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Objectives: Visual inspection with acetic acid (VIA) is a low‐cost approach for cervical cancer screening used in most low‐ and middle‐income countries (LMICs) but, similar to other visual tests, is subjective and requires sustained training and quality assurance. We developed, trained, and validated an artificial‐intelligence‐based "Automated Visual Evaluation" (AVE) tool that can be adapted to run on smartphones to assess smartphone‐captured images of the cervix and identify precancerous lesions, helping augment VIA performance. Design: Prospective study. Setting: Eight public health facilities in Zambia. Participants: A total of 8204 women aged 25–55. Interventions: Cervical images captured on commonly used low‐cost smartphone models were matched with key clinical information including human immunodeficiency virus (HIV) and human papillomavirus (HPV) status, plus histopathology analysis (where applicable), to develop and train an AVE algorithm and evaluate its performance for use as a primary screen and triage test for women who are HPV positive. Main Outcome Measures: Area under the receiver operating curve (AUC); sensitivity; specificity. Results: As a general population screening tool for cervical precancerous lesions, AVE identified cases of cervical precancerous and cancerous (CIN2+) lesions with high performance (AUC = 0.91, 95% confidence interval [CI] = 0.89–0.93), which translates to a sensitivity of 85% (95% CI = 81%–90%) and specificity of 86% (95% CI = 84%–88%) based on maximizing the Youden's index. This represents a considerable improvement over naked eye VIA, which as per a meta‐analysis by the World Health Organization (WHO) has a sensitivity of 66% and specificity of 87%. For women living with HIV, the AUC of AVE was 0.91 (95% CI = 0.88–0.93), and among those testing positive for high‐risk HPV types, the AUC was 0.87 (95% CI = 0.83–0.91). Conclusions: These results demonstrate the feasibility of utilizing AVE on images captured using a commonly available smartphone by nurses in a screening program, and support our ongoing efforts for moving to more broadly evaluate AVE for its clinical sensitivity, specificity, feasibility, and acceptability across a wider range of settings. Limitations of this study include potential inflation of performance estimates due to verification bias (as biopsies were only obtained from participants with visible aceto‐white cervical lesions) and due to this being an internal validation (the test data, while independent from that used to develop the algorithm was drawn from the same study). [ABSTRACT FROM AUTHOR]

Abstract Background The MISSION and CHOICE Acts expanded the Veterans Health Administration's (VA) capacity to purchase immunotherapy services for VA patients from community‐based providers. Our objective was to identify predictors of community‐based immunotherapy treatment, and assess differences in cost and utilization across community treatment settings METHODS We examined claims for 21,257 patients who started immunotherapy treatment between 2015 and 2020. We assessed growth in VA community‐based immunotherapy care, predictors of community‐based immunotherapy treatment using multivariable logistic regression based on patients' sociodemographic and clinical characteristics. We compared utilization and costs among those who received community‐based immunotherapy services in hospital outpatient departments (HOPDs) versus physician office settings (POs). Results The proportion of community‐based immunotherapy in the VA increased from 5.3% in 2015 to 32.1% in 2020, with total annual costs of immunotherapy growing from $6.1 million to $187 million. Older, married, and rural patients and those with more comorbidities were more likely than younger, single, or urban patients to be treated in the community. Black patients were more likely to be treated in the VA. Respiratory Cancer was the most common cancer type in both settings. Among community immunotherapy patients, we observed no meaningful differences in the number of units administered, the unit drug costs, or the cost per immunotherapy visit between POs and HOPDs. Conclusion Drug costs did not differ widely across HOPDs and POs among VA patients who receive community‐based immunotherapy.

Abstract Introduction Data on the impact of specific comorbidities on health outcomes is limited. We compared health status and mental distress between individuals with and without cancer according to comorbidity type. Methods A cross‐sectional analysis using data from the Australian National Health Survey 2017–18 including all respondents aged ≥25 years with and without a history of cancer. The odds of poor health and mental distress were reported according to cancer status, and specific individual and cluster of comorbidities. Results There were 1982 individuals (52% female) with cancer and 12,635 (51% female) without cancer. Individuals with cancer were older, and more likely to have a comorbidity compared with those without cancer. They were more likely to report poor health than those without cancer for each specific comorbidity; except for skin conditions and infectious diseases; with the adjusted odds ratio (aOR) ranging from 1.34 (95% CI = 1.01–1.79) for digestive disorders to 2.93 (95% CI = 1.62–5.29) for blood conditions. The strongest association with poor health (aOR 2.79, 95% CI = 2.27–3.43) and mental distress (aOR 9.01, 95% CI = 7.25–11.20) was observed for those with a comorbid mental illness. Exploratory cluster analysis identified four distinct comorbidity clusters: low comorbidity, musculoskeletal, respiratory and cardiometabolic; cancer survivors in the cardiometabolic cluster had a higher odds of reporting poor health (aOR 3.50, 95% CI = 2.48–4.92) and mental distress (aOR 2.33, 95% CI = 1.53–3.55) than those with a low comorbidity. Conclusions Comorbidities in cancer survivors were common and associated with inferior health status, although the magnitude of the effect varied by comorbidity type. Risk assessment and management of comorbidities should be an important priority for cancer care and research.

Abstract Background In our recent study, advanced disease stage and nonreceipt of surgery were the most important mediators of the racial disparity in breast cancer survival. The purpose of this study was to quantify the racial disparity in these two intermediate outcomes and investigate mediation by the more proximal mediators of insurance status and neighborhood poverty. Methods This was a cross‐sectional study of non‐Hispanic Black and non‐Hispanic White women diagnosed with first primary invasive breast cancer in Florida between 2004 and 2015. Log‐binomial regression was used to obtain prevalence ratios (PR) with 95% confidence intervals (CIs). Multiple mediation analysis was used to assess the role of having Medicaid/being uninsured and living in high‐poverty neighborhoods on the race effect. Results There were 101,872 women in the study (87.0% White, 13.0% Black). Black women were 55% more likely to be diagnosed with advanced disease stage at diagnosis (PR, 1.55; 95% CI, 1.50–1.60) and nearly twofold more likely to not receive surgery (PR, 1.97; 95% CI, 1.90–2.04). Insurance status and neighborhood poverty explained 17.6% and 5.3% of the racial disparity in advanced disease stage at diagnosis, respectively; 64.3% remained unexplained. For nonreceipt of surgery, insurance status explained 6.8% while neighborhood poverty explained 3.2%; 52.1% was unexplained. Conclusions Insurance status and neighborhood poverty were significant mediators of the racial disparity in advanced disease stage at diagnosis with a smaller impact on nonreceipt of surgery. However, interventions designed to improve breast cancer screening and receipt of high‐quality cancer treatment must address additional barriers for Black women with breast cancer.

Background: The MISSION and CHOICE Acts expanded the Veterans Health Administration's (VA) capacity to purchase immunotherapy services for VA patients from community‐based providers. Our objective was to identify predictors of community‐based immunotherapy treatment, and assess differences in cost and utilization across community treatment settings METHODS: We examined claims for 21,257 patients who started immunotherapy treatment between 2015 and 2020. We assessed growth in VA community‐based immunotherapy care, predictors of community‐based immunotherapy treatment using multivariable logistic regression based on patients' sociodemographic and clinical characteristics. We compared utilization and costs among those who received community‐based immunotherapy services in hospital outpatient departments (HOPDs) versus physician office settings (POs). Results: The proportion of community‐based immunotherapy in the VA increased from 5.3% in 2015 to 32.1% in 2020, with total annual costs of immunotherapy growing from $6.1 million to $187 million. Older, married, and rural patients and those with more comorbidities were more likely than younger, single, or urban patients to be treated in the community. Black patients were more likely to be treated in the VA. Respiratory Cancer was the most common cancer type in both settings. Among community immunotherapy patients, we observed no meaningful differences in the number of units administered, the unit drug costs, or the cost per immunotherapy visit between POs and HOPDs. Conclusion: Drug costs did not differ widely across HOPDs and POs among VA patients who receive community‐based immunotherapy. [ABSTRACT FROM AUTHOR]

Introduction: Data on the impact of specific comorbidities on health outcomes is limited. We compared health status and mental distress between individuals with and without cancer according to comorbidity type. Methods: A cross‐sectional analysis using data from the Australian National Health Survey 2017–18 including all respondents aged ≥25 years with and without a history of cancer. The odds of poor health and mental distress were reported according to cancer status, and specific individual and cluster of comorbidities. Results: There were 1982 individuals (52% female) with cancer and 12,635 (51% female) without cancer. Individuals with cancer were older, and more likely to have a comorbidity compared with those without cancer. They were more likely to report poor health than those without cancer for each specific comorbidity; except for skin conditions and infectious diseases; with the adjusted odds ratio (aOR) ranging from 1.34 (95% CI = 1.01–1.79) for digestive disorders to 2.93 (95% CI = 1.62–5.29) for blood conditions. The strongest association with poor health (aOR 2.79, 95% CI = 2.27–3.43) and mental distress (aOR 9.01, 95% CI = 7.25–11.20) was observed for those with a comorbid mental illness. Exploratory cluster analysis identified four distinct comorbidity clusters: low comorbidity, musculoskeletal, respiratory and cardiometabolic; cancer survivors in the cardiometabolic cluster had a higher odds of reporting poor health (aOR 3.50, 95% CI = 2.48–4.92) and mental distress (aOR 2.33, 95% CI = 1.53–3.55) than those with a low comorbidity. Conclusions: Comorbidities in cancer survivors were common and associated with inferior health status, although the magnitude of the effect varied by comorbidity type. Risk assessment and management of comorbidities should be an important priority for cancer care and research. [ABSTRACT FROM AUTHOR]

Background: In our recent study, advanced disease stage and nonreceipt of surgery were the most important mediators of the racial disparity in breast cancer survival. The purpose of this study was to quantify the racial disparity in these two intermediate outcomes and investigate mediation by the more proximal mediators of insurance status and neighborhood poverty. Methods: This was a cross‐sectional study of non‐Hispanic Black and non‐Hispanic White women diagnosed with first primary invasive breast cancer in Florida between 2004 and 2015. Log‐binomial regression was used to obtain prevalence ratios (PR) with 95% confidence intervals (CIs). Multiple mediation analysis was used to assess the role of having Medicaid/being uninsured and living in high‐poverty neighborhoods on the race effect. Results: There were 101,872 women in the study (87.0% White, 13.0% Black). Black women were 55% more likely to be diagnosed with advanced disease stage at diagnosis (PR, 1.55; 95% CI, 1.50–1.60) and nearly twofold more likely to not receive surgery (PR, 1.97; 95% CI, 1.90–2.04). Insurance status and neighborhood poverty explained 17.6% and 5.3% of the racial disparity in advanced disease stage at diagnosis, respectively; 64.3% remained unexplained. For nonreceipt of surgery, insurance status explained 6.8% while neighborhood poverty explained 3.2%; 52.1% was unexplained. Conclusions: Insurance status and neighborhood poverty were significant mediators of the racial disparity in advanced disease stage at diagnosis with a smaller impact on nonreceipt of surgery. However, interventions designed to improve breast cancer screening and receipt of high‐quality cancer treatment must address additional barriers for Black women with breast cancer. [ABSTRACT FROM AUTHOR]

Background: A strong relationship has been observed between comorbidities and the risk of severe/fatal COVID‐19 manifestations, but no score is available to evaluate their association in cancer patients. To make up for this lacuna, we aimed to develop a comorbidity score for cancer patients, based on the Lombardy Region healthcare databases. Methods: We used hospital discharge records to identify patients with a new diagnosis of solid cancer between February and December 2019; 61 comorbidities were retrieved within 2 years before cancer diagnosis. This cohort was split into training and validation sets. In the training set, we used a LASSO‐logistic model to identify comorbidities associated with the risk of developing a severe/fatal form of COVID‐19 during the first pandemic wave (March–May 2020). We used a logistic model to estimate comorbidity score weights and then we divided the score into five classes (<=−1, 0, 1, 2–4, >=5). In the validation set, we assessed score performance by areas under the receiver operating characteristic curve (AUC) and calibration plots. We repeated the process on second pandemic wave (October–December 2020) data. Results: We identified 55,425 patients with an incident solid cancer. We selected 21 comorbidities as independent predictors. The first four score classes showed similar probability of experiencing the outcome (0.2% to 0.5%), while the last showed a probability equal to 5.8%. The score performed well in both the first and second pandemic waves: AUC 0.85 and 0.82, respectively. Our results were robust for major cancer sites too (i.e., colorectal, lung, female breast, and prostate). Conclusions: We developed a high performance comorbidity score for cancer patients and COVID‐19. Being based on administrative databases, this score will be useful for adjusting for comorbidity confounding in epidemiological studies on COVID‐19 and cancer impact. [ABSTRACT FROM AUTHOR]

Angiogenesis inhibitors have become standard of care for advanced and/or metastatic renal cell carcinoma ( RCC), but data on the impact of adverse events ( AEs) and treatment modifications associated with these agents are limited. Medical records were abstracted at 10 tertiary oncology centers in Europe for 291 patients ≥18 years old treated with sunitinib as first-line treatment for advanced RCC (no prior systemic treatment for advanced disease). Logistic regression models were estimated to compare dose intensity among patients who did and did not experience AEs during the landmark periods (18, 24, and 30 weeks). Cox proportional hazard models were used to explore the possible relationship of low-dose intensity (defined using thresholds of 0.7, 0.8, and 0.9) and treatment modifications during the landmark periods to survival. 64.4% to 67.9% of patients treated with sunitinib reported at least one AE of any grade, and approximately 10% of patients experienced at least one severe (grade 3 or 4) AE. Patients reporting severe AEs were statistically significantly more likely to have dose intensities below either 0.8 or 0.9. Dose intensity below 0.7 and dose discontinuation during all landmark periods were statistically significantly associated with shorter survival time. This study of advanced RCC patients treated with sunitinib in Europe found a significant relationship between AEs and dose intensity. It also found correlations between dose intensity and shorter survival, and between dose discontinuation and shorter survival. These results confirm the importance of tolerable treatment and maintaining dose intensity. [ABSTRACT FROM AUTHOR]