Medicaid Expansion Increases Access for Rural and Impoverished Patients with Pancreatic Ductal Adenocarcinoma in Southern States.

INTRODUCTION: Medicaid expansion (ME) impacted patients when assessed at a national level. However, of the 32 states in which Medicaid expansion occurred, only 3 were Southern states. Whether results apply to Southern states that share similar geopolitical perspectives remains elusive. We aimed to assess the impact of ME on pancreatic ductal adenocarcinoma (PDAC) treatment in eight Southern states in the USA. PATIENTS AND METHODS: We identified uninsured or Medicaid patients (age 40-64 years) diagnosed with PDAC between 2011 and 2018 in Southern states from the North American Association of Central Cancer Registries-Cancer in North America (NAACCR-CiNA) research dataset. Medicaid-expanded states (MES; Louisiana, Kentucky, and Arkansas) were compared with non-MES (NMES; Tennessee, Alabama, Mississippi, Texas, and Oklahoma) using multivariate logistic regression. P < 0.05 was considered statistically significant. RESULTS: Among 3036 patients, MES significantly increased odds of Medicaid insurance by 36%, and increased proportions of insured Black patients by 3.7%, rural patients by 3.8%, and impoverished patients by 18.4%. After adjusting for age, race, rural-urban status, poverty status, and summary stage, the odds of receiving radiation therapy decreased by 26% for each year of expansion in expanded states (P = 0.01). Last, ME did not result in a significant difference between MES and NMES in diagnosing early stage disease (P = 0.98) nor in receipt of chemotherapy or surgery (P = 0.23 and P = 0.63, respectively). CONCLUSIONS: ME in Southern states increased insurance access to traditionally underserved groups. Interestingly, ME decreased the odds of receiving radiation therapy yearly and had no significant impact on receipt of chemotherapy or surgery.

Deep learning uncertainty quantification for clinical text classification.

INTRODUCTION: Machine learning algorithms are expected to work side-by-side with humans in decision-making pipelines. Thus, the ability of classifiers to make reliable decisions is of paramount importance. Deep neural networks (DNNs) represent the state-of-the-art models to address real-world classification. Although the strength of activation in DNNs is often correlated with the network's confidence, in-depth analyses are needed to establish whether they are well calibrated. METHOD: In this paper, we demonstrate the use of DNN-based classification tools to benefit cancer registries by automating information extraction of disease at diagnosis and at surgery from electronic text pathology reports from the US National Cancer Institute (NCI) Surveillance, Epidemiology, and End Results (SEER) population-based cancer registries. In particular, we introduce multiple methods for selective classification to achieve a target level of accuracy on multiple classification tasks while minimizing the rejection amount-that is, the number of electronic pathology reports for which the model's predictions are unreliable. We evaluate the proposed methods by comparing our approach with the current in-house deep learning-based abstaining classifier. RESULTS: Overall, all the proposed selective classification methods effectively allow for achieving the targeted level of accuracy or higher in a trade-off analysis aimed to minimize the rejection rate. On in-distribution validation and holdout test data, with all the proposed methods, we achieve on all tasks the required target level of accuracy with a lower rejection rate than the deep abstaining classifier (DAC). Interpreting the results for the out-of-distribution test data is more complex; nevertheless, in this case as well, the rejection rate from the best among the proposed methods achieving 97% accuracy or higher is lower than the rejection rate based on the DAC. CONCLUSIONS: We show that although both approaches can flag those samples that should be manually reviewed and labeled by human annotators, the newly proposed methods retain a larger fraction and do so without retraining-thus offering a reduced computational cost compared with the in-house deep learning-based abstaining classifier.

Survival paradox between stage IIB/C and stage IIIA colon cancer: is it time to revise the American Joint Committee on Cancer TNM system?

INTRODUCTION: A survival paradox between T4N0 (Stage IIB/IIC) and Stage IIIA colon cancer exists, even after adjusting for adequate lymph node (LN) retrieval and receipt of adjuvant chemotherapy (C). We conducted a large hospital-based study to re-evaluate this survival paradox based on the newest 8th edition staging system. METHODS: The National Cancer Data Base was queried to evaluate 35,606 patients diagnosed with Stage IIB, IIC, and IIIA colon cancer between 2010 and 2017. The Kaplan-Meier method and log-rank test were used to compare unadjusted overall survival (OS). Multivariable Cox proportional hazards model was used to determine the association of stage with hazard ratios adjusted for relevant demographic and clinical variables including ≥ 12 LNs retrieved and receipt of adjuvant chemotherapy. P value < 0.05 was considered statistically significant. RESULTS: The 5-year OS for optimally treated stage IIIA colon cancer (receipt of C) was 84.3%, which was significantly higher than stage IIB/C (≥ 12 LNs retrieved + C) (72.8%; P < 0.0001). Stage was an independent predictor of OS. Among optimally treated Stage IIIA patients, T1N1 had the best survival (90.6%) while stage T4bN0 (stage IIC) had the worst (70.9%) (P < 0.0001). Compared to stage IIB, stage IIC had a 17% increased risk of overall death while stage IIIA had a 21% reduction in death (P < 0.0001). CONCLUSION: Stage IIB/C and Stage IIIA survival paradox persists even after accounting for receipt of adjuvant chemotherapy and adequate lymph node retrieval. Future iteration of the TNM system should take this paradox into consideration.

Functional Outcomes After Localized Prostate Cancer Treatment.

Importance: Adverse outcomes associated with treatments for localized prostate cancer remain unclear. Objective: To compare rates of adverse functional outcomes between specific treatments for localized prostate cancer. Design, Setting, and Participants: An observational cohort study using data from 5 US Surveillance, Epidemiology, and End Results Program registries. Participants were treated for localized prostate cancer between 2011 and 2012. At baseline, 1877 had favorable-prognosis prostate cancer (defined as cT1-cT2bN0M0, prostate-specific antigen level <20 ng/mL, and grade group 1-2) and 568 had unfavorable-prognosis prostate cancer (defined as cT2cN0M0, prostate-specific antigen level of 20-50 ng/mL, or grade group 3-5). Follow-up data were collected by questionnaire through February 1, 2022. Exposures: Radical prostatectomy (n = 1043), external beam radiotherapy (n = 359), brachytherapy (n = 96), or active surveillance (n = 379) for favorable-prognosis disease and radical prostatectomy (n = 362) or external beam radiotherapy with androgen deprivation therapy (n = 206) for unfavorable-prognosis disease. Main Outcomes and Measures: Outcomes were patient-reported sexual, urinary, bowel, and hormone function measured using the 26-item Expanded Prostate Cancer Index Composite (range, 0-100; 100 = best). Associations of specific therapies with each outcome were estimated and compared at 10 years after treatment, adjusting for corresponding baseline scores, and patient and tumor characteristics. Minimum clinically important differences were 10 to 12 for sexual function, 6 to 9 for urinary incontinence, 5 to 7 for urinary irritation, and 4 to 6 for bowel and hormone function. Results: A total of 2445 patients with localized prostate cancer (median age, 64 years; 14% Black, 8% Hispanic) were included and followed up for a median of 9.5 years. Among 1877 patients with favorable prognosis, radical prostatectomy was associated with worse urinary incontinence (adjusted mean difference, -12.1 [95% CI, -16.2 to -8.0]), but not worse sexual function (adjusted mean difference, -7.2 [95% CI, -12.3 to -2.0]), compared with active surveillance. Among 568 patients with unfavorable prognosis, radical prostatectomy was associated with worse urinary incontinence (adjusted mean difference, -26.6 [95% CI, -35.0 to -18.2]), but not worse sexual function (adjusted mean difference, -1.4 [95% CI, -11.1 to 8.3), compared with external beam radiotherapy with androgen deprivation therapy. Among patients with unfavorable prognosis, external beam radiotherapy with androgen deprivation therapy was associated with worse bowel (adjusted mean difference, -4.9 [95% CI, -9.2 to -0.7]) and hormone (adjusted mean difference, -4.9 [95% CI, -9.5 to -0.3]) function compared with radical prostatectomy. Conclusions and Relevance: Among patients treated for localized prostate cancer, radical prostatectomy was associated with worse urinary incontinence but not worse sexual function at 10-year follow-up compared with radiotherapy or surveillance among people with more favorable prognosis and compared with radiotherapy for those with unfavorable prognosis. Among men with unfavorable-prognosis disease, external beam radiotherapy with androgen deprivation therapy was associated with worse bowel and hormone function at 10-year follow-up compared with radical prostatectomy.

Rural versus urban commuting patients with stage III colon cancer: is there a difference in treatment and outcome?

BACKGROUND: To evaluate if there are differences in outcomes for patients with stage III colon cancer in those from urban vs. rural commuting areas. METHODS: Data were evaluated on patients diagnosed with stage III colon cancer between 2012 and2018 from the Louisiana Tumor Registry. Patients were classified into rural and urban groups. Data on overall survival, time from diagnosis to surgery and time from surgery to chemotherapy, and sociodemographic factors (including race, age, and poverty level) were recorded. RESULTS: Of 2652 patients identified, 2159 were urban (81.4%) and 493 rural (18.6%). No age difference between rural and urban patients (p = 0.56). Stage IIIB accounted for 66.7%, followed by IIIC (21.6%) and IIIA (11%), with a significant difference between rural and urban patients based on stage (p = 0.02). There was no difference in the extent of surgery (p = 0.34) or tumor size (p = 0.72) between urban and rural settings. No difference in undergoing chemotherapy (p = 0.12). There was a statistically significant difference in receiving timely treatment for hospital volume (p < 0.0001) and poverty level (p < 0.0001), but no difference in time from diagnosis to surgery (p = 0.48), and time from surgery to chemotherapy (p = 0.27). Non-Hispanic Blacks were less likely to receive timely treatment when compared with non-Hispanic Whites for both surgery and adjuvant chemotherapy, (aHR 0.91, 95% CI 0.83-0.99) and (aHR 0.86, 95% CI 0.77-0.97), respectively. There was no difference in Kaplan-Meier overall survival curves comparing rural vs. urban patients (p = 0.77). CONCLUSIONS: There was no statistical difference in overall survival, time to surgery, and time to adjuvant chemotherapy between rural and urban patients with Stage III colon cancer.

Geographic determinants of colorectal cancer in Louisiana.

PURPOSE: Currently, rural residents in the United States (US) experience a greater cancer burden for tobacco-related cancers and cancers that can be prevented by screening. We aim to characterize geographic determinants of colorectal cancer (CRC) incidence in Louisiana due to rural residence and other known geographic risk factors, area socioeconomic status (SES), and cultural region (Acadian or French-speaking). METHODS: Primary colorectal cancer diagnosed among adults 30 years and older in 2008-2017 were obtained from the Louisiana Tumor Registry. Population and social and economic data were obtained from US Census American Community Survey. Rural areas were defined using US Department of Agriculture 2010 rural-urban commuting area codes. Estimates of relative risk (RR) were obtained from multilevel binomial regression models of incidence. RESULTS: The study population was 16.1% rural, 18.4% low SES, and 17.9% Acadian. Risk of CRC was greater among rural white residents (RR Women: 1.09(1.02-1.16), RR Men: 1.11(1.04-1.18)). Low SES was associated with increased CRC for all demographic groups, with excess risk ranging from 8% in Black men (RR: 1.08(1.01-1.16)) to 16% in white men (RR: 1.16(1.08-1.24)). Increased risk in the Acadian region was greatest for Black men (RR: 1.21(1.10-1.33)) and women (RR: 1.21(1.09-1.33)). Rural-urban disparities in CRC were no longer significant after controlling for SES and Acadian region. CONCLUSION: SES remains a significant determinant of CRC disparities in Louisiana and may contribute to observed rural-urban disparities in the state. While the intersectionality of CRC risk factors is complex, we have confirmed a robust regional disparity for the Acadian region of Louisiana.

Impact of diabetes and modifiable risk factors on pancreatic cancer survival in a population-based study after adjusting for clinical factors.

PURPOSES: Our study aimed to examine the impact of diabetes, smoking and BMI on pancreatic cancer survival in a population-based setting by adjusting both sociodemographic and clinical factors and measuring their attributable risk. METHODS: Data on pancreatic adenocarcinoma patients diagnosed in 2011-2017 were acquired from the Louisiana Tumor Registry. Diabetes, smoking, height, and weight were abstracted from medical records and linked with Hospital Inpatient Discharge Data to enhance the completeness of the diabetes data. The Cox regression model was used to assess effect sizes of diabetes, smoking, and BMI on cancer-specific survival and survival rate. The partial population attributable risk was employed to measure the attributable risk of these risk factors. RESULTS: Of the 3,200 eligible patients, 34.6% were diabetics, 23.9% were current smokers, and 52.3% had BMI ≥ 25 kg/m2. After adjusting for sociodemographic and clinical factors, diabetic patients had an increased cancer-specific death risk of 15% (95% CI, 1.06-1.25), 36% (95% CI, 1.19-1.44) for current smokers, and 24% (95% CI, 1.00-1.54) for patients with a BMI ≥ 40 when compared to their counterparts. Diabetic current smokers had significantly lower 2- and 3-year adjusted cancer-specific survival rates, 13.1% and 10.5%, respectively. By eliminating diabetes and modifiable risk factors, an estimated 16.6% (95% CI, 6.9%-25.9%) of the cancer-specific deaths could be avoided during a nine-year observational period between 2011 and 2019. CONCLUSIONS: Diabetes and smoking contributed substantially to the reduction of pancreatic cancer survival even after controlling for sociodemographic and clinical factors; however, BMI ≥ 35 was observed to increase risk of mortality among stage III-IV patients only.

Patient-reported Outcomes After External Beam Radiotherapy With Low Dose Rate Brachytherapy Boost vs Radical Prostatectomy for Localized Prostate Cancer: Five-year Results From a Prospective Comparative Effectiveness Study.

PURPOSE: Data comparing radical prostatectomy and external beam radiation therapy with low dose rate brachytherapy boost are lacking. To better guide shared decision making regarding treatment, we compared patient reported outcomes through 5 years following radical prostatectomy or external beam radiation therapy with low dose rate brachytherapy boost for localized prostate cancer. MATERIALS AND METHODS: From 2011-2012, men aged <80 years with localized prostate adenocarcinoma were enrolled and followed longitudinally. Patient reported outcomes included the Expanded Prostate Index Composite. Regression models adjusted for baseline scores and covariates were constructed. RESULTS: The study population included 112 men treated with external beam radiation therapy with low dose rate brachytherapy boost and 1,553 treated with radical prostatectomy. Compared to radical prostatectomy, external beam radiation therapy with low dose rate brachytherapy boost was associated with clinically meaningful worse urinary irritative/obstructive (adjusted mean score difference [95% confidence interval]: 5.0 [-8.7, -1.3]; P = .008 at 5 years) and better urinary incontinence function (13.3 [7.7, 18.9]; P < .001 at 5 years) through 5 years. Urinary function bother was similar between groups (P > .4 at all timepoints). Treatment with external beam radiation therapy with low dose rate brachytherapy boost was associated with worse bowel function (-4.0 [-6.9, -1.1]; P = .006 at 5 years) through 5 years compared to radical prostatectomy. Treatment with external beam radiation therapy with low dose rate brachytherapy boost was associated with better sexual function at 1 year (12.0 [6.5, 17.5]; P < .001 at 1 year) compared to radical prostatectomy, but there was insufficient evidence to reject the supposition that no difference was seen at 3 or 5 years. CONCLUSIONS: Compared to radical prostatectomy, external beam radiation therapy with low dose rate brachytherapy boost was associated with clinically meaningful worse urinary irritative/obstructive and bowel functions but better urinary incontinence function through 5 years after treatment. These patient-reported functional outcomes may clarify treatment expectations and help inform treatment choices for localized prostate cancer.

Association between Treatment for Localized Prostate Cancer and Mental Health Outcomes.

PURPOSE: We aimed to compare patient-reported mental health outcomes for men undergoing treatment for localized prostate cancer longitudinally over 5 years. MATERIALS AND METHODS: We conducted a prospective population-based analysis using the Comparative Effectiveness Analysis of Surgery and Radiation (CEASAR) study. Patient-reported depressive symptoms (Centers for Epidemiologic Studies Depression [CES-D]) and domains of the Medical Outcomes Study 36-item Short Form survey evaluating emotional well-being and energy/fatigue were assessed through 5 years after treatment with surgery, radiotherapy (with or without androgen deprivation therapy) and active surveillance. Regression models were adjusted for outcome-specific baseline function, demographic and clinicopathological characteristics, and treatment approach. RESULTS: A total of 2,742 men (median [quartiles] age 64 [59-70]) met inclusion criteria. Baseline depressive symptoms, as measured by the CES-D, were low (median 4, quartiles 1-8) without differences between groups. We found no effect of treatment modality on depressive symptoms (p=0.78), though older age, poorer health, being unmarried and baseline CES-D score were associated with declines in mental health. There was no clinically meaningful association between treatment modality and scores for either emotional well-being (p=0.81) or energy/fatigue (p=0.054). CONCLUSIONS: This prospective, population-based cohort study of men with localized prostate cancer showed no clinically important differences in mental health outcomes including depressive symptoms, emotional well-being, and energy/fatigue according to the treatment received (surgery, radiotherapy, or surveillance). However, we identified a number of characteristics associated with worse mental health outcomes including: older age, poorer health, being unmarried, and baseline CES-D score which may allow for early identification of patients most at risk of these outcomes following treatment.

The Utility of Pathology Reports to Identify Persons With Cancer Recurrence.

BACKGROUND: Cancer recurrence is an important measure of the impact of cancer treatment. However, no population-based data on recurrence are available. Pathology reports could potentially identify cancer recurrences. Their utility to capture recurrences is unknown. OBJECTIVE: This analysis assesses the sensitivity of pathology reports to identify patients with cancer recurrence and the stage at recurrence. SUBJECTS: The study includes patients with recurrent breast (n=214) or colorectal (n=203) cancers. RESEARCH DESIGN: This retrospective analysis included patients from a population-based cancer registry who were part of the Patient-Centered Outcomes Research (PCOR) Study, a project that followed cancer patients in-depth for 5 years after diagnosis to identify recurrences. MEASURES: Information abstracted from pathology reports for patients with recurrence was compared with their PCOR data (gold standard) to determine what percent had a pathology report at the time of recurrence, the sensitivity of text in the report to identify recurrence, and if the stage at recurrence could be determined from the pathology report. RESULTS: One half of cancer patients had a pathology report near the time of recurrence. For patients with a pathology report, the report's sensitivity to identify recurrence was 98.1% for breast cancer cases and 95.7% for colorectal cancer cases. The specific stage at recurrence from the pathology report had a moderate agreement with gold-standard data. CONCLUSIONS: Pathology reports alone cannot measure population-based recurrence of solid cancers but can identify specific cohorts of recurrent cancer patients. As electronic submission of pathology reports increases, these reports may identify specific recurrent patients in near real-time.

Class imbalance in out-of-distribution datasets: Improving the robustness of the TextCNN for the classification of rare cancer types.

In the last decade, the widespread adoption of electronic health record documentation has created huge opportunities for information mining. Natural language processing (NLP) techniques using machine and deep learning are becoming increasingly widespread for information extraction tasks from unstructured clinical notes. Disparities in performance when deploying machine learning models in the real world have recently received considerable attention. In the clinical NLP domain, the robustness of convolutional neural networks (CNNs) for classifying cancer pathology reports under natural distribution shifts remains understudied. In this research, we aim to quantify and improve the performance of the CNN for text classification on out-of-distribution (OOD) datasets resulting from the natural evolution of clinical text in pathology reports. We identified class imbalance due to different prevalence of cancer types as one of the sources of performance drop and analyzed the impact of previous methods for addressing class imbalance when deploying models in real-world domains. Our results show that our novel class-specialized ensemble technique outperforms other methods for the classification of rare cancer types in terms of macro F1 scores. We also found that traditional ensemble methods perform better in top classes, leading to higher micro F1 scores. Based on our findings, we formulate a series of recommendations for other ML practitioners on how to build robust models with extremely imbalanced datasets in biomedical NLP applications.

Contributions of Adenocarcinoma and Carcinoid Tumors to Early-Onset Colorectal Cancer Incidence Rates in the United States.

BACKGROUND: Early-onset colorectal cancer (EOCRC) incidence rates (IRs) are rising, according to previous cancer registry analyses. However, analysis of histologic subtypes, including adenocarcinoma (the focus of CRC screening and diagnostic testing) and carcinoid tumors (which are classified as "colorectal cancer" in SEER [Surveillance, Epidemiology, and End Results] databases but have a distinct pathogenesis and are managed differently from adenocarcinoma), has not been reported. OBJECTIVE: To assess EOCRC IRs and changes in IRs over time, stratified by histology. DESIGN: Retrospective analysis. SETTING: Yearly IRs according to SEER 18 data from 2000 to 2016 on age-specific colon-only, rectal-only, and combined-site CRC cases, stratified by histology ("overall" CRC [all histologic subtypes], adenocarcinoma, and carcinoid tumors) and age. PATIENTS: 119 624 patients with CRC. MEASUREMENTS: IRs per 100 000 population, changes in 3-year average annual IRs (pooled IRs from 2000 to 2002 vs. those from 2014 to 2016), and annual percentage change (APC) in persons aged 20 to 29, 30 to 39, 40 to 49, and 50 to 54 years. RESULTS: The steepest changes in adenocarcinoma 3-year average annual IRs were for rectal-only cases in persons aged 20 to 29 years (+39% [0.33 to 0.46 per 100 000]; P < 0.050) and 30 to 39 years (+39% [1.92 to 2.66 per 100 000]; P < 0.050) and colon-only cases in those aged 30 to 39 years (+20% [3.30 to 3.97 per 100 000]; P < 0.050). Corresponding APCs were 1.6% (P < 0.050), 2.2% (P < 0.050), and 1.2% (P < 0.050), respectively. In persons aged 40 to 49 years, 3-year average annual IRs increased in both colon-only (+13% [12.21 to 13.85 per 100 000]; P < 0.050) and rectal-only (+16% [7.50 to 8.72 per 100 000]; P < 0.050) subsites. Carcinoid tumors were common, representing approximately 4% to 20% of all colorectal and 8% to 34% of all rectal cancer cases, depending on age group and calendar year. Colon-only carcinoid tumors were rare. Colorectal carcinoid tumor IRs increased more steeply than adenocarcinoma in all age groups, thus affecting the contribution of carcinoid tumors to overall cancer cases over time. These changes were driven by rectal subsites and were most pronounced in persons aged 50 to 54 years, in whom rectal carcinoid tumors increased by 159% (2.36 to 6.10 per 100 000) between 2000 to 2002 and 2014 to 2016, compared with 10% for adenocarcinoma (18.07 to 19.84 per 100 000), ultimately accounting for 22.6% of all rectal cancer cases. LIMITATION: Population-based data. CONCLUSION: These findings underscore the importance of assessing histologic CRC subtypes independently. Doing so may lead to a better understanding of the drivers of temporal changes in overall CRC incidence and a more accurate measurement of outcomes from efforts to reduce adenocarcinoma risk, and can guide future research. PRIMARY FUNDING SOURCE: None.

Deep active learning for classifying cancer pathology reports.

BACKGROUND: Automated text classification has many important applications in the clinical setting; however, obtaining labelled data for training machine learning and deep learning models is often difficult and expensive. Active learning techniques may mitigate this challenge by reducing the amount of labelled data required to effectively train a model. In this study, we analyze the effectiveness of 11 active learning algorithms on classifying subsite and histology from cancer pathology reports using a Convolutional Neural Network as the text classification model. RESULTS: We compare the performance of each active learning strategy using two differently sized datasets and two different classification tasks. Our results show that on all tasks and dataset sizes, all active learning strategies except diversity-sampling strategies outperformed random sampling, i.e., no active learning. On our large dataset (15K initial labelled samples, adding 15K additional labelled samples each iteration of active learning), there was no clear winner between the different active learning strategies. On our small dataset (1K initial labelled samples, adding 1K additional labelled samples each iteration of active learning), marginal and ratio uncertainty sampling performed better than all other active learning techniques. We found that compared to random sampling, active learning strongly helps performance on rare classes by focusing on underrepresented classes. CONCLUSIONS: Active learning can save annotation cost by helping human annotators efficiently and intelligently select which samples to label. Our results show that a dataset constructed using effective active learning techniques requires less than half the amount of labelled data to achieve the same performance as a dataset constructed using random sampling.

Positive impact of the Patient Protection and Affordable Care Act Medicaid expansion on Louisiana women with breast cancer.

BACKGROUND: Louisiana is one of the few Southern states that enacted the Medicaid expansion of the Patient Protection and Affordable Care Act (ACA). To the authors' knowledge, the issue of how this has affected the breast cancer landscape in Louisiana is unknown. The authors have postulated that ACA expansion had a positive impact for Louisiana women diagnosed with breast cancer. METHODS: Data from the Louisiana Tumor Registry regarding 14,640 women aged 20 to 64 years who resided in Louisiana and were diagnosed with American Joint Committee on Cancer stage 0 to stage IV breast cancer between 2012 and 2018 were analyzed. The study period was divided into 2 groups: 1) before ACA expansion (January 1, 2012-May 31, 2016); and 2) after ACA expansion (June 1, 2016-December 31, 2018). The chi-square test and multivariable logistic regression models were used to assess the impact of ACA expansion. A P value <.05 was considered statistically significant. RESULTS: After ACA expansion, the rate of uninsured patients decreased from 5.4% to 3.0% (P < .0001), and the rate of Medicaid recipients increased from 11.6% to 17.7% (P < .0001). The diagnosis of stage I breast cancer increased from 36.8% to 44.7% (P < .0001), whereas the diagnosis of stage III breast cancer decreased from 10.7% to 8.5% (P < .0001). The receipt of radiotherapy after breast-conserving surgery increased from 81.2% to 84.0% (P = .0035), and the receipt of radiotherapy within 90 days increased from 57.2% to 61.7% (P = .0012). After adjustment for sociodemographic and clinical variables, the models demonstrated that ACA expansion decreased the uninsured rate by 48% (odds ratio [OR], 0.52; 95% CI, 0.43-0.63), increased the diagnosis of early-stage disease (stage0 to stage II) by 27% (OR, 1.27; 95% CI, 1.15-1.41), increased receipt of radiotherapy after breast-conserving surgery by 19% (OR, 1.19; 95% CI, 1.03-1.37), and reduced the delay of receipt of radiotherapy by 16% (OR, 0.84; 95% CI, 0.74-0.95). CONCLUSIONS: ACA expansion in Louisiana reduced the uninsured rate, increased the diagnosis of early-stage disease, and increased access to treatment.

Five-year outcomes from a prospective comparative effectiveness study evaluating external-beam radiotherapy with or without low-dose-rate brachytherapy boost for localized prostate cancer.

BACKGROUND: To inform patients who are in the process of selecting prostate cancer treatment, the authors compared disease-specific function after external-beam radiotherapy (EBRT) alone versus EBRT plus a low-dose-rate (LDR) brachytherapy boost (EBRT-LDR). METHODS: For this prospective study, men who had localized prostate cancer in 2011 and 2012 were enrolled. Assessments at baseline, 0.5, 1, 3, and 5 years included the patient-reported Expanded Prostate Index Composite, the 36-item Medical Outcomes Study Short-Form Health Survey, and treatment-related regret. Regression models were adjusted for baseline function and for patient and treatment characteristics. The minimum clinically important difference in scores on the Expanded Prostate Index Composite 26-item instrument was from 5 to 7 for urinary irritation and from 4 to 6 for bowel function. RESULTS: Six-hundred ninety-five men met inclusion criteria and received either EBRT (n = 583) or EBRT-LDR (n = 112). Patients in the EBRT-LDR group were younger (median age, 66 years [interquartile range [IQR], 60-71 years] vs 69 years [IQR, 64-74 years]; P < .001), were less likely to receive pelvic radiotherapy (10% vs 18%; P = .040), and had higher baseline 36-item Medical Outcomes Study Short-Form Health Survey physical function scores (median score, 95 [IQR, 86-100] vs 90 [IQR, 70-100]; P < .001). Over a 3-year period, compared with EBRT, EBRT-LDR was associated with worse urinary irritative scores (adjusted mean difference at 3 years, -5.4; 95% CI, -9.3, -1.6) and bowel function scores (-4.1; 95% CI, -7.6, -0.5). The differences were no longer clinically meaningful at 5 years (difference in urinary irritative scores: -4.5; 95% CI, -8.4, -0.5; difference in bowel function scores: -2.1; 95% CI, -5.7, -1.4). However, men who received EBRT-LDR were more likely to report moderate or big problems with urinary function bother (adjusted odds ratio, 3.5; 95% CI, 1.5-8.2) and frequent urination (adjusted odds ratio, 2.6; 95% CI, 1.2-5.6) through 5 years. There were no differences in survival or treatment-related regret between treatment groups. CONCLUSIONS: Compared with EBRT alone, EBRT-LDR was associated with clinically meaningful worse urinary irritative and bowel function over 3 years after treatment and more urinary bother at 5 years. LAY SUMMARY: In men with prostate cancer who received external-beam radiation therapy (EBRT) with or without a brachytherapy boost (EBRT-LDR), EBRT-LDR was associated with clinically worse urinary irritation and bowel function through 3 years but resolved after 5 years. Men who received EBRT-LDR continued to report moderate-to-big problems with urinary function bother and frequent urination through 5 years. There was no difference in treatment-related regret or survival between patients who received EBRT and those who received EBRT-LDR. These intermediate-term estimates of function may facilitate counseling for men who are selecting treatment.

Patient-Reported Financial Toxicity Associated with Contemporary Treatment for Localized Prostate Cancer.

PURPOSE: Contemporary treatment modalities for localized prostate cancer provide comparable overall and cancer-specific survival. However, the degree of financial burden imposed by treatment, the factors contributing to that burden, and how different treatments compare with regard to financial toxicity remain poorly understood. MATERIALS AND METHODS: The Comparative Effectiveness Analysis of Surgery and Radiation (CEASAR) study enrolled men with localized prostate cancer from 2011 to 2012. Questionnaires were collected at 6, 12, 36, and 60 months after enrollment. Differences in patient-reported financial burden were compared between active surveillance, radical prostatectomy, and external beam radiotherapy using multivariable logistic regression. RESULTS: Among 2,121 patients meeting inclusion criteria, 15% reported large or very large burden of treatment costs within 6 months, declining to 3% by year 5. When controlling for age, education, income and other covariates, external beam radiotherapy was associated with greater financial burden than active surveillance and radical prostatectomy at 1 year (OR 2.2, 95% CI 1.2-4.1 and OR 1.5, 95% CI 1.0-2.3, respectively) and 3 years (OR 3.1 95% CI 1.1-8.8 and OR 2.1, 95% CI 1.2-3.7, respectively). Radical prostatectomy and active surveillance had similar rates of financial burden at all time points. Age, race, education, and D'Amico risk group were associated with financial burden. CONCLUSIONS: External beam radiotherapy was associated with the highest financial burden, even when controlling for age, education and income. Prospective studies that directly measure out-of-pocket and indirect costs and account more thoroughly for baseline socioeconomic differences are warranted in order to identify those most at risk.

Understanding the patient journey to diagnosis of lung cancer.

OBJECTIVE: This research describes the clinical pathway and characteristics of two cohorts of patients. The first cohort consists of patients with a confirmed diagnosis of lung cancer while the second consists of patients with a solitary pulmonary nodule (SPN) and no evidence of lung cancer. Linked data from an electronic medical record and the Louisiana Tumor Registry were used in this investigation. MATERIALS AND METHODS: REACHnet is one of 9 clinical research networks (CRNs) in PCORnet®, the National Patient-Centered Clinical Research Network and includes electronic health records for over 8 million patients from multiple partner health systems. Data from Ochsner Health System and Tulane Medical Center were linked to Louisiana Tumor Registry (LTR), a statewide population-based cancer registry, for analysis of patient's clinical pathways between July 2013 and 2017. Patient characteristics and health services utilization rates by cancer stage were reported as frequency distributions. The Kaplan-Meier product limit method was used to estimate the time from index date to diagnosis by stage in lung cancer cohort. RESULTS: A total of 30,559 potentially eligible patients were identified and 2929 (9.58%) had primary lung cancer. Of these, 1496 (51.1%) were documented in LTR and their clinical pathway to diagnosis was further studied. Time to diagnosis varied significantly by cancer stage. A total of 24,140 patients with an SPN were identified in REACHnet and 15,978 (66.6%) had documented follow up care for 1 year. 1612 (10%) had no evidence of any work up for their SPN. The remaining 14,366 had some evidence of follow up, primarily office visits and additional chest imaging. CONCLUSION: In both cohorts multiple biopsies were evident in the clinical pathway. Despite clinical workup, 70% of patients in the lung cancer cohort had stage III or IV disease. In the SPN cohort, only 66% were identified as receiving a diagnostic work-up.

Trend and survival benefit of Oncotype DX use among female hormone receptor-positive breast cancer patients in 17 SEER registries, 2004-2015.

PURPOSE: To examine (1) the trend and associated factors of Oncotype DX (ODX) use among hormone receptor-positive (HR+) breast cancer (BC) patients in 2004-2015; (2) the trend of reported chemotherapy by Recurrence Score (RS); and (3) the survival differences associated with ODX use. METHODS: ODX data from Genomic Health Inc. were linked with 17 SEER registries data. HR + BC cases with lymph node negative (N0) or 1-3 positive LNs (N1) from 2004-2015 were analyzed. The Cochrane-Armitage trend test, logistic regression, Kaplan-Meier survival curve, and stratified Cox model were performed. Survival analysis was restricted to HR+/HER2- patients from 2010 to 2014, matched on propensity score. RESULTS: ODX use increased substantially from 2004 to 2015 (N0: 2.0% to 42.7%; N1: 0.3% to 27.9%). Non-Hispanic black and Medicaid insured patients had lower odds of receiving ODX. N0 patients with moderately differentiated or 2.1-5.0 cm tumor and N1 patients with well-differentiated or < 2.0 cm tumor had higher odds of using ODX. The reported chemotherapy use decreased significantly with low and intermediate RS, and increased for high RS among N0 patients. ODX use was associated with better breast cancer-specific survival [hazard ratio (95% CI) N0 1.96 (1.60-2.41), N1 1.90 (1.42-2.54)] and overall survival [N0 2.06 (1.83-2.31), N1 1.72 (1.42-2.09)], especially in the first 36 months. CONCLUSION: ODX use has increased significantly since 2004, nonetheless disparities remain, especially for racial/ethnic minorities and Medicaid insured patients. Administering chemotherapy based on ODX results has been improved among N0 patients. Patients receiving ODX had better survival than those not.

Assessing the Quality of Surgical Care for Clinically Localized Prostate Cancer: Results from the CEASAR Study.

PURPOSE: Prior studies suggest that nationally endorsed quality measures for prostate cancer care are not linked closely with outcomes. Using a prospective, population based cohort we measured clinically relevant variation in structure, process and outcome measures in men undergoing radical prostatectomy. MATERIALS AND METHODS: The Comparative Effectiveness Analysis of Surgery and Radiation (CEASAR) Study enrolled men with clinically localized prostate cancer diagnosed from 2011 to 2012 with 1,069 meeting the final inclusion criteria. Quality of life was assessed using the Expanded Prostate Index Composite (EPIC-26) and clinical data by chart review. Six quality measures were assessed, including pelvic lymphadenectomy with risk of lymph node involvement 2% or greater, appropriate nerve sparing, negative surgical margins, urinary and sexual function, treatment by high volume surgeon, and 30-day and 1-year complications. Receipt of high quality care was compared across categories of race, age, surgeon volume and surgical approach via multivariable analysis. RESULTS: There were no significant differences in quality across race, age or surgeon volume strata, except for worse urinary incontinence in Black men. However, robotic surgery patients experienced fewer complications (3% vs 9.3% short-term and 11% vs 16% long-term), were more likely to be treated by a high volume surgeon (47% vs 25%) and demonstrated better sexual function. CONCLUSIONS: In this cohort we did not identify meaningful variation in quality of care across racial groups, age groups and surgeon volume strata, suggesting that men are receiving comparable quality of care across these strata. However, we did find variation between open and robotic surgery with fewer complications, improved sexual function and increased use of high volume surgeons in the robotic group, possibly reflecting differences in quality between approaches, differences in practice patterns and/or biases in patient selection.

Accelerated training of bootstrap aggregation-based deep information extraction systems from cancer pathology reports.

OBJECTIVE: In machine learning, it is evident that the classification of the task performance increases if bootstrap aggregation (bagging) is applied. However, the bagging of deep neural networks takes tremendous amounts of computational resources and training time. The research question that we aimed to answer in this research is whether we could achieve higher task performance scores and accelerate the training by dividing a problem into sub-problems. MATERIALS AND METHODS: The data used in this study consist of free text from electronic cancer pathology reports. We applied bagging and partitioned data training using Multi-Task Convolutional Neural Network (MT-CNN) and Multi-Task Hierarchical Convolutional Attention Network (MT-HCAN) classifiers. We split a big problem into 20 sub-problems, resampled the training cases 2,000 times, and trained the deep learning model for each bootstrap sample and each sub-problem-thus, generating up to 40,000 models. We performed the training of many models concurrently in a high-performance computing environment at Oak Ridge National Laboratory (ORNL). RESULTS: We demonstrated that aggregation of the models improves task performance compared with the single-model approach, which is consistent with other research studies; and we demonstrated that the two proposed partitioned bagging methods achieved higher classification accuracy scores on four tasks. Notably, the improvements were significant for the extraction of cancer histology data, which had more than 500 class labels in the task; these results show that data partition may alleviate the complexity of the task. On the contrary, the methods did not achieve superior scores for the tasks of site and subsite classification. Intrinsically, since data partitioning was based on the primary cancer site, the accuracy depended on the determination of the partitions, which needs further investigation and improvement. CONCLUSION: Results in this research demonstrate that 1. The data partitioning and bagging strategy achieved higher performance scores. 2. We achieved faster training leveraged by the high-performance Summit supercomputer at ORNL.