Improving Equity in Deep Learning Medical Applications with the Gerchberg-Saxton Algorithm.

Deep learning (DL) has gained prominence in healthcare for its ability to facilitate early diagnosis, treatment identification with associated prognosis, and varying patient outcome predictions. However, because of highly variable medical practices and unsystematic data collection approaches, DL can unfortunately exacerbate biases and distort estimates. For example, the presence of sampling bias poses a significant challenge to the efficacy and generalizability of any statistical model. Even with DL approaches, selection bias can lead to inconsistent, suboptimal, or inaccurate model results, especially for underrepresented populations. Therefore, without addressing bias, wider implementation of DL approaches can potentially cause unintended harm. In this paper, we studied a novel method for bias reduction that leverages the frequency domain transformation via the Gerchberg-Saxton and corresponding impact on the outcome from a racio-ethnic bias perspective.

T-DM1 after Pertuzumab plus Trastuzumab: Treatment Sequence-Induced Selection Bias in HER2-Positive Metastatic Breast Cancer.

Real-world studies have suggested decreased trastuzumab emtansine (T-DM1) effectiveness in patients with metastatic breast cancer (mBC) who received prior trastuzumab plus pertuzumab (H + P). However, these studies may have been biased toward pertuzumab-experienced patients with more aggressive disease. Using an electronic health record-derived database, patients diagnosed with mBC on/after 1 January 2011 who initiated T-DM1 in any treatment line (primary cohort) or who initiated second-line T-DM1 following first-line H ± P (secondary cohort) from 22 February 2013 to 31 December 2019 were included. The primary outcome was time from index date to next treatment or death (TTNT). In the primary cohort (n = 757), the percentage of patients with prior P increased from 37% to 73% across the study period, while population characteristics and treatment effectiveness measures were generally stable. Among P-experienced patients from the secondary cohort (n = 246), median time from mBC diagnosis to T-DM1 initiation increased from 10 to 14 months (2013-2019), and median TTNT increased from 4.4 to 10.2 months (2013-2018). Over time, prior H + P prevalence significantly increased with no observable impact on T-DM1 effectiveness. Drug approval timing should be considered when assessing treatment effectiveness within a sequence.

An overview of real-world data sources for oncology and considerations for research.

Generating evidence on the use, effectiveness, and safety of new cancer therapies is a priority for researchers, health care providers, payers, and regulators given the rapid pace of change in cancer diagnosis and treatments. The use of real-world data (RWD) is integral to understanding the utilization patterns and outcomes of these new treatments among patients with cancer who are treated in clinical practice and community settings. An initial step in the use of RWD is careful study design to assess the suitability of an RWD source. This pivotal process can be guided by using a conceptual model that encourages predesign conceptualization. The primary types of RWD included are electronic health records, administrative claims data, cancer registries, and specialty data providers and networks. Careful consideration of each data type is necessary because they are collected for a specific purpose, capturing a set of data elements within a certain population for that purpose, and they vary by population coverage and longitudinality. In this review, the authors provide a high-level assessment of the strengths and limitations of each data category to inform data source selection appropriate to the study question. Overall, the development and accessibility of RWD sources for cancer research are rapidly increasing, and the use of these data requires careful consideration of composition and utility to assess important questions in understanding the use and effectiveness of new therapies.

Development and validation of a 5-year mortality prediction model using regularized regression and Medicare data.

PURPOSE: De-implementation of low-value services among patients with limited life expectancy is challenging. Robust mortality prediction models using routinely collected health care data can enhance health care stakeholders' ability to identify populations with limited life expectancy. We developed and validated a claims-based prediction model for 5-year mortality using regularized regression methods. METHODS: Medicare beneficiaries age 66 or older with an office visit and at least 12 months of pre-visit continuous Medicare A/B enrollment were identified in 2008. Five-year mortality was assessed through 2013. Secondary outcomes included 30-, 90-, and 180-day and 1-year mortality. Claims-based predictors, including comorbidities and indicators of disability, frailty, and functional impairment, were selected using regularized logistic regression, applying the least absolute shrinkage and selection operator (LASSO) in a random 80% training sample. Model performance was assessed and compared with the Gagne comorbidity score in the 20% validation sample. RESULTS: Overall, 183 204 (24%) individuals died. In addition to demographics, 161 indicators of comorbidity and function were included in the final model. In the validation sample, the c-statistic was 0.825 (0.823-0.828). Median-predicted probability of 5-year mortality was 14%; almost 4% of the cohort had a predicted probability greater than 80%. Compared with the Gagne score, the LASSO model led to improved 5-year mortality classification (net reclassification index = 9.9%; integrated discrimination index = 5.2%). CONCLUSIONS: Our claims-based model predicting 5-year mortality showed excellent discrimination and calibration, similar to the Gagne score model, but resulted in improved mortality classification. Regularized regression is a feasible approach for developing prediction tools that could enhance health care research and evaluation of care quality.

The relationship of travel distance with cystectomy access and outcomes.

PURPOSE: Regionalization of care and travel distance may result in unintended consequences for complex surgery such as cystectomy. Our objective was to evaluate effect of differential distance on cystectomy receipt among patients with muscle-invasive bladder cancer (MIBC) and investigate the association between travel distance and cystectomy outcomes such as readmission. METHODS: Using a linked data resource combining the NC Central Cancer Registry with claims data from Medicare, Medicaid, and private insurance plans, we included 736 patients with MIBC and 1,082 who underwent cystectomy. To evaluate access, differential distance was calculated as the difference between the nearest urologist and nearest cystectomy provider. To assess outcomes, logistic regression was used to evaluate rehospitalization and major complications, and Cox proportional hazards model for survival analysis. RESULTS: To evaluate access and outcomes, 736 patients with MIBC and 1,082 patients undergoing cystectomy were evaluated, respectively. Overall, 29% (211 of 736) with MIBC underwent cystectomy. Differential distance was not a predictor of cystectomy receipt (odds ratio = 1.0; 95% CI: 1.00, 1.01). Among patients undergoing cystectomy, travel distance from cystectomy provider was not a significant predictor of 30- or 31 to 90day readmissions (odds ratio = 1.0; 95% CI: 1.00, 1.00) although patients who lived further from their cystectomy provider were more likely to be readmitted to a nonindex hospital (P<0.001) when controlling for other factors. Although travel distance did not have a significant effect on overall survival, patients readmitted between 31 to 90days had worse overall survival (P<0.0001). CONCLUSIONS: The additional distance needed to reach a cystectomy provider did not predict receipt of surgery for MIBC. Furthermore, travel distance from cystectomy provider was not a significant predictor for subsequent readmission after cystectomy and did not affect overall survival.

Influence of provider factors and race on uptake of breast cancer gene expression profiling.

BACKGROUND: Gene expression profiling (GEP) has been rapidly adopted for early breast cancer and can aid in chemotherapy decision making. Study results regarding racial disparities in testing are conflicting, and may reflect different care settings. To the authors' knowledge, data regarding the influence of provider factors on testing are scarce. METHODS: The authors used a statewide, multipayer, insurance claims database linked to cancer registry records to examine the impact of race and provider characteristics on GEP uptake in a cohort of patients newly diagnosed with breast cancer between 2005 and 2012. Incidence proportion models were used to examine the adjusted likelihood of testing. Models were stratified by lymph node status (N0 vs N1). RESULTS: Among 11,958 eligible patients, 23% of black and 26% of non-Hispanic white patients received GEP. Among patients with N0 disease, black individuals were 16% less likely to receive testing after adjustment for clinical factors and the provider's specialty and volume of patients with breast cancer (95% confidence interval, 0.77-0.93). Adjustment for provider characteristics did not attenuate the effect of race on testing. Patients of middle-volume providers were more likely to be tested compared with those with either high-volume or low-volume providers, whereas patients seeing a medical oncologist were more likely to be tested compared with those whose only providers were from surgical specialties. CONCLUSIONS: Provider volume and specialty were found to be significant predictors of GEP use, but did not explain racial disparities in testing. Further research concerning the key contributors to lagging test use among black women is needed to optimize the equitable use of GEPs and support personalized treatment decision making for all patients. Cancer 2018;124:1743-51. © 2018 American Cancer Society.

Association of Delays in Surgery for Melanoma With Insurance Type.

Importance: Timely receipt of treatment for cancer is an important aspect of health care quality. It is unknown how delays of surgery for melanoma vary by insurance type. Objective: To analyze factors associated with delays between diagnosis and surgery for melanoma in patients with Medicare, Medicaid, or private insurance. Design, Setting, and Participants: Retrospective cohort study of patients who received a diagnosis of melanoma between 2004 and 2011 in North Carolina using data from the North Carolina Cancer Registry linked to administrative claims from Medicare, Medicaid, and private insurance. Inclusion criteria were incident patients with a diagnosis of melanoma stage 0 to III and with continuous insurance enrollment from at least 1 month prior to the month of diagnosis to 12 months after diagnosis of melanoma. Main Outcomes and Measures: Surgical delay, defined as definitive surgical excision occurring more than 6 weeks after melanoma diagnosis. Generalized linear models with log link, Poisson distributions, and robust standard errors were used to estimate adjusted risk ratios (RRs) to model risk of delay in definitive surgery. Results: A total of 7629 patients were included (4210 [55%] female; mean [SD] age, 64 [15] years), 48% (n = 3631) Medicare, 48% (n = 3667) privately insured, and 4% (n = 331) Medicaid patients. Privately insured patients were least likely to experience a delay in definitive surgery, followed by Medicare and Medicaid patients (519 [14%], 609 [17%], and 79 [24%], respectively; P < .001). After demographic adjustment, the risk of surgical delay was significantly increased in patients with Medicaid compared with private insurance (RR, 1.36; 95% CI, 1.09-1.70). Delays were more likely in nonwhite patients (RR, 1.38; 95% CI, 1.02-1.87). Surgical delays were less likely if the physician performing the surgery (RR, 0.82; 95% CI, 0.72-0.93) or the diagnosing clinician (RR, 0.81; 95% CI, 0.71-0.93) was a dermatologist as compared with a nondermatologist. Conclusion and Relevance: Surgical treatment delays were common but were less prevalent in patients diagnosed or surgically treated by a dermatologist. Medicaid patients experienced the most surgical delays. A reduction in delays in melanoma surgery could be achieved through better access to specialty care and cross-disciplinary coordination.

Reducing Racial Disparities in Breast Cancer Care: The Role of 'Big Data'.

Advances in a wide array of scientific technologies have brought data of unprecedented volume and complexity into the oncology research space. These novel big data resources are applied across a variety of contexts-from health services research using data from insurance claims, cancer registries, and electronic health records, to deeper and broader genomic characterizations of disease. Several forms of big data show promise for improving our understanding of racial disparities in breast cancer, and for powering more intelligent and far-reaching interventions to close the racial gap in breast cancer survival. In this article we introduce several major types of big data used in breast cancer disparities research, highlight important findings to date, and discuss how big data may transform breast cancer disparities research in ways that lead to meaningful, lifesaving changes in breast cancer screening and treatment. We also discuss key challenges that may hinder progress in using big data for cancer disparities research and quality improvement.

Data Linkage to Improve Geriatric Oncology Research: A Feasibility Study.

Older adults (aged 65 years and older) diagnosed with cancer account for most cancer-related morbidity and mortality in the United States but are often underrepresented on clinical trials. Recent attention from a variety of professional, research, regulatory, and patient advocacy groups has centered on data linkage and data sharing as a means to capture patient information and outcomes outside of clinical trials to accelerate progress in the fight against cancer. The development of a more robust observational research data infrastructure would help to address gaps in the evidence base regarding optimal approaches to treating cancer among the growing and complex population of older adults. To demonstrate the feasibility of building such a resource, we linked information from a sample of older adults with cancer in North Carolina using three distinct, but complementary, data sources: (a) the Carolina Senior Registry, (b) the North Carolina Central Cancer Registry, and (c) North Carolina fee-for-service Medicare claims data. A description of the linkage process, metrics, and characteristics of the final cohort is reported. This study highlights the potential for data linkage to improve the characterization of health status among older adults with cancer and the possibility to conduct passive follow-up for outcomes of interest over time. Extensions of these linkage efforts in partnership with other institutions will enhance our ability to generate evidence that can inform the management of older adults with cancer.

Association Between Choice of Radical Prostatectomy, External Beam Radiotherapy, Brachytherapy, or Active Surveillance and Patient-Reported Quality of Life Among Men With Localized Prostate Cancer.

Importance: Patients diagnosed with localized prostate cancer have to decide among treatment strategies that may differ in their likelihood of adverse effects. Objective: To compare quality of life (QOL) after radical prostatectomy, external beam radiotherapy, and brachytherapy vs active surveillance. Design, Setting, and Participants: Population-based prospective cohort of 1141 men (57% participation among eligible men) with newly diagnosed prostate cancer were enrolled from January 2011 through June 2013 in collaboration with the North Carolina Central Cancer Registry. Median time from diagnosis to enrollment was 5 weeks, and all men were enrolled with written informed consent prior to treatment. Final follow-up date for current analysis was September 9, 2015. Exposures: Treatment with radical prostatectomy, external beam radiotherapy, brachytherapy, or active surveillance. Main Outcomes and Measures: Quality of life using the validated instrument Prostate Cancer Symptom Indices was assessed at baseline (pretreatment) and 3, 12, and 24 months after treatment. The instrument contains 4 domains-sexual dysfunction, urinary obstruction and irritation, urinary incontinence, and bowel problems-each scored from 0 (no dysfunction) to 100 (maximum dysfunction). Propensity-weighted mean domain scores were compared between each treatment group vs active surveillance at each time point. Results: Of 1141 enrolled men, 314 pursued active surveillance (27.5%), 469 radical prostatectomy (41.1%), 249 external beam radiotherapy (21.8%), and 109 brachytherapy (9.6%). After propensity weighting, median age was 66 to 67 years across groups, and 77% to 80% of participants were white. Across groups, propensity-weighted mean baseline scores were 41.8 to 46.4 for sexual dysfunction, 20.8 to 22.8 for urinary obstruction and irritation, 9.7 to 10.5 for urinary incontinence, and 5.7 to 6.1 for bowel problems. Compared with active surveillance, mean sexual dysfunction scores worsened by 3 months for patients who received radical prostatectomy (36.2 [95% CI, 30.4-42.0]), external beam radiotherapy (13.9 [95% CI, 6.7-21.2]), and brachytherapy (17.1 [95% CI, 7.8-26.6]). Compared with active surveillance at 3 months, worsened urinary incontinence was associated with radical prostatectomy (33.6 [95% CI, 27.8-39.2]); acute worsening of urinary obstruction and irritation with external beam radiotherapy (11.7 [95% CI, 8.7-14.8]) and brachytherapy (20.5 [95% CI, 15.1-25.9]); and worsened bowel symptoms with external beam radiotherapy (4.9 [95% CI, 2.4-7.4]). By 24 months, mean scores between treatment groups vs active surveillance were not significantly different in most domains. Conclusions and Relevance: In this cohort of men with localized prostate cancer, each treatment strategy was associated with distinct patterns of adverse effects over 2 years. These findings can be used to promote treatment decisions that incorporate individual preferences.

Cost-Effectiveness Analysis of Four Simulated Colorectal Cancer Screening Interventions, North Carolina.

INTRODUCTION: Colorectal cancer (CRC) screening rates are suboptimal, particularly among the uninsured and the under-insured and among rural and African American populations. Little guidance is available for state-level decision makers to use to prioritize investment in evidence-based interventions to improve their population's health. The objective of this study was to demonstrate use of a simulation model that incorporates synthetic census data and claims-based statistical models to project screening behavior in North Carolina. METHODS: We used individual-based modeling to simulate and compare intervention costs and results under 4 evidence-based and stakeholder-informed intervention scenarios for a 10-year intervention window, from January 1, 2014, through December 31, 2023. We compared the proportion of people living in North Carolina who were aged 50 to 75 years at some point during the window (that is, age-eligible for screening) who were up to date with CRC screening recommendations across intervention scenarios, both overall and among groups with documented disparities in receipt of screening. RESULTS: We estimated that the costs of the 4 intervention scenarios considered would range from $1.6 million to $3.75 million. Our model showed that mailed reminders for Medicaid enrollees, mass media campaigns targeting African Americans, and colonoscopy vouchers for the uninsured reduced disparities in receipt of screening by 2023, but produced only small increases in overall screening rates (0.2-0.5 percentage-point increases in the percentage of age-eligible adults who were up to date with CRC screening recommendations). Increased screenings ranged from 41,709 additional life-years up to date with screening for the voucher intervention to 145,821 for the mass media intervention. Reminders mailed to Medicaid enrollees and the mass media campaign for African Americans were the most cost-effective interventions, with costs per additional life-year up to date with screening of $25 or less. The intervention expanding the number of endoscopy facilities cost more than the other 3 interventions and was less effective in increasing CRC screening. CONCLUSION: Cost-effective CRC screening interventions targeting observed disparities are available, but substantial investment (more than $3.75 million) and additional approaches beyond those considered here are required to realize greater increases population-wide.

Using Procedure Codes to Define Radiation Toxicity in Administrative Data: The Devil is in the Details.

BACKGROUND: Systematic coding systems are used to define clinically meaningful outcomes when leveraging administrative claims data for research. How and when these codes are applied within a research study can have implications for the study validity and their specificity can vary significantly depending on treatment received. SUBJECTS: Data are from the Surveillance, Epidemiology, and End Results-Medicare linked dataset. STUDY DESIGN: We use propensity score methods in a retrospective cohort of prostate cancer patients first examined in a recently published radiation oncology comparative effectiveness study. RESULTS: With the narrowly defined outcome definition, the toxicity event outcome rate ratio was 0.88 per 100 person-years (95% confidence interval, 0.71-1.08). With the broadly defined outcome, the rate ratio was comparable, with 0.89 per 100 person-years (95% confidence interval, 0.76-1.04), although individual event rates were doubled. Some evidence of surveillance bias was suggested by a higher rate of endoscopic procedures the first year of follow-up in patients who received proton therapy compared with those receiving intensity-modulated radiation treatment (11.15 vs. 8.90, respectively). CONCLUSIONS: This study demonstrates the risk of introducing bias through subjective application of procedure codes. Careful consideration is required when using procedure codes to define outcomes in administrative data.

Framework for Deploying a Virtualized Computing Environment for Collaborative and Secure Data Analytics.

INTRODUCTION: Large amounts of health data generated by a wide range of health care applications across a variety of systems have the potential to offer valuable insight into populations and health care systems, but robust and secure computing and analytic systems are required to leverage this information. FRAMEWORK: We discuss our experiences deploying a Secure Data Analysis Platform (SeDAP), and provide a framework to plan, build and deploy a virtual desktop infrastructure (VDI) to enable innovation, collaboration and operate within academic funding structures. It outlines 6 core components: Security, Ease of Access, Performance, Cost, Tools, and Training. CONCLUSION: A platform like SeDAP is not simply successful through technical excellence and performance. It's adoption is dependent on a collaborative environment where researchers and users plan and evaluate the requirements of all aspects.

Statewide geographic variation in outcomes for adults with acute myeloid leukemia in North Carolina.

BACKGROUND: Population-based studies have demonstrated survival disparities related to socioeconomic factors for patients with acute myeloid leukemia (AML). The objective of the current study was to determine whether the local health care infrastructure, represented by Area Health Education Centers (AHEC) region, or treating center experience, represented by National Cancer Institute Comprehensive Cancer Center (NCICCC) designation, were associated with outcomes among patients with AML in North Carolina. METHODS: Patients who were diagnosed with AML from 2003 to 2009 were identified using the University of North Carolina Lineberger Integrated Cancer Information and Surveillance System, a database linking insurance claims to the North Carolina Cancer Registry. A Cox proportional-hazards model was used to explore survival based on AHEC region. A subset of patients who received inpatient chemotherapy was examined to evaluate the impact of treatment at an NCICCC. RESULTS: Nine hundred patients were identified in the study period, 553 of whom received inpatient chemotherapy therapy within 30 days of diagnosis. Almost one-half of these patients (n = 294) received chemotherapy at a non-NCICCC. Among the patients who received intensive inpatient therapy, residence in 3 of 9 AHEC regions was associated with a higher risk of mortality (hazard ratio: range, 1.97-4.03; P < .01) at 1 year in multivariate analysis. Treatment at a non-NCICCC was not associated with an increased risk of mortality at 1 year (hazard ratio, 1.25; 95% confidence interval, 0.95-1.65). CONCLUSIONS: Survival among patients with AML in North Carolina varies according to geographic region. Further examination of local practice and referral patterns may inform strategies to improve AML outcomes across the state. Cancer 2016;122:3041-3050. © 2016 American Cancer Society.

Clinical Benefits Associated With Medicaid Coverage Before Diagnosis of Gynecologic Cancers.

PURPOSE: Many low-income patients enroll in Medicaid at the time of cancer diagnosis, which improves survival outcomes. Medicaid enrollment before cancer diagnosis may confer additional benefits. Our objective was to compare stage at diagnosis and overall mortality between women with and without Medicaid enrollment before gynecologic cancer diagnosis. METHODS AND MATERIALS: Women younger than 65 years with a gynecologic cancer (2003 to 2008) were identified through the North Carolina Central Cancer Registry and linked to state Medicaid enrollment files. Those with and without Medicaid enrollment within 6 months before diagnosis were identified. Propensity matching was used to balance the exposure groups. Stage at diagnosis was evaluated by using logistic regression, and all-cause mortality was assessed with Cox proportional hazard models. RESULTS: Of 564 women, one half (n = 282) had prediagnosis Medicaid enrollment. Disease sites included the cervix (44%), uterus (25%), ovary (26%), and vulva/vagina (5%). More than one half (51%) of cancers were advanced stage. Women without prediagnosis Medicaid had an increased odds of advanced-stage disease (hazard ratio, 1.46; 95% CI, 1.03 to 2.05). Crude survival outcomes differed significantly between the groups; however, when adjusted for stage at diagnosis, lack of prediagnosis Medicaid coverage had a hazard ratio of 1.19 (95% CI, 0.92 to 1.53). CONCLUSION: Medicaid enrollment before gynecologic cancer diagnosis is associated with an earlier stage at presentation. Given the existence of a cervical cancer screening program in North Carolina and lack of Medicaid expansion, these data suggest that screening programs alone are not sufficient to counteract the delay in diagnosis that is common for uninsured individuals.

Referral patterns between high- and low-volume centers and associations with uterine cancer treatment and survival: a population-based study of Medicare, Medicaid, and privately insured women.

BACKGROUND: High-volume center surgery and gynecologic oncology care are associated with improved outcomes for women with uterine cancer. Referral patterns, from biopsy through to chemotherapy, may have patients interacting with high-volume centers for all, a portion, or none of their care. The relative frequency, the underlying factors that contribute to referral, and the potential impact of these referral patterns on treatment outcomes are unknown. OBJECTIVE: We sought to analyze the referral patterns and subsequent impact of care sites on treatment for women with high- and low-risk uterine cancer. STUDY DESIGN: This is a population-based retrospective cohort study of uterine cancer cases from 2004 through 2009 in North Carolina. Using state cancer registry files linked to Medicare, Medicaid, and private payer insurance claims, we analyzed referral and treatment patterns by annual surgical volume (high ≥12/y). We examined clinical and demographic factors associated with referral and used modified Poisson regression to evaluate risk of referral, lymphadenectomy, and chemotherapy. Stratified Kaplan-Meier plots and Cox proportional hazard models were used to examine survival. RESULTS: A total of 2053 women were analyzed, including 34% (n = 677) with grade 3 histology. Of 1630 (80%) women with preoperative biopsies, referral patterns (biopsy to surgery) were: low volume to high volume (n = 652, 40%), followed by high volume to high volume (n = 605, 37%), then low volume to low volume (n = 318, 20%), and the rare high volume to low volume (n = 50, 3%). Women retained in low-volume centers after biopsy were older, were less likely to have private insurance, and had more comorbidities. High-risk histology (aRR, 1.14; 95% confidence interval, 1.04-1.25) was positively associated with referral, while Medicaid insurance was negatively associated with referral (aRR, 0.64; 95% confidence interval, 0.42-0.96). Most women (74%, n = 1557) had surgery at high-volume centers. Lymphadenectomy was less likely at low-volume centers (aRR, 0.71; 95% confidence interval, 0.64-0.77). Similarly, for high-risk patients, the relationship between low-volume center surgery and subsequent chemotherapy was aRR, 0.71 (95% confidence interval, 0.48-1.02). Of 290 women who received chemotherapy, the referral patterns (surgery to chemotherapy) were: high volume-all (high volume to high volume), high volume-hybrid (high volume to low volume, or low volume to high volume), and high volume-none (low volume to low volume). In all, 36% (n = 104/290) received chemotherapy at a low-volume center, the majority (68%, n = 71/104) of whom were referred from high-volume centers after surgery. Crude, unadjusted mortality risk of chemotherapy recipients differed by referral pattern (surgery to chemotherapy): high volume-all patients (hazard ratio, 1.0; referent), followed by high volume-hybrid (hazard ratio, 1.33; 95% confidence interval, 0.93-1.91) then high volume-none patients (RR, 1.95; 95% confidence interval, 1.24-3.08). CONCLUSION: Most women with uterine cancer treated at high-volume centers arrive through referral, which is affected by age and type of insurance, in addition to histology. For high-risk women who require chemotherapy, survival may be related to the extent of treatment received at high-volume centers.

Video Feedback in Key Word Signing Training for Preservice Direct Support Staff.

PURPOSE: Research has demonstrated that formal training is essential for professionals to learn key word signing. Yet, the particular didactic strategies have not been studied. Therefore, this study compared the effectiveness of verbal and video feedback in a key word signing training for future direct support staff. METHOD: Forty-nine future direct support staff were randomly assigned to 1 of 3 key word signing training programs: modeling and verbal feedback (classical method [CM]), additional video feedback (+ViF), and additional video feedback and photo reminder (+ViF/R). Signing accuracy and training acceptability were measured 1 week after and 7 months after training. RESULTS: Participants from the +ViF/R program achieved significantly higher signing accuracy compared with the CM group. Acceptability ratings did not differ between any of the groups. CONCLUSION: Results suggest that at an equal time investment, the programs containing more training components were more effective. Research on the effect of rehearsal on signing maintenance is warranted.

Racial Differences in Diffusion of Intensity-Modulated Radiation Therapy for Localized Prostate Cancer.

Intensity-modulated radiation therapy (IMRT), an innovative treatment option for prostate cancer, has rapidly diffused over the past decade. To inform our understanding of racial disparities in prostate cancer treatment and outcomes, this study compared diffusion of IMRT in African American (AA) and Caucasian American (CA) prostate cancer patients during the early years of IMRT diffusion using the Surveillance, Epidemiology and End Results (SEER)-Medicare linked database. A retrospective cohort of 947 AA and 10,028 CA patients diagnosed with localized prostate cancer from 2002 through 2006, who were treated with either IMRT or non-IMRT as primary treatment within 1 year of diagnoses was constructed. Logistic regression was used to examine potential differences in diffusion of IMRT in AA and CA patients, while adjusting for socioeconomic and clinical covariates. A significantly smaller proportion of AA compared with CA patients received IMRT for localized prostate cancer (45% vs. 53%, p < .0001). Racial differences were apparent in multivariable analysis though did not achieve statistical significance, as time and factors associated with race (socioeconomic, geographic, and tumor related factors) explained the preponderance of variance in use of IMRT. Further research examining improved access to innovative cancer treatment and technologies is essential to reducing racial disparities in cancer care.

Gynecologic cancer outcomes in the elderly poor: A population-based study.

BACKGROUND: Adults aged ≥65 years who are dually enrolled in Medicare and Medicaid are an at-risk group in health care. However, to the best of the authors' knowledge, the outcomes of women with gynecologic cancers in this population are unknown. METHODS: The current study was a population-based cohort study of North Carolina state cancer registry cases of uterine, ovarian, cervical, and vulvar/vaginal cancers (2003-2009), with linked enrollment in Medicare and state Medicaid. Outcomes of all-cause mortality and stage of disease at the time of diagnosis were analyzed as a function of enrollment status using multivariate analysis and survival curves. RESULTS: Of 4522 women aged ≥65 years (3702 of whom were enrolled in Medicare [82%] and 820 of whom were dually enrolled [18%]), there were 2286 cases of uterine (51%), 1587 cases of ovarian (35%), 302 cases of cervical (7%), and 347 cases of vulvar/vaginal (8%) cancers. Dual enrollees had increased all-cause mortality overall (adjusted hazard ratio [aHR], 1.34; 95% confidence interval [95% CI], 1.19-1.49), and within each cancer site (uterine: aHR, 1.22 [95% CI, 1.02-1.47]; ovarian: aHR, 1.25 [95% CI, 1.05-1.49]; cervical: aHR, 1.34 [95% CI, 0.96-1.87]; and vulvar/vaginal: aHR, 1.93 [95% CI, 1.36-2.72]). Increased odds of advanced-stage disease at the time of diagnosis among dual enrollees was only present in patients with uterine cancer (adjusted odds ratio, 1.38; 95% CI, 1.06-1.79). Stratified survival curves demonstrated the strongest disparities among women with early-stage uterine and early-stage vulvar/vaginal cancers. CONCLUSIONS: Women aged ≥65 years who were dually enrolled in Medicare and Medicaid were found to have an overall 34% increase in all-cause mortality after diagnosis with a gynecologic cancer compared with the non-dually enrolled Medicare population. Women with early-stage uterine and vulvar/vaginal cancers appeared to have the most disparate outcomes. Because these malignancies are generally curable, they have the most potential for benefit from targeted interventions.