bluuebunny/crossref_metadata_2025_split huggingface dataset:
The percentage of unnecessary mastectomy due to false size prediction by preoperative imaging studies in patients with breast cancer who underwent neoadjuvant chemotherapy.
Authors: Han Yireh , Han Wonshik 
Published: June 2022

573 Background: It was shown that, with neoadjuvant chemotherapy (NCT), about 40-50% of breast conserving surgery (BCS) ineligible breast cancer converted to BCS-eligible. Because the estimated tumor extent with imaging after NCT tend to be discordant with pathologic extent, we assumed that proportion of unnecessary total mastectomy (TM) might be greater in NCT patients compared with non-NCT patients. We aimed to determine the proportion of TM for potential BCS candidate due to false size prediction after NCT and factors affecting that. Methods: We prospectively enrolled patients with invasive breast cancer (Stage II or III) who were scheduled for TM from 2018 to 2021 at Seoul National University Hospital (SNUH). Patients who were determined to undergo TM by only patient’s preference, who had BRCA1/2 mutation, multicentric cancer, diffuse malignant calcification over more than a quadrant, and inflammatory cancer were excluded. The decision of TM was done by operating surgeon considering the tumor extent, location, and breast size. Breast imaging including mammography, ultrasonography (USG), and MRI were done in patients. Before surgery, each surgeon recorded a hypothetic maximum tumor size (HMS) that the surgeon would have been able to try BCS if the patient had actually less than that size of tumor at that location in the patient. After operation, the HMS was compared with final pathologic total extent of the tumor including invasive and in situ cancer. In SNUH, decisions and tries of BCS led to eventual BCS with negative margin in 97.4% of patients during same period with this study. Results: Among 360 patients enrolled, 130 were patients who underwent NCT, and 230 were chemotherapy naïve as a control group. 62 of 130 (52.3%) in the NCT group and 49 of 230 (21.3%) in the non-NCT group were found to have smaller tumor extent than the pre-recorded HMS, respectively (NCT vs non-NCT p-value <0.001). Further analyses were done only for NCT group. In an analysis according to subtype, the proportion of TM with false size prediction were more in HER2-positve (63.3%) and triple-negative breast cancer (TNBC) (57.6%) than in ER-positive/HER2-negative breast cancer (25.0%) (p-value <0.001). In an imaging analysis, MRI size were larger than HMS in 73.8% of all patients. Both MRI-pathology size and USG-pathology size discrepancies were significantly associated with false decision of TM (both p<0.001), but not with mammography. Without MRI, the false decision would have been reduced by 26.1%. Conclusions: We found that 52.3% of patients who received TM after NCT were actually BCS eligible, which was significantly higher than non-NCT patients. The proportion of false prediction were more in HER2-positive and TNBC. MRI imaging contributed to false size prediction and subsequent TM for BCS eligible patients. Clinical trial information: NCT04689529.
NOHA: A sensitive, low-cost, and accessible blood-based biomarker to determine breast cancer estrogen receptor status in low-resource settings.
Authors: Mohan Srinidi , Musyoka Augustine , Guthikonda Divya , Saunders Jamie , Girata Lora , Mremi Alex , Serventi Furaha , Mbaga Blandina , Patrick Elizabeth , Jones Michael A , Emery Ivette F. , Lucas Frances L. , Miesfeldt Susan 
Published: June 2022

580 Background: Significant challenges to breast cancer control in low- and middle-income countries (LMICs) include late-stage disease presentation because of few/no early detection programs, inadequately staffed and equipped pathology laboratories, and constrained treatment options. Estrogen receptor (ER) expression is critical to determining candidacy for cost efficient and accessible hormonal agents in LMICs; however, access to standard immunohistochemistry (IHC)-based ER analysis is grossly limited/nonexistent due to cost and technical requirements. We have identified Nw-hydroxy-L-Arginine (NOHA) as a low cost and accessible blood-based biomarker to distinguish estrogen-receptor negative (ER–) from estrogen-receptor positive (ER+) breast cancer, differentiate ER– high grade versus low grade tumors, and correlate ER– molecular phenotype with ethnic variation. Our studies with US patients suggest the NOHA threshold of <4nM as a reliable indicator of ER– versus ER+ disease (Table 1). Here we examine the clinical utility of NOHA as an alternative to IHC in distinguishing ER– from ER+ breast tumors in Tanzanian patients. Methods: Following informed consent, 70 newly diagnosed breast cancer patients were recruited at Kilimanjaro Christian Medical Center (KCMC; Moshi, Tanzania). Prior to any treatment, a needle prick amount of blood was collected from each patient on a Noviplex plasma card (Shimadsu, U.S.) and stored at -80˚C. Plasma cards and unstained tumor pathology slides were shipped at 2-3 months intervals to US labs for NOHA and immunohistochemistry (IHC) ER testing. Statistical difference was set at p<0.01, with NOHA and IHC assay operators blinded to patient clinical status. Results: Our early data show correlation between NOHA levels and ER IHC results, providing a means to distinguish ER– from ER+ breast cancer in the low-resource setting. Plasma cards stored at -80˚C for up to 3 months retained NOHA stability in assays involving a proprietary antibody-based ELISA, and by LC-MS. Conclusions: This study suggests the clinical utility of NOHA as a cost-effective, accessible replacement for standard IHC testing in determining ER status among breast cancer patients in LMICs, promising to extend access to cost efficient and available hormonal agents and improving outcomes and quality of life. The present study provides foundational knowledge for broader studies of NOHA utility in global breast cancer control, as well as in ongoing development of NOHA rapid-testing technologies. [Table: see text]
Collaborative federated learning behind hospitals’ firewalls for predicting histological complete response to neoadjuvant chemotherapy in triple-negative breast cancer.
Authors: Ogier du Terrail Jean , Leopold Armand , Joly Clément , Andreux Mathieu , Maussion Charles , Schmauch Benoit , Zaslavskiy Mikhail , Wainrib Gilles , Milder Maud , Gervasoni Julie , Guérin Julien , Durand Thierry , Livartowski Alain , Moutet Kelvin , Gautier Clément , Moisson Anne-Laure , Marini Camille , Galtier Mathieu , Heudel Pierre Etienne , Bataillon Guillaume 
Published: June 2022

590 Background: Triple-Negative Breast Cancer (TNBC) is characterized by high metastatic potential and poor prognosis with limited treatment options. Neoadjuvant chemotherapy (NACT) is the standard of care in non-metastastic setting due to the ability to assess pathologic responses providing important prognostic information and guidance in adjuvant therapy decisions. However, the histological response heterogeneity is still poorly understood. We investigate the use of Machine Learning (ML) to predict from diagnosis Whole-Slide Images (WSI) of early TNBC the positive histological Complete Response (pCR) to NACT on surgical specimens. To overcome the known biases of small scale studies while respecting data privacy, we conduct a study in a multi-centric fashion behind hospitals’ firewalls using collaborative Federated Learning (FL). Thereby allowing access to enough TNBC data to sustain a complete response heterogeneity investigation. Methods: We collected in both comprehensive cancer centers: Centre Léon Bérard (A)(n=99) and Institut Curie (B) (n=420), WSI of biopsies performed at diagnosis and relevant clinical variables. We use traditional Multiple Instance Learning pipelines by tiling the matter on each WSI with a pre-trained Neural Network (NN). We train a second NN to predict the NACT pCR using the mean feature of each WSI. ML trainings are performed using either one cohort in isolation (NN Local) or both cohorts using FL. We compare the performance of this federated WSI based model to the best clinical model (Clin.) simulating clinical practice (using grade and Tumor-Infiltrating Lymphocytes (TILs) percentage) on both centers. Results: Performance of models to predict NACT pCR (AUC). All results are evaluated in 5 repeated 4-folds cross validations. Conclusions: The final ML model, that was trained in a privacy preserving fashion on both hospitals, provides better prediction of NACT pCR than current clinical standards. This study shows that 1. Not all relevant information is routinely extracted from WSI and 2. Non simulated FL is possible in Healthcare and gives better results than siloed studies on open medical questions. Additional interpretability results of the model show that it has re-discovered known biomarkers such as TILs and apocrine tumor cells without any tile-level annotation, and hints at potential new biomarkers. [Table: see text]
Artificial intelligence (AI)–powered spatial analysis of tumor-infiltrating lymphocytes (TIL) for prediction of response to neoadjuvant chemotherapy (NAC) in triple-negative breast cancer (TNBC).
Authors: Lee Hee Jin , Cho Soo Yoon , Cho Eun Yoon , Lim Yoojoo , Cho Soo Ick , Jung Wonkyung , Song Sanghoon , Kang Mingu , Ryu Jeongun , Ma Minuk , Park Seonwook , Paeng Kyunghyun , Ock Chan-Young , Song Sang Yong , Gong Gyungyub 
Published: June 2022

595 Background: Stromal TIL are a well-recognized prognostic and predictive biomarker in breast cancer. There is a need for tools assisting visual assessment of TIL, to improve reproducibility as well as for convenience. This study aims to assess the clinical significance of AI-powered spatial TIL analysis in the prediction of pathologic complete response (pCR) after NAC in TNBC patients. Methods: H&E stained slides and clinical outcomes data were obtained from stage I – III TNBC patients treated with NAC in two centers in Korea. For spatial TIL analysis, we used Lunit SCOPE IO, an AI-powered H&E Whole-Slide Image (WSI) analyzer, which identifies and quantifies TIL within the cancer or stroma area. Lunit SCOPE IO was developed with a 13.5 x 109 micrometer2 area and 6.2 x 106 TIL from 17,849 H&E WSI of multiple cancer types, annotated by 104 board-certified pathologists. iTIL score and sTIL score were defined as area occupied by TIL in the intratumoral area (%) and the surrounding stroma (%), respectively. Immune phenotype (IP) of each slide was defined from spatial TIL calculation, as inflamed (high TIL density in tumor area), immune-excluded (high TIL density in stroma), or desert (low TIL density overall). Results: A total of 954 TNBC patients treated from 2006 to 2019 were included in this analysis. pCR (ypT0N0) was confirmed in 261 (27.4%) patients. The neoadjuvant regimens used were mostly anthracycline (97.8%) and taxane (75.1%) -based, with 116 (12.1%) patients receiving additional platinum and 41 (4.3%) patients treated as part of immune checkpoint inhibitor or PARP inhibitor clinical trials. The median iTIL score and sTIL score were 4.3% (IQR 3.2 – 5.8) and 8.1% (IQR 6.3 – 13.4), respectively. The mean iTIL score was significantly higher in patients who achieved pCR after NAC (5.8% vs. 4.5%, p < 0.001), and a similar difference was observed with sTIL score (12.1%.1 vs. 9.4%, p < 0.001). iTIL score was found to remain as an independent predictor of pCR along with cT stage and Ki-67 in the multivariable analysis (adjusted odds ratio 1.211 (95% CI 1.125 – 1.304) per 1 point (%) change in the score, p <0.001). By IP groups, 291 (30.5%) patients were classified as inflamed, 502 (52.6%) as excluded, and 161 (16.9%) as desert phenotype. The patients with inflamed phenotype were more likely to achieve pCR (44.7%) than other phenotypes (19.8%, p < 0.001). Conclusions: AI-powered spatial TIL analysis could assess TIL densities in the cancer area and surrounding stroma of TNBC, and TIL density scores and IP classification could predict pCR after NAC.
Does race influence long-term outcomes after neoadjuvant chemotherapy in breast cancer: A National Cancer Database analysis.
Authors: Roy Arya Mariam , Jiang Changchuan , Yao Song , Perimbeti Stuthi , Gandhi Shipra 
Published: June 2022

606 Background: Pathologic complete response (pCR) after neoadjuvant chemotherapy (NACT) is a surrogate predictor for long-term survival in breast cancer (BC). Patients who attain pCR have improved relapse-free and overall survival (OS) when compared to patients with residual disease (RD). We examined the pCR in Black and White BC patients who received NACT and their OS after attaining pCR and RD. Methods: The National Cancer Database (NCDB) was queried for Black and White females with non-metastatic BC from the years 2010 – 2016 who received NACT. Logistic regression was used to analyze pCR/RD and Cox proportional hazards regression to analyze OS, with adjustment for age, race, stage, grade, body mass index, treatments received, insurance status and comorbidities. STATA/IC 16.0 was used for analysis and a two-sided p-value < 0.05 was considered significant. Results: A total of 101,014 White and Black BC patients were identified, including 24,852 (Whites - 74.43%, Black - 25.57%) triple negative breast cancer (TNBC), 51,043 (Whites - 84%, Blacks - 16%) hormone receptor positive HER2 negative (HR+HER2-) and 17,818 (Whites - 83%, Blacks - 17%) HER2 positive. Whites had a slightly higher odds of attaining pCR compared to Blacks (adjusted Odds Ratio (aOR) = 1.040, 95% Confidence Interval (CI) = 1.02 - 1.19, p = 0.02). The difference was largest in TNBC subtype (TNBC: aOR = 1.34, 95% CI = 1.20 - 1.56, p < 0.001; HR+HER2-: aOR = 1.1; 95% CI = 1.02 - 1.32, p = 0.038; HER2+: aOR = 1.13, 95% CI = 1.08 - 1.27, p < 0.001). Among those who attained pCR, Blacks had worse OS when compared to Whites in HER2+ subtype (adjusted Hazard Ratio (aHR) = 1.41, 95% CI = 1.04 - 1.93, p = 0.028) but not in TNBC or HR+HER2- subtypes. Among those with RD, Blacks had worse OS in the whole cohort compared to Whites (aHR = 1.43, 95% CI = 1.26 - 1.58, p < 0.001), and in all subtypes: TNBC (aHR = 1.17, 95% CI = 1.11 - 1.23, p < 0.001), HR+HER2- (aHR = 1.38, 95% CI = 1.31 - 1.45, p < 0.001) and HER2+ (aHR = 1.45, 95% CI = 1.32 - 1.59, p < 0.001). Conclusions: Black BC patients with TNBC were less likely to achieve pCR than Whites after NACT. When Black patients with HER2+ subtype did attain pCR, they still had worse OS than Whites. The same racial difference in OS was observed in all BC subtypes - TNBC, HR+HER2- and HER2+ among patients with RD. This highlights the importance to investigate novel personalized treatment strategies for Black patients.
State public welfare spending and racial/ethnic disparities in overall survival among adults with cancer.
Authors: Barnes Justin Michael , Johnston Kenton J , Osazuwa-Peters Nosayaba 
Published: June 2022

6509 Background: State public welfare spending may partially address social determinants of health and mitigate structural racism. However, its association with racial and ethnic disparities and overall survival for newly diagnosed patients with cancer is unknown. Methods: Adults ages 18 and older with a new cancer diagnosis from 2007-2016 were queried from the Surveillance, Epidemiology, and End Results program. Annual state spending data were obtained from the US Census Bureau. We evaluated the association of 5-year overall survival (OS) and public welfare spending using cluster-robust regression. Analyses were conducted overall, by race and ethnicity, and by cancer site. To determine whether public welfare spending was associated with changes in racial and ethnic disparities in survival, we additionally assessed for interaction effects between public welfare spending and race and ethnicity. Analyses were adjusted for covariates including age, sex, metropolitan residence, state, county-level income and education, insurance status, cancer site, stage at diagnosis, and year of diagnosis. Sensitivity analyses were conducted also accounting for state Medicaid expansion effects and state spending on health care and hospitals. Results: A total of 2,925,550 individuals were identified in our cohort. 5-year OS was 10.6% lower in non-Hispanic Black vs. White patients. Public welfare spending was not associated with 5-year OS overall (0.25 % per 10% increase in spending, -1.47 to 1.96, p =.78) or for non-Hispanic White patients (0.52% per 10% increase in spending, 95% CI -1.30 to 2.33, p =.58). However, increased public welfare spending was associated with increased 5-year OS among non-Hispanic Black patients (2.02% per 10% increase in spending, 95% CI = 0.01 to 4.03, p =.049). There was a 4.46% (95% CI = 2.63 to 6.30, pinteraction<.001) narrowing of the 5-year OS disparity in non-Hispanic Black relative to White patients per 10% increase in spending, or a 42% closure of the 10.6% OS disparity. Specifically, increased public welfare spending was associated with a narrowed Black vs. White 5-year OS disparity for patients with breast (7.50% increase in 5-yr OS for non-Hispanic Black relative to White per 10% increasing in spending, corresponding to closing 42.1% of the disparity), cervical (12.2%, 45.9%), colorectal (3.37%, 44.9%), head and neck (8.23%, 35.7%), liver (4.54%, 44.8%), lung (1.76%, 63.3%), ovarian (6.43%, 35.9%), prostate (2.89%, 41.9%), bladder (7.62%, 42.9%), and uterine cancers (14.9%, 40.9%). Results were similar after accounting for state health care and hospital spending and state Medicaid expansion effects. Conclusions: State investment in public welfare was associated with improved 5-year OS for non-Hispanic Black individuals with cancer, decreasing racial disparities in cancer outcomes overall and for many cancer sites.
Racial and socioeconomic disparities in telemedicine use among US patients initiating cancer treatment during the COVID-19 pandemic.
Authors: Guadamuz Jenny , Wang Xiaoliang , Royce Trevor Joseph , Calip Gregory Sampang 
Published: June 2022

6511 Background: The COVID-19 pandemic was associated with declines in in-person clinical visits. While telemedicine visits have increased, uptake has varied. Here we assess demographic and socioeconomic factors associated with telemedicine use among patients initiating treatment for 21 common cancers at community oncology clinics. Methods: This retrospective study uses the nationwide Flatiron Health electronic health record-derived de-identified database of patients with cancer. Patient characteristics were determined using structured and unstructured data curated via technology-enabled abstraction. We included patients (≥ 18 years) who initiated first-line cancer treatment between March 2020 and September 2021 (follow-up through December 2021). We focused on differences in telemedicine use (≥ 1 telemedicine visit within 90 days after treatment initiation) across race/ethnicity, insurance coverage, rurality (per Rural-Urban Commuting Areas), and socioeconomic status (SES). SES was defined using census block group data from the American Community Survey (2015-2019) (quintiles representing least to most affluent areas) based on patient addresses and measured using the Yost Index (incorporating income, home values, rental costs, poverty, blue-collar employment, unemployment, and education information). We used logistic regression models adjusted for clinical characteristics ( i.e., age, sex, performance status, and stage) to examine differences in telemedicine use. Results: This study included 24,164 patients (48.1% women, median age: 69 [interquartile range: 61-77] years), of whom 15.9% used telemedicine services. Black patients were less likely to use telemedicine services than White patients (11.4% vs. 15.6%, odds ratio [OR] 0.69 [95% confidence interval [CI]: 0.59-0.79], p<0.01). Telemedicine use was also lower among patients without documented insurance than well-insured (commercial and Medicare payers) patients (10.7% vs. 15.9%, OR 0.62 [95% CI: 0.54-0.72], p<0.01). Those in rural (9.8%, OR 0.51 [95% CI: 0.45-0.58], p<0.01) and suburban areas (13.1%, OR 0.71 [95%: 0.64-0.79], p<0.01) were less likely to use telemedicine services than patients in urban areas (17.6%). Finally, patients in the least affluent areas had lower telemedicine use than those in the most affluent areas (10.2% vs. 24.3%, OR 0.35 [95% CI: 0.31-0.40], p<0.01). Conclusions: During the COVID-19 pandemic, nearly one-fifth of patients initiating cancer treatment used telemedicine services. However, there were substantial disparities: Black, uninsured, non-urban, and less affluent patients are less likely to use telemedicine services. While telemedicine may expand access to specialty care, the proliferation of these services may widen cancer care disparities if vulnerable populations do not have equitable access.
Survival among patients with multiple myeloma in the U.S. military health system compared to the Surveillance, Epidemiology, and End Results (SEER) program.
Authors: Dew Alexander , Darmon Sarah , Lin Jie , Ware Jason , Roswarski Joseph Lee , Shriver Craig D , Zhu Kangmin , Chiu Alden Vincent 
Published: June 2022

6524 Background: Multiple myeloma (MM) is the second most common hematologic malignancy and remains incurable despite therapeutic advances. The US Military Health System (MHS) provides universal healthcare to beneficiaries and has been associated with improved survival across multiple malignancies. It is unknown whether access to universal healthcare via the MHS translates to improved survival for MM patients. We sought to answer this question by comparing survival data from the Department of Defense’s Automated Central Tumor Registry (ACTUR) and the NCI’s SEER database. Methods: Patients 18 years and older diagnosed with histologically confirmed MM between 1987-2013 were identified in ACTUR (N=1,488) and SEER (N=2,976) databases. Two SEER patients were matched to an ACTUR patient by age group, sex, race, and diagnosis year group. Five and 10-year survival was compared between ACTUR and SEER patients using Kaplan-Meier curves and log-rank tests. Cox proportional hazard model was used to estimate hazard ratios (HR) and 95% confidence intervals (95% CI) adjusted for potential confounders of age at diagnosis, sex, race and diagnosis year. The proportional hazards assumption for the analysis was assessed with log-log survival curves. Results: Median survival in the ACTUR patients was 47.1 months (95% CI: 43.9-50.4) compared to 33.0 months (95% CI: 32.0-35.0) in the SEER group. Five and 10-year survival was superior in patients from the ACTUR group compared to the SEER group with an aHR of 0.74 (95% CI: 0.68-0.81) and 0.79 (95% CI: 0.74-0.85) after adjustment for potential confounders, respectively. The survival advantage of ACTUR patients was preserved when stratified by age, sex, race, and diagnosis year. Conclusions: Patients treated with MM in the MHS had superior 5 and 10-year overall survival when compared to the general population. This benefit remained despite age, sex, race, and diagnosis year. Our study findings suggest the benefits of universal healthcare provided by the MHS improve survival among MM patients. Further research is warranted to delineate factors which improve survival and reduce disparity in the treatment of MM patients.[Table: see text]