Nengliang Yao

Breast Cancer Screening, Area Deprivation, and Later-Stage Breast Cancer in Appalachia: Does Geography Matter?

OBJECTIVE To model the relationship of an area-based measure of a breast cancer screening and geographic area deprivation on the incidence of later stage breast cancer (LSBC) across a diverse region of Appalachia. DATA SOURCE Central cancer registry data (2006-2008) from three Appalachian states were linked to Medicare claims and census data. STUDY DESIGN Exploratory spatial analysis preceded the statistical model based on negative binomial regression to model predictors and effect modification by geographic subregions. PRINCIPAL FINDINGS Exploratory spatial analysis revealed geographically varying effects of area deprivation and screening on LSBC. In the negative binomial regression model, predictors of LSBC included receipt of screening, area deprivation, supply of mammography centers, and female population aged>75 years. The most deprived counties had a 3.31 times greater rate of LSBC compared to the least deprived. Effect of screening on LSBC was significantly stronger in northern Appalachia than elsewhere in the study region, found mostly for high-population counties. CONCLUSIONS Breast cancer screening and area deprivation are strongly associated with disparity in LBSC in Appalachia. The presence of geographically varying predictors of later stage tumors in Appalachia suggests the importance of place-based health care access and risk.

Mammography Use After the 2009 Debate

In November 2009, the United States Preventive Services Task Force (USPSTF) updated their guidelines to recommend against routine screening mammography for women aged 40 to 49 years and recommended biennial instead of annual mammography for women aged 50 to 74 years for women of average risk.1,2 The Task Force also concluded that “current evidence is insufficient to assess the additional benefits and harms of screening mammography in women age 75 years or older (p.716).”1 The guideline update invoked many medical societies to release their own guidelines to support annual mammogram in women age 40 years and older.3 Most private and public insurers continued to cover annual mammography for women age 40 years and older.4-7 Moreover, breast cancer screening is the only preventive procedure that the Patient Protection and Affordable Care Act (ACA) coverage did not match the 2009 USPSTF recommendations and instead, covers annual mammography without co-pay or co-insurance for women starting at age 40 years of average risk.8 The National Breast and Cervical Cancer Early Detection Program continues to pay for annual mammography for underserved women aged 40 to 64 years of average risk.9 We used the Medical Expenditure Panel Survey-National Health Interview Survey (MEPS-NHIS) linked data to identify women aged 41 years and older. We obtained person-level data covering three calendar years (2008-2010). Women aged 41 years or older were asked about mammography use in the past year three times during the study period. We stratified women into three age groups: 41 to 49, 51 to 74, and 76 years and older. We reported trends of the percentage of women who reported a mammogram in the past year by age group. We estimated logistic multivariate regression models with person-specific fixed effects to compare self-reported mammography screening in each of the three years. Variables in the regression analyses include survey year, household income compared to federal poverty line, insurance status, whether the respondent has a usual source of care, and self-rated health status measure. Because we stratify by age, we do not further control for it in the regression models. Insurance status was not controlled in the analyses of the age group 75 years of older because they are by and large Medicare beneficiaries. The model included person-specific fixed effects to account for unobservable characteristics that could bias estimates of mammography utilization. In the 41 to 49 age group, the percentage of women reporting a past-year mammogram rose from 46% in 2008 to 56% in 2010 (p<0.05). We have observed The mammography rates in older women were virtually unchanged (Figure 1). Table 1 confirms the patterns observed. Women aged 41 to 49 years (odds ratio=2.00, 95% CI: 1.26-3.17) were more likely to report a past-year mammogram in 2010 than in 2008. For women aged 51 to 74 and 76 or older, the past-year mammograms were unchanged from 2008 to 2010 in the multivariate analyses. Women aged 51 to 74 years who had a usual source of care were more likely to report mammography in the past year (odds ratio =2.84, 95% CI: 1.60-5.04). Figure 1 Percentage of women reporting a past-year mammogram Table 1 The Odds Ratio (95% CI) By following a cohort of women from 2008 to 2010, we found that mammography screening rates did not decrease in any age group after the 2009 issuance of guideline changes. Contrasting to a downward trend in mammography rates between 2000 and 2008,10 the percentage of women who reported a past-year mammogram was higher in 2010 than in 2008 in women aged 41 to 49 years. Although aging may explain some of the increase in mammography use in this age group, it probably safe to conclude that there was very little response to the new USPSTF guideline recommendations for younger women. Mammography rates were unchanged over time in other age groups. The vigorous debate following the USPTF new guidelines may have raised the awareness of breast cancer screening. Continued analysis of mammography rates with more years of longitudinal data will inform whether there is a long-term impact of the 2009 guidelines on screening rates. The next USPSTF breast cancer screening recommendations are due in the near future. We should be prepared for an ongoing debate about balance of benefit and harms, the age at which screening should begin and end, and issues of over-diagnosis/over-treatment.

Cancer Disparities in Rural Appalachia: Incidence, Early Detection, and Survivorship

PURPOSE To document cancer-related health disparities in Appalachia. METHODS The current study investigated disparities in cancer incidence, mortality, and staging between rural Appalachians and those living outside of rural Appalachia. To accomplish this, mortality data for the United States from 1969 to 2011 were obtained from the National Center for Health Statistics (NCHS) using SEER* Stat. These data were used to compare trends in mortality between rural Appalachians, urban Appalachians, rural non-Appalachians, and urban non-Appalachians. Cancer incidence trends, staging, and survivorship data were compared across regions using the SEER-18 Program, which represented 28% of the US population and includes 2 Appalachian states: Georgia and Kentucky. RESULTS Cancer mortality rates declined in all regions, but disparities remained such that rural Appalachia has the highest incidence, while urban non-Appalachia has the lowest. In all but 1 state, rural Appalachians had higher cancer mortality rates than urban non-Appalachians. Cancer incidence declined for all regions except rural Appalachia. Rural Appalachians had lower rates of early stage breast cancer diagnoses than their urban non-Appalachian counterparts. Finally, rural Appalachians had lower 3- and 5-year survival rates than their urban non-Appalachian counterparts. CONCLUSIONS Rural Appalachians are faced with poorer cancer-related health outcomes across the continuum of cancer care. A systematic effort is needed to reduce the burden of cancer for rural Appalachia. Additional research should explore reasons for the disparities that were observed.

Would screening for lung cancer benefit 75- to 84-year-old residents of the United States?

Background: The National Lung Screening Trial demonstrated that screening for lung cancer improved overall survival (OS) and reduced lung cancer mortality in the 55- to 74-year-old age group by increasing the proportion of cancers detected at an early stage. Because of the increasing life expectancy of the American population, we investigated whether screening for lung cancer might benefit men and women aged 75–84 years. Materials/Methods: Rates of non-small cell lung cancer (NSCLC) from 2000 to 2009 were calculated in both younger and older age groups using the surveillance epidemiology and end reporting database. OS and lung cancer-specific survival (LCSS) in patients with Stage I NSCLC diagnosed from 2004 to 2009 were analyzed to determine the effects of age and treatment. Results: The per capita incidence of NSCLC decreased in the 55–74 cohort, but increased in the 75–84 cohort over the study period. Crude lung cancer death rates in the two age groups who had no specific treatment were 39.5 and 44.9%, respectively. These rates fell in both age groups when increasingly aggressive treatment was used. Rates of OS and LCSS improved significantly with increasingly aggressive treatment in the 75–84 age group. The survival benefits of increasingly aggressive treatment in 75- to 84-year-old females did not differ from their counterparts in the younger cohort. Conclusion: Screening for lung cancer might be of benefit to individuals at increased risk of lung cancer in the 75–84 age group. The survival benefits of aggressive therapy are similar in females between 55–74 and 75–84 years old.

Citizenship, length of stay, and screening for breast, cervical, and colorectal cancer in women, 2000–2010

BackgroundTwo factors jointly account for significant gaps in access to health care among immigrants who are present in the U.S.—legal status, and length of residence. The objective of this study is to examine the association between citizenship and length of residence in the U.S. and cancer screening (breast, cervical, and colorectal) among women.MethodsWe analyzed 11 years (2000–2010) of consolidated data from the Medical Expenditure Panel Survey linked with the National Health Interview Survey. Multivariate analyses compared cancer screening among U.S.-born citizens (n = 58,484), immigrant citizens (n = 8,404), and immigrant non-citizens (n = 6,564).ResultsImmigrant non-citizens living in the U.S. for less than 5 years were less likely to receive guideline-concordant breast (OR = 0.68 [0.53–0.88]), cervical (OR = 0.65 [0.54–0.78]), and colorectal (OR = 0.31 [0.19–0.50]) cancer screening compared to U.S.-born citizens. Immigrant citizens and non-citizens living in the U.S. for 5 years or more had higher odds of being screened for breast and cervical cancer compared to U.S.-born citizens; (OR = 1.26 [1.13–1.41] and OR = 1.17 [1.06–1.29]) for immigrant citizens, (OR = 1.28 [1.13–1.45] and OR = 1.23 [1.09–1.38]) for non-citizens. Immigrant non-citizens living in the U.S. for 5 years or more had lower odds of being screened for colorectal cancer compared to U.S.-born citizens (OR = 0.76 [0.65–0.90]).ConclusionsBased on these findings, duration mandates in immigration policy may indirectly influence future pathways to preventive health care and cancer disparities disproportionately affecting immigrant women. We suggest that limits of duration mandates be reevaluated, as they may offer pathways to preventive health care for this vulnerable population, and prevent future cancer disparities.

Individual, Area, and Provider Characteristics Associated With Care Received for Stages I to III Breast Cancer in a Multistate Region of Appalachia

PURPOSE We describe individual, area, and provider characteristics associated with care patterns for early-stage breast cancer in Appalachian counties of Kentucky, North Carolina, Ohio, and Pennsylvania. METHODS Cases of stages I to III breast cancer from 2006 to 2008 were linked to Medicare claims occurring within 1 year of diagnosis. Rates of guideline-concordant endocrine therapy (n = 1,429), chemotherapy (n = 1,480), and radiation therapy (RT) after breast-conserving surgery were studied; RT was studied in women age ≥ 70 years with stage I estrogen receptor (ER) -positive/progesterone receptor (PR) -positive cancer, for whom RT was optional (n = 1,108), and in all others, for whom RT was guideline concordant (n = 1,422). Univariable and multivariable analyses were performed. Independent variables included age, race, county-level economic status, state, surgeon graduation year and volume, comorbidity, diagnosis year, Medicaid/Medicare dual status, histology, tumor size, tumor sequence, positive lymph nodes, ER/PR status, stage, trastuzumab use, and surgery type. RESULTS Population mean age was 74 years; 97% were white. For endocrine therapy, chemotherapy, and RT, guideline concordance was 76%, 48%, and 83%, respectively. Where it was optional, 77% received RT. Guideline-concordant endocrine therapy was lower in North Carolina versus Pennsylvania (odds ratio [OR], 0.60; 95% CI, 0.41 to 0.88) and higher if surgeon graduated between 1984 and 1988 versus ≥ 1989 (OR, 1.58; 95% CI, 1.06 to 2.34). Guideline-concordant chemotherapy varied significantly by state, county-level economic status, and surgeon volume. In guideline-concordant RT, lower surgeon volume (v highest) predicted RT use (OR, 1.63; 95% CI, 1.61 to 2.36). In optional RT, North Carolina residence (v Pennsylvania; OR, 0.29; 95% CI, 0.17 to 0.48) and counties with higher economic status (OR, 0.61; 95% CI, 0.40 to 0.94) predicated RT omission. CONCLUSION Notable variation in care by geographic and surgical provider characteristics provides targets for further research in underserved areas.

Health Services & Policy Research in translational medicine

Translational medicine is often defined through its process. Researchers from different disciplines may see the process differently (Figure 1) (1). Basic scientists and clinicians may describe it as the “bench to bedside” approach of medical research (2). Only a few institutes of translational medicine realize that Health Services & Policy Research (HSPR) is an important component in translational medicine (3,4). Health services & policy researchers can bridge laboratory research, clinical studies, community practice, and health policy to improve public health. Figure 1 Process of translational medicine from different researchers’ perspective. The goal of translational medicine is to translate academic research into population health (5). US National Health Institute launched the Clinical and Translational Science Awards (CTSA) program in 2006 to strengthen the full spectrum of translational research. In 2012, NIH published a summary report based on the stakeholders’ feedback about the CTSA program. Only two vague long-term outcomes were proposed to measure the value added by the CTSA program: increased utilization of new treatments in the community and community health indicators improvement (6). However, the CTSA program has realized that NIH should engage with Center of Medicare and Medicaid Services (CMS) and Agency of Healthcare Research and Quality (AHRQ) to promote HSPR such as comparative effectiveness research and patient centered outcomes research. Basic scientists and clinicians need to work synergistically with health services & policy researchers in the translational process. HSPR in translational medicine is different from the biostatistical support in the current CTSA program. HSPR evaluates effectiveness and cost-effectiveness of the new technology or treatment with observational data and survey data when the new treatment expands discovery to larger patient populations. HSPR employs comparative effectiveness research to determine if a certain treatment or technology works in a real-world setting when the practice-oriented stage of translational research is implemented and find out subgroups of patients who benefit the most (or the least) from the new therapy. If everything was successful, we need to evaluate the current healthcare policy and delivery system to identify barriers to disseminate and implement the new therapy and propose certain policy changes to efficiently reach clinicians and patients. In summary, translational medicine is not just bench to bedside, prototype to device, or beaker to pill. HSPR is an essential component of translational medicine. It is a critical move for Annals of Translational Medicine to create a new HSPR column. This new column will provide a forum for the researches that bridge academic research, health policy, and medical practice. The articles appearing in this column will be authored by scholars from universities, government, private research organizations, and industry. We welcome all submissions that examine how and whether new therapies and research knowledge reach the intended people and are implemented efficiently. The publications from the HSPR column will strengthen communication with practitioners and policymakers and influence medical practice and health policy at all administrative levels.

Patterns of cancer screening, incidence and treatment disparities in China: protocol for a population-based study

Introduction Cancer has become the leading cause of death in China. Several knowledge gaps exist with respect to the patterns of cancer care and disparities in China. Chinese healthcare researchers do not have access to cancer research data of high quality. Only cancer incidence and mortality rates have been analysed in China while the patterns of cancer screening and treatment and disparities have not been rigorously examined. Potential disparities in cancer care by socioeconomic status have not been analysed in the previous literature. Population-based estimates of cancer care costs remain unexamined in China. This project will depict the pattern of cancer screening, incidence and treatment in Shandong province and enhance our understanding of causes of disparities in cancer control. Methods and analysis We will create the first linked database of cancer registry and health insurance claims in China. We obtained cancer registry data on breast, gastrointestinal and lung cancer incidence from 2011 to 2014 and their health insurance claims information from 6 cities/counties of 10.63 million population and validated it with hospital discharge data. A 1600 participant survey will be administered to collect additional information of patients’ socioeconomic status, employment and cancer care costs. Frequency analysis, spatial data exploratory analysis, multivariate logistic regression with instrumental variable, generalised linear regression and subgroup analysis will be used to analyse the following: the receipt of cancer screening, stage at diagnosis, guideline-concordant treatment and cancer care costs. Patient characteristics, tumour features, hospital characteristics, patient comorbidities and county-level descriptors will be used as covariates in the multivariate analysis. Ethics and dissemination The Institutional Review Board of the School of Public Health of Shandong University approved this study (20140201). Data compiled from this project will be made available to all Chinese healthcare researchers. Study results will be disseminated through peer-reviewed publications and presentations at national and international meetings.

Diabetes management before and after cancer diagnosis: missed opportunity.

BACKGROUND Few studies have examined the management of comorbidities in cancer patients. This study used population-based data to estimate the guideline concordance rates for diabetes management before and after cancer diagnosis and examined if diabetes management services among cancer patients was associated with characteristics of the hospital where the patient was treated. METHODS We linked 2005-2009 Medicare claims data to information on 2,707 breast and colorectal cancers patients in state cancer registry files. Multivariate logistic regression models examined hospital characteristics associated with receipt of diabetes management care after cancer diagnosis. RESULTS The rates of HbAlc testing, LDL-C testing, and retinal eye exam decreased from 72.7%, 79.6%, and 57.9% before cancer diagnosis to 58.3%, 69.5%, and 55.8% after diagnosis. The pre- and post-diagnosis diabetes management care was not significantly different by hospital characteristics in the bivariate analysis except for that the distance between residence and hospital was negatively related to retinal eye exam after diagnosis (P<0.05). The multivariate analysis did not identify any significant differences in diabetes management care after cancer diagnosis by hospital characteristics. CONCLUSIONS Cancer patients received fewer diabetes management care after diagnosis than prior to diagnosis, even for those who were treated in large comprehensive centers. This may reflect a missed opportunity to connect diabetic cancer patients to diabetes care. This study provides benchmarks to measure improvements in comorbidity management among cancer patients.

The Effects of Hospital Characteristics on Delays in Breast Cancer Diagnosis in Appalachian Communities: A Population-Based Study.

PURPOSE Despite being generally accepted that delays in diagnosing breast cancer are of prognostic and psychological concern, the influence of hospital characteristics on such delays remains poorly understood, especially in rural and underserved areas. However, hospital characteristics have been tied to greater efficiency and warrant further investigation as they may have implications for breast cancer care in these areas. METHODS Study data were derived from the Kentucky, North Carolina, Ohio, and Pennsylvania state central cancer registries (2006-2008). We then linked Medicare enrollment files and claims data (2005-2009), the Area Resource File (2006-2008), and the American Hospital Association Annual Survey of Hospitals (2007) to create an integrated data set. Hierarchical linear modeling was used to regress the natural log of breast cancer diagnosis delay on a number of hospital-level, demographic, and clinical characteristics. FINDINGS The baseline study sample consisted of 4,547 breast cancer patients enrolled in Medicare that lived in Appalachian counties at the time of diagnosis. We found that hospitals with for-profit ownership (P < .01) had shorter diagnosis delays than their counterparts. Estimates for comprehensive oncology services, system membership and size were not statistically significant at conventional levels. CONCLUSIONS Some structural characteristics of hospitals (eg, for-profit ownership) in the Appalachian region are associated with having shorter delays in diagnosing breast cancer. Researchers and practitioners must go beyond examining patient-level demographic and tumor characteristics to better understand the drivers of timely cancer diagnosis, especially in rural and underserved areas.