , Liu Jieqiong , Zhang Jian , Hu Shihui , Wang Yajun , Gong Cc , Li Yi , Xie Yizhao , Ge Rui , Xu Fei , Wang Biyun
Published: June 2021

e13057

Background: Eribulin is a nontaxane microtubule inhibitor approved in China for patients with locally advanced or metastatic breast cancer previously treated with anthracyclines and taxane. The aim of this study was to evaluate the efficacy and safety profile of eribulin and explore potential predictive factors for the efficacy of eribulin among Chinese women with metastatic breast cancer (MBC) in real-world practice. Methods: A total of 272 consecutive MBC patients who were treated with eribulin from November 2019 to October 2020 in 9 institutions nationwide were included in this study. Eribulin was administered intravenously at a dose of 1.4 mg/m2 on days 1 and 8 of a 21-day cycle. Efficacy outcomes included progression-free survival (PFS), overall survival (OS), objective response rate (ORR), and clinical benefit rate (CBR). Adverse events (AEs) were graded according to The National Cancer Institute Common Toxicity Criteria (NCI-CTC) version 5.0. Results: Eribulin showed a median PFS of 3.9 months (95% confidence interval [CI] 3.3–4.3); however, the OS data were immature. The ORR was 16.2%, and the CBR was 21.7%. A total of 51.8% of patients received eribulin monotherapy, and 48.2% of patients were treated with eribulin combine with targeted therapy or other chemotherapy. The number of metastatic sites, duration of previous taxane treatment for MBC, and combination regimen with bevacizumab were significant in Cox multivariate analysis (p=0.048, p=0.039, and p=0.045, respectively) and were significantly associated with PFS of eribulin. The most common AEs with eribulin treatment were hematological toxicities, including neutropenia, leukopenia, and anemia. Conclusions: This is the first cohort of eribulin real-world data base on retrieval currently after eribulin launched in China. Eribulin was effective with a manageable toxicity profile in clinical practice. Furthermore, when prescribed in combination with other agents, eribulin did not increase the toxic effects of each agents. Eribulin monotherapy or combine with other agents is alternative for the heavily pretreated patients with MBC. [Table: see text]
Genomic landscape of cell-free DNA in a diverse cohort of metastatic breast cancer patients.
Authors: Cheng Shirley , Nguyen Edward , Pagano Ian , Fukui Jami Aya
Published: June 2021

e13066

Background: Breast cancer is the most prevalent cancer and the second leading cause of cancer deaths among women in the United States. Once the primary breast cancer has metastasized to other parts of the body, despite treatment, patients have an incurable disease. Compared to the primary tumor, often the metastasized tumor sites have different mutational profiles that are not represented in the initial biopsy. Liquid biopsy is becoming a more commonly accepted method in clinical practice to determine the heterogeneity of metastatic tumors by analyzing cell-free DNA (cfDNA). Several studies have demonstrated that cfDNA can be utilized as an effective prognostic tool and can reveal multiple clinically targetable alterations in metastatic breast cancer (mBC). Methods: We characterized the genomic landscape of cfDNA in a diverse patient population and across different subtypes of mBC. We performed a retrospective chart review in patients (n = 41) with metastatic breast cancer from a medical oncology clinic within the Hawaii Pacific Health system. Patients who had at least one cfDNA testing by Guardant360 were evaluated. Patient demographics, age at diagnosis, race, subtype and mutations were reviewed along with treatment information. Results: We found no statistically significant differences in genomic landscape according to race, however there were differences seen in tumor genomics according to age and subtype. Older patients were less likely to have detectable disease on liquid biopsy compared to younger patients (age 70+ and 60-69 vs 30-39; xp 0.02). Consistent with subtype, mutations in ESR1 (n = 12) and PIK3CA (n = 14) were more commonly seen in hormone positive (HR+) mBC where known tailored treatment options are available (ie. fulvestrant and alpelisib respectively). Postmenopausal patients were more likely to have ESR1 mutations than premenopausal patients (50-59 and 70+ vs 30-39 and 40-49, xp 0.009). About half (n = 20) had TP53 mutations, followed by PIK3CA (n = 14), ESR1 (n = 12), CCND1 (n = 7) and MYC (n = 6). Conclusions: We evaluated 41 unique cases of mBC and correlated them with their genomic profiles. We plan to further investigate genomic changes according to treatment with subsequent repeat liquid biopsies. We hope to utilize these findings to help prognosticate and guide future treatment options.
Development of the oncology opportunity cost assessment tool.
Authors: Handley Nathan , Binder Adam F , Gentsch Alexandra , Granberg Rachel , Heyer Arianna , Davis Garrison , Nord Garrison , Rising Kristin
Published: June 2021

e13502

Background: While awareness of direct patient-level costs of cancer care are growing, less is known about the patient-level opportunity cost of care. Opportunity costs of care may include time spent seeking care, lost wages, lost leisure time, and other indirect costs associated with seeking care. Despite acknowledgment of the importance of considering patient opportunity costs in care treatment decisions, assessment of opportunity costs experienced by individual patients or caregivers is not routinely performed by healthcare providers in general, or oncology providers in particular. The purpose of this work was to develop an instrument, the Oncology Opportunity Cost Assessment Tool (OOCAT), to evaluate patient opportunity cost of seeking oncology care. Methods: Survey development was an iterative process with multiple rounds of stakeholder engagement. First the research team developed a list of potential opportunity cost themes informed by their own experiences. Next, we met with an established patient advisory group within the cancer center to expand this list of themes. We then conducted focus groups with patients and caregivers to explore in further depth their logistical and financial considerations related to seeking care. Findings were used to further expand the list of opportunity cost themes, with this list reviewed in real time with the focus group participants to ensure perspectives were appropriately captured. We then generated a set of survey items to represent each of the themes listed. We generated two items to represent each unique theme. The first item of the instrument sought to quantify the opportunity cost of the theme (e.g. time spent parking); the second component ascertained the patient-perceived importance of the theme using a 7-point Likert scale. Upon drafting of the initial OOCAT, we performed cognitive interviews with a random sampling of patients in order to ensure content validity and clarity of instrument items. Results: We completed 4 virtual focus groups with a total of 23 participants (17 patients and 6 caregivers) followed by cognitive interviews with 13 patients. The resulting OOCAT consists of 17 items that examine time requirements, financial implications, and logistical and quality of life challenges for both patients and caregivers associated seeking oncology care. Conclusions: The OOCAT is a 17-item instrument designed to quantify patient-level opportunity costs of seeking oncology care. Further studies work is needed to validate the OOCAT survey and assess the impact of incorporating quantified assessment of opportunity cost into decision regarding when and where to seek oncology care.
A medication acquisition program to facilitate access to nonstandard targeted oncologic therapies.
Authors: Doctor Vicki , Markman Maurie , Parikh Ankur Rasik , Conte Bellinda
Published: June 2021

e13505

Background: Precision oncology provides targeted approaches to cancer diagnosis and treatment, but also carries significant risks to reimbursement and patient access. A recent survey found that up to 60% of authorization denials are due to the therapy being off-label and experimental. The Cancer Treatment Centers of America's Medication Acquisition Program (CTCA-MAP) was initiated in October 2015 with the goal of helping patients successfully navigate a medication acquisition process following prior authorization denials for off-label therapy. Methods: A consecutive series of cancer patients who were non-responsive to standard-of-care, and for whom off-label targeted therapies have been matched to a potentially actionable genetic or molecular variant were enrolled into CTCA-MAP following the denial of payer preauthorization. The CTCA-MAP appeals payer denials, and simultaneously coordinates applications to patient assistance programs. Each payer appeal is customized to the patient's disease profile and unique tumor genomics and is based on any available evidence supporting the therapy’s use and safety in the patient’s tumor type. Results: A total of 825 patients (338 males and 487 females; median age 57 years) were enrolled into the program from October 2015 to October 2020. The most common tumor types were breast (n = 157), colorectal (n = 96), pancreas (n = 72), lung (n = 68), ovarian (n = 35) and prostate (n = 35). 682 (82.7%) patients were able to access therapy through patient assistance programs (n = 548), overturned payer appeals (n = 133) or conversion from patient assistance to insurance (n = 1) within a median of 16 days from the date of program referral. Only 5 (0.6%) patients were unable to access therapy through payer appeals or philanthropic programs. The remaining 138 (16.7%) patients could not complete the program due to disease progression or death. The overturned payer appeals led to insurance coverage for an estimated USD 7.95 million in drugs (calculated as the multiplication of drug cost per cycle and the number of cycles received). Conclusions: The CTCA-MAP provides a mechanism through which cancer patients with potentially actionable genetic variants can acquire access to existing off-label targeted therapies when standard-of-care is no longer effective, or when they are ineligible for a clinical trial. This program's outcomes to date demonstrate a need for a concerted advocacy effort to increase accessibility for cancer patients to these innovative targeted therapies.
Incidence of asymptomatic COVID-19 positivity in cancer patients and effects on therapy.
Authors: Ross Nicole , Handorf Elizabeth A. , Meeker Caitlin R. , Chen Giana , Baldwin Donald , Vijayvergia Namrata
Published: June 2021

e13506

Background: As the coronavirus disease 2019 (COVID-19) pandemic threatens the delivery of cancer care, challenges to providing safe and quality care persist. Screening measures including SARS-CoV-2 polymerase-chain reaction (CovPCR) testing prior to invasive procedures, therapy administration, were instituted to address risk of spread from asymptomatic (AS) pts. Studies have documented poor outcomes with COVID-19 in cancer pts with rate of AS COVID-19 ranging from 0.6%- 8%. (Liang et.al, 2020; Al-Shamsi, et.al, 2020, Shah et.al. 2020). In the general population, rates of AS cases was estimated to be 17% (Byambasuren, O., 2020). This study aimed to examine the incidence and characteristics of AS COVID -19 in cancer pts, and determine its effect on cancer care delivery at a tertiary care center. Methods: With IRB approval, a retrospective chart review was conducted on cancer pts undergoing CoVPCR screening. Pts were considered AS if they had no recent fever (≥100.5 °F), cough, headache, loss of taste/smell, shortness of breath, diarrhea, or high risk exposure. This analysis compared cases (positive CoVPCR) identified by screening of AS pts to control (negative CoVPCR) pts (matched by planned procedure type and month of screening). Each COVID case was matched to 2 negative controls on month and planned procedure type. Patient characteristics and outcomes were compared between cases and controls using conditional logistic regression or Mantel-Haenszel tests. Results: Between 03/2020 and 09/2020, 4143 AS pts underwent CovPCR testing and 75 were chosen for analysis (25 cases; 50 controls). The incidence of AS COVID-19 in cancer pts was 0.6% (25/4143). Median age was lower in the cases (64 vs 70y, p = 0.04). Gender, race, primary cancer diagnosis, and co-morbidity distribution was similar between cases and controls. Of the cases, 10 pts (40%) never underwent the planned oncologic intervention while 11 (44%) had a delay related to the positive CoVPCR (2 pts had no intervention planned). Only 1 pt (2%) in control arm didn’t undergo the planned procedure. The mean duration of delay was 18 days (range 0-49 days, SD 16.72) in cases versus Zero days in control. Four (16.7%) cases developed symptoms within 14 days of positive CoVPCR testing but the PCR value did not predict this conversion. Conclusions: Incidence of AS COVID in our cancer pts was significantly lower than general population. Active screening delayed oncologic care but with institution of safety measures like separate treatment rooms and scheduling procedures at the end of the day have ensured safe and prompt cancer care delivery during the pandemic. Future research needs will address incorporating vaccination status into the screening algorithm to limit widespread CoVPCR screening, thus improving care delivery and cost effectiveness.
The use of quasi-experimental design methods to evaluate and improve the impact of acute care centers on oncologic emergencies.
Authors: Sweetenham John W. , Chaudhry Basit Iqbal , Teng Benjamin , Yue Andrew , Connor Nora
Published: June 2021

e13515

Background: Reducing avoidable hospital and emergency department (ED) use are national priorities in cancer care. Acute care centers (ACCs) that expand access for patients with oncologic emergencies are increasingly implemented as alternatives to inpatient and ED care. The impact of these ACCs is uncertain. Additionally, how to rigorously evaluate these interventions and to iteratively improve their effectiveness remains unclear as infrastructure interventions such as ACCs are not amenable to experimental manipulation. Methods: We are developing a novel quasi-experimental framework for evaluating and improving the effectiveness of an ACC intervention at the Simmons Comprehensive Cancer Center (SCCC) of the University of Texas Southwestern. SCCC covers one of the largest geographic regions of any academic medical center in the country, creating challenges addressing access to care. Drawing on the Andersen model for healthcare utilization we hypothesize that ACC effectiveness is mediated through enabling factors, particularly distance. Our initial evaluation framework draws on an untreated control group design with multiple pretest and post-test samples. The control group is comprised of patients living in zip codes farther away from the ACC. Additional analytic work will assess the feasibility of adding a matching cohort group structure based on factors such as onset of illness and matching individual patient episodes based on risk adjustment parameters. If the ACC is later expanded to other sites, the design can be further developed by adding a switching replications methodology to augment the quasi-experiment. Data collection draws on claims data provided through SCCC’s participation in Medicare’s Oncology Care Model (OCM). Results: Over OCM’s initial four performance periods (each six months long), all-cause risk adjusted hospitalization rates for SCCC patients ranged from 25.2% to 27.2%. All-cause risk adjusted OCM ED use ranged from 28.1 to 29.9%. Seeking to improve performance for both, SCCC leadership initially implemented a temporary urgent care clinic in August 2018. This initial prototype clinic was formalized into an operational ACC in August 2020. Evaluation of the impact of this ACC intervention is ongoing. Conclusions: ACCs represent potentially important means to reduce avoidable hospital and ED use. However, complex infrastructure interventions are not amenable to experimental evaluations assessing their impact, and it remains difficult to gain insights into how to tailor services through these interventions to support patients with oncologic urgencies and emergencies. Quasi-experimental approaches when integrated alongside ACC interventions represent promising mechanisms of evaluation and continuous quality improvement.
A solution to reducing avoidable emergency department visits: Implementation of an outpatient oncology acute care clinic.
Authors: Charania Sadaf , Devlin Judy , Brucker Edie , Simon Shayna , Hong Christine , Nair Kavitha , Bazzell Angela F. , Sweetenham John W.
Published: June 2021

e13517

Background: Emergency Department (ED) utilization by oncology patients accounts for more than 4.5 million visits in the United States annually, leading to hospitalization four times the rate of the general population.1,2 Many ED visits are the result of symptoms related to cancer or cancer treatment that can be managed on an outpatient basis. Unnecessary admissions lead to possible delays in cancer treatment and increased burden on healthcare resources.3 Simmons Acute Care (SAC), an advanced practice provider (APP)-led clinic, was established in August 2020 to provide an alternative model of oncology care to address these issues. Methods: A multidisciplinary team of key stakeholders was formed to develop an action plan. Institutional data was reviewed to identify the timing and volume of ED visits by oncology patients. Clinic hours were set Monday through Friday, 7:00am – 7:00pm, and referrals were made from primary oncology providers. Evidence-based clinical pathways were developed to standardize patient management, and a data collection plan was implemented to measure outcomes. Internal communications to patients and presentations at staff and faculty meetings occurred to inform patients and clinical staff/providers. Results: From August to December 2020, 165 patient visits were completed in SAC, 141 patients discharged home, 14 patients directly admitted to the hospital, and 10 patients transferred to the ED for a higher level of care. Based on data from 2020, the average cost of an ED visit for an oncology patient was $5,500 and increased to $28,500 if the patient is admitted. Patients with hematologic and gastrointestinal malignancies represented approximately 30% of all visits. Gastrointestinal symptoms were the most frequent presenting chief complaint. Conclusions: Supporting oncology patients in the ambulatory setting provided a reduction in admissions and unnecessary ED visits, leading to cost savings/avoidance to the patient and health system. Based on internal cost analyses, there are potential savings of over $2 million to the organization during this 5-month period. Additional studies are underway to assess patient satisfaction, as well as the economic impact for patients. 1. Rui PKK. National Hospital Ambulatory Medical Care Survey: 2015 emergency department summary tables. https://www.cdc.gov/nchs/data/nhamcs/web_tables/2015_ed_web_tables.pdf 2. Hong AS, Froehlich T, Clayton Hobbs S, Lee SJC, Halm EA. Impact of a Cancer Urgent Care Clinic on Regional Emergency Department Visits. J Oncol Pract. 2019;15(6):e501-e509. doi:10.1200/JOP.18.00743 3. Roy M, Halbert B, Devlin S, Chiu D, Graue R, Zerillo JA. From metrics to practice: identifying preventable emergency department visits for patients with cancer. Support Care Cancer Off J Multinatl Assoc Support Care Cancer. Published online November 7, 2020. doi:10.1007/s00520-020-05874-3
Implementation of a clinic to facilitate the transition from pediatric to adult cancer survivorship care.
Authors: Smith Stephanie M , Jin Alexander , Simon Pam , Clayton Alison , Benedict Catherine , Liedtke Michaela , Muffly Lori S. , Schapira Lidia
Published: June 2021

e13519

Background: Transitions from pediatric to adult care settings are challenging for adults with a history of complex childhood illness such as cancer. We developed a new clinical model to support young adult survivors of leukemia and bone marrow transplant (BMT) with transitioning from pediatric to adult focused survivorship care. Methods: We established the GREAT (Getting Regular Evaluations After Treatment) survivorship clinic as a collaboration between the adolescent/young adult (AYA) cancer program, pediatric oncologists, and specialists in adult hematologic malignancies. New patient appointments consist of two back-to-back visits: (1) a medical survivorship visit with a pediatric oncologist and an oncologist who specializes in hematologic malignancies/BMT to review the treatment history, medical issues, risk of late effects, and surveillance recommendations, and (2) an AYA-focused visit with a nurse practitioner to review fertility, education/career, and psychosocial concerns. Patients receive a treatment summary through the Passport for Care, based on pediatric survivorship guidelines. The clinic team then communicates with the patient’s primary care provider (PCP) or assists the patient with finding a PCP. Results: Since August 2020, we have seen 17 patients (12 telehealth, 5 in-person, 53% male, 47% non-Hispanic white, 41% Hispanic/Latino, 12% Asian). The median age at clinic visit was 28 years (range 24-39) and median time since treatment was 15 years (range 1-29). Patients were referred through the AYA cancer program: 8 had been regularly followed in the pediatric survivorship clinic, 2 had not been seen in pediatric oncology/survivorship for many years, 3 were treated as children but most recently seen by adult oncologists, and 4 were treated by adult oncologists and referred for AYA-specific survivorship care. Twelve (71%) patients had a PCP they see regularly, while 2 did not have a PCP and 3 were not sure. Communication with PCPs consisted of faxing the clinic note and calling the PCP’s office. All PCPs were receptive and expressed interest in receiving survivorship care recommendations; some preferred to order late effects surveillance imaging/labs, while others preferred the GREAT clinic team to do so, illustrating the value of two-way communication. Thirteen (76%) patients participated in post-clinic interviews. All stated they would recommend the clinic to others. Common themes from interviews included understanding more about their past treatment and having greater confidence managing their health. Conclusions: The model for facilitating care transitions was highly regarded by young adult cancer survivors and highlights opportunities for improving self-management and care coordination. Future directions include expanding to more cancer types, addressing barriers to primary care follow-up, and exploring shared care or co-management with PCPs.
Association between primary care and acute care services utilization in the year following diagnosis of breast cancer.
Authors: Tran Vincent , Hamal Ruchi , Hu Xiao , Byrne Margaret , Cao Yu
Published: June 2021

e13522

Background: Primary care physicians (PCPs) play a pivotal role during cancer diagnosis. Lack of access to primary care has been linked to worse outcomes including increased mortality in patients with cancer. Higher PCP continuity of care has been associated with lower likelihood of acute care services use among breast cancer survivors, however the impact of PCP utilization is not well studied in those newly diagnosed. This study examines the association between PCP visits and emergency department (ED) use and hospitalization in the year following diagnosis of breast cancer. Methods: Electronic medical records of women newly diagnosed with primary breast cancer from 2013 to 2019 at a single institution (Tufts Medical Center, Boston, Massachusetts) with an established PCP in the same system were retrospectively reviewed. Demographic (age at diagnosis, menopausal status, race/ethnicity), clinical (Charlson Comorbidity Index (CCI), Eastern Cooperative Oncology Group (ECOG) performance status, body mass index, mental health disorder, chronic pain syndrome), and tumor (histology, stage, grade, hormone receptor (HR) positivity, HER2 status) characteristics were extracted in addition to information on treatment modalities (if patient received surgery, radiation (RT), chemotherapy (CT), endocrine therapy (ET), ovarian suppression (OFS)). Univariate and multivariate logistic regression models were used to examine associations between frequency of PCP visits and ED use and hospitalizations within a year after diagnosis of breast cancer. Results: Of 182 women ages 33-93 (mean 60) years old, 131 (72%) were postmenopausal, 116 (64%) Caucasian; 176 (97%) had stages 1-3, and 157 (86%) had HR positivity. In the year following diagnosis, 178 (98%) received surgery, 127 (67%) RT, 142 (78%) ET, 19 (10%) OFS, 70 (39%) CT; 68 (37%) had ≤1 PCP visit, and 45 (25%) had 4-10 PCP visits. Increased PCP visits correlated with advancing age, increased BMI, greater mental health disorders and chronic pain syndromes, and increasing CCI and ECOG score. After adjusting for these confounders and tumor and treatment characteristics, logistic regressions showed that while frequency of PCP visits was not associated with hospitalizations (univariate: OR = 1.02, 95% CI [0.53, 1.62], p = 0.93; multivariate: OR = 0.35, 95% CI [0.05, 1.50], p = 0.184), increased PCP visits tended toward association with increased ED use (univariate: OR = 1.12, 95% CI [0.97,1.29], p = 0.124; multivariate: OR = 1.15, 95% CI [0.94, 1.41], p = 0.188), however did not demonstrate statistical significance. Conclusions: Primary care utilization was not associated with acute care services utilization in women newly diagnosed with breast cancer. Higher PCP utilization tended toward correlation with increased ED use. These findings may help in evaluating multidisciplinary care support in patients newly diagnosed with breast cancer.
Predicting symptom complexity: Using autoregressive integrated moving average (ARIMA) models to create responsive clinic scheduling.
Authors: Watson Linda , Qi Siwei , Deiure Andrea , Link Claire , Hildebrand April , Chmielewski Lindsi , Smith Louise , Ruether Dean , Rawson Krista
Published: June 2021

e13529

Background: Increasing cancer incidence, coupled with a trend in treating patients for longer periods of time, presents challenges in addressing all patients’ symptoms/concerns within the allotted time for ambulatory clinic appointments. Consequently, the ability to forecast and monitor the percentage of cancer patients with different symptom complexity levels is extremely valuable. Symptom complexity is a summary score that weighs the severity of all patient reported symptom scores at one time point. If a clinic could predict how many patients may need more time due to complex symptom management needs, clinic-scheduling templates could be adjusted to include a set number of longer appointments. Methods: Auto Regressive Integrated Moving Average (ARIMA) models were utilized to forecast the percentage of patients with a high symptom complexity level within one cancer clinic in Alberta, Canada. Goodness-of-fit measures such as Bayesian information criterion (BIC) and Ljung-Box test were used to determine optimal form for the ARIMA model. Following model selection, the autocorrelation function (ACF) was performed. These tests together verified that chosen AR, MA and differencing (I) were appropriate. Model performance on the historical data for model fit was summarized by Mean Absolute Error (MAE) and Root Squared Mean Error (RSME). Forecasting accuracy was assessed using mean absolute prediction error by comparing the forecasts with actual clinic data. Results: Of the multiple model structures tested, ARIMA (0, 0, 1) was selected, with the lowest BIC and non-significant Ljung-Box test. We obtained forecasts of the percentage of patients with high symptom complexity levels, with an MAE at 4.0%. To assess forecast accuracy, we calculated the absolute prediction error by comparing the forecasted percentages of patients with high symptom complexity levels to actual clinic visit data and the mean absolute prediction error was 5.9%. Conclusions: This forecasting model has important implications, allowing clinics to adjust scheduling templates to provide a select number of longer timeslots and therefore, be better prepared to meet the symptom management needs of cancer patients who are considered highly complex. This model could be applied to other clinical populations to allow for a tailored scheduling approach based on each clinic’s symptom complexity forecasting.
An assessment of the NAVIFY clinical trial match application using clinical simulation-based research methods.
Authors: Prime Matthew Stewart , Guo Chaohui , Fontana Gianluca , Ghafur Saira , Halligan Jack , Gardner Clarissa
Published: June 2021

e13552

Background: Cancer clinical trials require matching patients to strict, and sometimes lengthy, eligibility criteria. NAVIFY Clinical Trial Match (CTM) is a digital solution that uses data on an individual patient’s condition, genomic alterations and institution’s postal code to automatically find suitable clinical trials. We assessed the efficiency, accuracy and cognitive burden of NAVIFY CTM on matching patients to cancer clinical trials in the UK. Methods: 10 clinicians (8 medical doctors, 2 clinical trial practitioners) participated. Synthetic patient cases were developed with input from two oncologists, a histopathologist and a radiologist. Participants were instructed to identify appropriate trials for five patients using the NAVIFY CTM and five patients with the legacy approach (i.e. online trial databases) within one hour. For each method, participants were advised to approach the exercise with the level of scrutiny employed in a normal clinical setting. The efficiency, quality, and cognitive burden of trial matching was measured for each participant. The quality of trial matches was independently scored by an oncologist who did not participate in the simulations. The cognitive burden was measured subjectively, via a single-item questionnaire used to measure mental effort (Paas scale), and objectively, via Stroop test before and after each method. A survey was also conducted. Results: Efficiency: Participants completed the trial matching more efficiently using NAVIFY CTM, with trial matches completed on average one minute and 42 seconds faster using the digital solution (n = 73 matches) compared with the most commonly used online trial database, ClinicalTrials.gov (n = 52). Participants were more likely to ‘completely agree’ that they had enough time to complete the task using the NAVIFY CTM (70%) compared to online trial databases (40%). Quality of the matches: On the survey, more participants reported that trial suggestions were ‘mostly relevant’ for NAVIFY CTM (70%) compared with ClinicalTrials.gov (30%). The quality of trial matches was the same for both methods (as scored independently by an oncologist). Cognitive burden: On the subjective measure of cognitive burden, more participants required ‘low’ or ‘rather low’ mental effort to use NAVIFY CTM (50%) compared to online trial databases (7%). On the objective measure, there is a seemingly less pronounced Stroop effect (often interpreted as higher mental agility) using NAVIFY CTM vs. legacy approach. Conclusions: Preliminary findings suggest that, compared to online trial databases, the NAVIFY CTM can reduce the amount of time to match patients to clinical trials, provide more relevant trial suggestions, and decrease self-reported mental effort for the decision-maker.
Predicting 180-day mortality for women with ovarian cancer using machine learning and patient-reported outcome data.
Authors: Sidey-Gibbons Chris , Sun Charlotte C. , Xu Cai , Schneider Amy , Lu Sheng-Chieh , Subbiah Ishwaria Mohan , Wright Alexi A. , Meyer Larissa
Published: June 2021

e13555

Background: Contra to national guidelines, women with ovarian cancer often receive aggressive treatment until the end-of-life. We trained machine learning algorithms to predict mortality within 180 days for women with ovarian cancer. Methods: Data were collected data from a single academic cancer institution in the United States. Women with recurrent ovarian cancer completed biopsychosocial patient-reported outcome measures (PROMs) every 90 days. We randomly partitioned our dataset into training and testing samples with a 2:1 ratio. We used synthetic minority oversampling to reduce class imbalance in the training dataset. We fitted training data to six machine learning algorithms and combined their classifications on the testing dataset into a voting ensemble. We assessed the accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve (AUROC) for each algorithm. Results: We recruited 245 patients who completed 1319 assessments. The final voting ensemble performed well across all performance metrics (Accuracy = .79, Sensitivity = .71, Specificity = .80, AUROC = .76). The algorithm correctly identified 25 of the 35 women in the testing dataset who died within 180 days of assessment Conclusions: Machine learning algorithms trained using PROM data offer state-of-the-art performance in predicting whether a woman with ovarian cancer will reach the end-of-life within 180 days. We highlight the importance of PROM data in ML models of mortality. Our model exhibits substantial improvements in prediction sensitivity compared to other similar models trained using electronic health record data alone. This model could inform clinical decision making and improve the uptake of appropriate end-of-life care. Further research is warranted to expand on these findings in a larger, more diverse sample.
Comparing phase 3 “go” decisions (Ph3-GO) between single arm trials with real-world external control (SAT+rwEC) versus randomized phase 2 trials (rPh2).
Authors: Hobbs Brian , Ton Thanh , Li Xiao , Hong David S. , Hubbard Rebecca A. , Mangat Pam K. , Capra William , Kong Shengchun , Pang Herbert , Samant Meghna , Segal Brian D. , Garrett-Mayer Liz
Published: June 2021

e13564

Background: Traditional rPh2 trials have limitations that may yield suboptimal Ph3-GO. Compared to a rPh2 of equivalent sample size, SAT+rwEC allows more patients to receive experimental therapies while preserving the ability to compare experimental and control groups. Bias arising from measurement error and confounding in the rwEC, however, poses challenges to statistical inference. Preliminary studies suggest higher response rates are observed in rwEC than randomized controls. We compared Ph3-GO decisions between SAT+rwEC and rPh2. Methods: Ph3-GO probability was compared using simulation studies that resembled the oncology setting with objective response rate (ORR) endpoint. rPh2 simulated parameters were: sample size (60-120) with 1:1 randomization, ORR in rPh2 control (15%-50%), true treatment effect (ΔORR: 0-50). For each rPh2 of a given sample size, we evaluated an SAT+rwEC that re-allocated all rPh2 control patients to the experimental arm (i.e., doubling the sample size of the experimental arm) and added an rwEC. SAT+rwEC were simulated with assumptions for size (rwEC to SAT ratio: 0.5 to 2) and net bias (-10 to +10), which was simulated as a composite representing ORR measurement error plus residual confounding after multivariable adjustment. Positive direction of net bias corresponds to higher ORR in the rwEC. Ph3-GO thresholds varied from 10-30%. Ph3-GO was considered “False-GO” when true treatment effect < threshold, and “True-GO” when true treatment effect ≥ threshold. Results: With positive net bias of +10, SAT+rwEC had lower False-GO and True-GO decisions compared to rPh2. With negative net bias of -10, both False-GO and True-GO probabilities were higher for the SAT+rwEC. When net bias=0, the increased size of SAT+rwEC resulted in observable Ph3-GO improvements with lower False-GO and higher True-GO than corresponding rPh2. Conclusions: An interactive dashboard was developed for users. The magnitude and direction of net bias relative to the decision threshold affect the performance of SAT+rwEC. The relative sample size of rwEC to rPh2 may also impact performance. The dashboard can provide quantitative guidance for Ph3-GO if net bias can be estimated by independent studies. Further work to quantify net bias and refine Ph3-GO criteria can help reduce the currently high False-GO rates while increasing opportunities for patients to receive experimental therapies through the SAT+rwEC design. Ph3-GO probability for rPh2 vs. SAT+rwEC with threshold=15%, baseline ORR=20% (select scenarios).[Table: see text]
Results from a global survey of clinical cancer researchers on clinical trial design and conduct during the COVID-19 pandemic and beyond.
Authors: De Paula Bruno Henrique Rala , Doherty Gary
Published: June 2021

e13576

Background: The COVID-19 pandemic has had profound detrimental consequences on cancer patient outcomes and clinical cancer research, with considerable adaptations made to both standard care and clinical research to optimise patient safety. Detailed perspectives of clinical researchers on such risk mitigation, and granular insight into which adaptions should persist long term, are required to inform future clinical trial design. Methods: We designed and performed an in depth, global survey (open between 04/22/20 and 06/10/2020) of cancer research professionals to assess the impact of the pandemic on clinical care and research, and how researchers prioritise and view clinical research methodologies. Results: 162 valid responses were received (58.7% oncologists, 14.8% research nurses; 69.1% working in academic centers) from six continents. There was significant heterogeneity in how the pandemic has affected healthcare workers, patients on standard of care or investigational trial treatments, and clinical trial recruitment. Our results detail how trial and non-trial patient care has altered in respondents’ centres and how respondents would prioritise specific trial designs while the pandemic continues. We show marked variance in the perceived value of specific trial protocol features and assessments (regardless of the pandemic). More respondents agreed than disagreed that trial eligibility criteria are too restrictive (48% agreed versus 28% disagreed), that screening assessments generally have unnecessary tests (51% versus 23%), that physical examination should only be performed when clinically indicated (43% versus 30%), that electronic patient outcomes/questionnaires are better at detecting adverse events that a consultation with a study doctor (33% versus 29%), that wearable technology/validated tools for patients to perform self-examination would provide more useful information than vital sign assessment in the study center (48% versus 13%), and that replacing routine in person visits with virtual visits would not significantly compromise patient safety (36% versus 28%). However, 65% of respondents indicated that fully virtual clinical trials (in the absence of reported clinically significant toxicities) would not be sufficiently safe (versus 15% who indicated that they would be). Conclusions: These detailed data provide further evidence of a significant adverse impact of the pandemic on cancer patient care and drug development, may help inform risk mitigation for studies in times of heightened infection risk, and aid with future clinical trial design.