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Background: Pneumococcal conjugate vaccines (PCVs) provide strong direct protection in children, while limited data are available on their indirect effect on mortality among older age groups. This multicountry study aimed to assess the population-level impact of pediatric PCVs on all-cause pneumonia mortality among children ≥5 years of age, and invasive pneumococcal disease (IPD) cases in Chile., Methods: Demographic and mortality data from Argentina, Brazil, Chile, Colombia, and Mexico were collected considering the ≥ 5-year-old population, from 2000 to 2019, with 1 795 789 deaths due to all-cause pneumonia. IPD cases in Chile were also evaluated. Time series models were employed to evaluate changes in all-cause pneumonia deaths during the postvaccination period, with other causes of death used as synthetic controls for unrelated temporal trends., Results: No significant change in death rates due to all-cause pneumonia was detected following PCV introduction among most age groups and countries. The proportion of IPD cases caused by vaccine serotypes decreased from 29% (2012) to 6% (2022) among people aged ≥65 years in Chile., Discussion: While an effect of PCV against pneumonia deaths (a broad clinical definition that may not be specific enough to measure indirect effects) was not detected, evidence of indirect PCV impact was observed among vaccine-type-specific IPD cases., Competing Interests: Potential conflicts of interest . D. M. W. has received consulting fees from Pfizer, Merck, Affinivax, and Matrivax for work unrelated to this article; and is Principal Investigator on grants from Pfizer and Merck to Yale University for work unrelated to this article. All other authors report no potential conflicts. All authors have submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Conflicts that the editors consider relevant to the content of the manuscript have been disclosed., (© The Author(s) 2024. Published by Oxford University Press on behalf of Infectious Diseases Society of America.)

Meta-analysis is a powerful analytic method for summarizing effect estimates across studies. However, conventional meta-analysis often assumes a linear exposure-outcome relationship and does not account for variability over the exposure ranges. In this work, we first used simulation techniques to illustrate that the linear-based meta-analytical approach may result in oversimplistic effect estimation based on three plausible non-linear exposure-outcome curves (S-shape, inverted U-shape, and M-shape). We showed that subgroup meta-analysis that stratifies on exposure levels can investigate non-linearity and identify the consistency of effect magnitudes in these simulated examples. Next, we examined the heterogeneity of effect estimates across exposure ranges in two published linear-based meta-analyses of prenatal exposure to per- and polyfluoroalkyl substances (PFAS) on changes in mean birth weight or risk of preterm birth. The re-analysis found some varying effect sizes and potential heterogeneity when restricting to different PFAS exposure ranges, but findings were sensitive to the cut-off choices used to rank the exposure levels. Finally, we discussed methodological challenges and recommendations for detecting and interpreting potential non-linear associations in meta-analysis. Using meta-analysis without accounting for exposure range could contribute to literature inconsistency for exposure-induced health effects and impede evidence-based policymaking. Therefore, investigating result heterogeneity by exposure range is recommended., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Studies of the relationships between environmental exposures and adverse health outcomes often rely on a two-stage statistical modeling approach, where exposure is modeled/predicted in the first stage and used as input to a separately fit health outcome analysis in the second stage. Uncertainty in these predictions is frequently ignored, or accounted for in an overly simplistic manner when estimating the associations of interest. Working in the Bayesian setting, we propose a flexible kernel density estimation (KDE) approach for fully utilizing posterior output from the first stage modeling/prediction to make accurate inference on the association between exposure and health in the second stage, derive the full conditional distributions needed for efficient model fitting, detail its connections with existing approaches, and compare its performance through simulation. Our KDE approach is shown to generally have improved performance across several settings and model comparison metrics. Using competing approaches, we investigate the association between lagged daily ambient fine particulate matter levels and stillbirth counts in New Jersey (2011-2015), observing an increase in risk with elevated exposure 3 days prior to delivery. The newly developed methods are available in the R package KDExp., (© The Author 2022. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Background: Since 2014, multiple outbreaks of human immunodeficiency virus (HIV) among people who inject drugs have occurred across the United States along with hepatitis C virus (HCV), skin and soft tissue infections (SSTIs), and infective endocarditis (IE), creating a converging public health crisis., Methods: We analyzed the temporal patterns of infectious disease and overdose using a hierarchical Bayesian distributed lag logistic regression model examining the probability that a given geographic area experienced at least 1 HIV case in a given month as a function of the counts/rates of overdose, HCV, SSTI, and IE and associated medical procedures at different lagged time periods., Results: Current-month HIV is associated with increasing HCV cases, abscess incision and drainage, and SSTI cases, in distinct temporal patterns. For example, 1 additional HCV case occurring 5 and 7 months previously is associated with a 4% increase in the odds of observing at least 1 current-month HIV case in a given locale (odds ratios, 1.04 [90% credible interval {CrI}: 1.01-1.10] and 1.04 [90% CrI: 1.00-1.09]). No such associations were observed for echocardiograms, IE, or overdose., Conclusions: Lagged associations in other infections preceding rises in current-month HIV counts cannot be described as predictive of HIV outbreaks but may point toward newly discovered epidemics of injection drug use and associated clinical sequalae, prompting clinicians to screen patients more carefully for substance use disorder and associated infections., Competing Interests: Potential conflicts of interest. The authors: No reported conflicts of interest. All authors have submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Conflicts that the editors consider relevant to the content of the manuscript have been disclosed., (© The Author(s) 2023. Published by Oxford University Press on behalf of Infectious Diseases Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

With increased attention to the financing and structure of healthcare, dramatic increases in the cost of diagnosing and treating cancer, and corresponding disparities in access, the study of healthcare economics and delivery has become increasingly important. The Healthcare Delivery Research Program (HDRP) in the Division of Cancer Control and Population Sciences at the National Cancer Institute (NCI) was formed in 2015 to provide a hub for cancer-related healthcare delivery and economics research. However, the roots of this program trace back much farther, at least to the formation of the NCI Division of Cancer Prevention and Control in 1983. The creation of a division focused on understanding and explaining trends in cancer morbidity and mortality was instrumental in setting the direction of cancer-related healthcare delivery and health economics research over the subsequent decades. In this commentary, we provide a brief history of health economics and healthcare delivery research at NCI, describing the organizational structure and highlighting key initiatives developed by the division, and also briefly discuss future directions. HDRP and its predecessors have supported the growth and evolution of these fields through the funding of grants and contracts; the development of data, tools, and other research resources; and thought leadership including stimulation of research on previously understudied topics. As the availability of new data, methods, and computing capacity to evaluate cancer-related healthcare delivery and economics expand, HDRP aims to continue to support this growth and evolution., (Published by Oxford University Press 2022. This work is written by (a) US Government employee(s) and is in the public domain in the US.)

In the United States, concentrations of criteria air pollutants have declined in recent decades. Questions remain regarding whether improvements in air quality are equitably distributed across subpopulations. We assessed spatial variability and temporal trends in concentrations of particulate matter with an aerodynamic diameter ≤2.5 μm (PM2.5) and ozone (O3) across North Carolina from 2002-2016, and associations with community characteristics. Estimated daily PM2.5 and O3 concentrations at 2010 Census tracts were obtained from the Fused Air Quality Surface Using Downscaling archive and averaged to create tract-level annual PM2.5 and O3 estimates. We calculated tract-level measures of: racial isolation of non-Hispanic Black individuals, educational isolation of non-college educated individuals, the neighborhood deprivation index (NDI), and percentage of the population in urban areas. We fitted hierarchical Bayesian space-time models to estimate baseline concentrations of and time trends in PM2.5 and O3 for each tract, accounting for spatial between-tract correlation. Concentrations of PM2.5 and O3 declined by 6.4 μg/m3 and 13.5 ppb, respectively. Tracts with lower educational isolation and higher urbanicity had higher PM2.5 and more pronounced declines in PM2.5. Racial isolation was associated with higher PM2.5 but not with the rate of decline in PM2.5. Despite declines in pollutant concentrations, over time, disparities in exposure increased for racially and educationally isolated communities., (© The Author(s) 2022. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Estimates of the reproductive number for novel pathogens, such as severe acute respiratory syndrome coronavirus 2, are essential for understanding the potential trajectory of epidemics and the levels of intervention that are needed to bring the epidemics under control. However, most methods for estimating the basic reproductive number (R0) and time-varying effective reproductive number (Rt) assume that the fraction of cases detected and reported is constant through time. We explored the impact of secular changes in diagnostic testing and reporting on estimates of R0 and Rt using simulated data. We then compared these patterns to data on reported cases of coronavirus disease 2019 and testing practices from different states in the United States from March 4, 2020, to August 30, 2020. We found that changes in testing practices and delays in reporting can result in biased estimates of R0 and Rt. Examination of changes in the daily numbers of tests conducted and the percentages of patients who tested positive might be helpful for identifying the potential direction of bias. Changes in diagnostic testing and reporting processes should be monitored and taken into consideration when interpreting estimates of the reproductive number of coronavirus disease., (© The Author(s) 2021. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Background: Limitations in the sensitivity and accessibility of diagnostic tools for childhood tuberculosis contribute to the substantial gap between estimated cases and cases notified to national tuberculosis programs. Thus, tools to make accurate and rapid clinical diagnoses are necessary to initiate antituberculosis treatment in more children., Methods: We analyzed data from a prospective cohort of children <13 years old being routinely evaluated for pulmonary tuberculosis in Cape Town, South Africa, from March 2012 to November 2017. We developed a regression model to describe the contributions of baseline clinical evaluation to the diagnosis of tuberculosis using standardized, retrospective case definitions. We included baseline chest radiographic and Xpert MTB/RIF assay results to the model to develop an algorithm with ≥90% sensitivity in predicting tuberculosis., Results: Data from 478 children being evaluated for pulmonary tuberculosis were analyzed (median age, 16.2 months; interquartile range, 9.8-30.9 months); 242 (50.6%) were retrospectively classified with tuberculosis, bacteriologically confirmed in 104 (43.0%). The area under the receiver operating characteristic curve for the final model was 0.87. Clinical evidence identified 71.4% of all tuberculosis cases in this cohort, and inclusion of baseline chest radiographic results increased the proportion to 89.3%. The algorithm was 90.1% sensitive and 52.1% specific, and maintained a sensitivity of >90% among children <2 years old or with low weight for age., Conclusions: Clinical evidence alone was sufficient to make most clinical antituberculosis treatment decisions. The use of evidence-based algorithms may improve decentralized, rapid treatment initiation, reducing the global burden of childhood mortality., (© The Author(s) 2021. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail: journals.permissions@oup.com.)

Background: Pneumococcal conjugate vaccines (PCVs) are recommended for use in pediatric immunization programs worldwide. Few data are available on their effect against mortality. We present a multicountry evaluation of the population-level impact of PCVs against death due to pneumonia in children < 5 years of age., Methods: We obtained national-level mortality data between 2000 and 2016 from 10 Latin American and Caribbean countries, using the standardized protocol. Time series models were used to evaluate the decline in all-cause pneumonia deaths during the postvaccination period while controlling for unrelated temporal trends using control causes of death., Results: The estimated declines in pneumonia mortality following the introduction of PCVs ranged from 11% to 35% among children aged 2-59 months in 5 countries: Colombia (24% [95% credible interval {CrI}, 3%-35%]), Ecuador (25% [95% CrI, 4%-41%]), Mexico (11% [95% CrI, 3%-18%]), Nicaragua (19% [95% CrI, 0-34%]), and Peru (35% [95% CrI, 20%-47%]). In Argentina, Brazil, and the Dominican Republic, the declines were not detected in the aggregated age group but were detected in certain age strata. In Guyana and Honduras, the estimates had large uncertainty, and no declines were detected. Across the 10 countries, most of which have low to moderate incidence of pneumonia mortality, PCVs have prevented nearly 4500 all-cause pneumonia deaths in children 2-59 months since introduction., Conclusions: Although the data quality was variable between countries, and the patterns varied across countries and age groups, the balance of evidence suggests that mortality due to all-cause pneumonia in children declined after PCV introduction. The impact could be greater in populations with a higher prevaccine burden of pneumonia., (© The Author(s) 2020. Published by Oxford University Press for the Infectious Diseases Society of America.)

Background: The importance of specific serotypes causing invasive pneumococcal disease (IPD) differs by age. Data on pneumococcal carriage in different age groups, along with data on serotype-specific invasiveness, could help explain these age-related patterns and their implications for vaccination., Methods: Using pneumococcal carriage and disease data from Israel, we evaluated the association between serotype-specific IPD in adults and serotype-specific carriage prevalence among children in different age categories, while adjusting for serotype-specific invasiveness. We estimated carriage prevalence using different age groupings that were selected a priori. The Deviance Information Criterion was used to determine which age groupings of carriage data best fit the adult IPD data. Serotype-specific disease patterns were further evaluated by stratifying IPD data by comorbidity status., Results: The relative frequency of serotypes causing IPD differed between adults and children, and also differed between older and younger adults and between adults with and without comorbidities. Serotypes overrepresented as causes of IPD in adults were more commonly carried in older children compared with younger children. In line with this, the serotype-specific frequency of carriage in older children, rather than infants, best correlated with serotype-specific IPD in adults., Conclusions: These analyses demonstrate that the serotype patterns in carriage in older children, rather than infants, are best correlated with disease patterns in adults. This might suggest these older children are more influential for disease patterns in adults. These insights could help in optimizing vaccination strategies to reduce disease burden across all ages., (© The Author(s) 2020. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail: journals.permissions@oup.com.)

Understanding the impact that environmental exposure during different stages of pregnancy has on the risk of adverse birth outcomes is vital for protection of the fetus and for the development of mechanistic explanations of exposure-disease relationships. As a result, statistical models to estimate critical windows of susceptibility have been developed for several different reproductive outcomes and pollutants. However, these current methods fail to adequately address the primary objective of this line of research; how to statistically identify a critical window of susceptibility. In this article, we introduce critical window variable selection (CWVS), a hierarchical Bayesian framework that directly addresses this question while simultaneously providing improved estimation of the risk parameters. Through simulation, we show that CWVS outperforms existing competing techniques in the setting of highly temporally correlated exposures in terms of (i) correctly identifying critical windows and (ii) accurately estimating risk parameters. We apply all competing methods to a case/control analysis of pregnant women in North Carolina, 2005-2008, with respect to the development of very preterm birth and exposure to ambient ozone and particulate matter $<$ 2.5 $\mu$m in aerodynamic diameter, and identify/estimate the critical windows of susceptibility. The newly developed method is implemented in the R package CWVS., (© The Author 2019. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Distributed lag models have been used to identify critical pregnancy periods of exposure (i.e. critical exposure windows) to air pollution in studies of pregnancy outcomes. However, much of the previous work in this area has ignored the possibility of spatial variability in the lagged health effect parameters that may result from exposure characteristics and/or residual confounding. We develop a spatially varying Gaussian process model for critical windows called 'SpGPCW' and use it to investigate geographic variability in the association between term low birth weight and average weekly concentrations of ozone and PM 2:5 during pregnancy by using birth records from North Carolina. SpGPCW is designed to accommodate areal level spatial correlation between lagged health effect parameters and temporal smoothness in risk estimation across pregnancy. Through simulation and a real data application, we show that the consequences of ignoring spatial variability in the lagged health effect parameters include less reliable inference for the parameters and diminished ability to identify true critical window sets, and we investigate the use of existing Bayesian model comparison techniques as tools for determining the presence of spatial variability. We find that exposure to PM 2:5 is associated with elevated term low birth weight risk in selected weeks and counties and that ignoring spatial variability results in null associations during these periods. An R package (SpGPCW) has been developed to implement the new method.

Medical care costing studies have excluded patients with a prior cancer history. This study aims to update methods for estimating medical care costs attributable to cancer and to evaluate the effect of a prior history of cancer on costs for colorectal cancer (CRC) patients. We used Surveillance, Epidemiology, and End Results (SEER)-Medicare data and matched cancer patients to controls without cancer to estimate cancer-attributable costs by phases of care using Medicare 2007-2013 claims. CRC annualized average cancer-attributable costs were $56.0 K, $5.3 K, $92.5 K, and $24.3 K in the initial, continuing, and end-of-life cancer and noncancer death phases, respectively, in 2014 dollars. Costs were higher for patients diagnosed with more advanced stage, younger ages, and nonwhite races. Costs for patients with prior cancers were consistently higher than patients without prior cancers, especially in the continuing (4.9 K vs 7.2 K) and end-of-life noncancer death (22.7 K vs 30.0 K). Our CRC costs improve previous estimates by using more recent data and updated methods., (Published by Oxford University Press 2020. This work is written by US Government employees and is in the public domain in the US.)

Background: Health services researchers have studied how care from oncologists impacts treatment and outcomes for cancer patients. These studies frequently identify physician specialty using files from the Center for Medicare and Medicaid Services (CMS) or the American Medical Association (AMA). The completeness of the CMS data resources, individually or combined, to identify oncologists is unknown. This study assessed the sensitivity of CMS data to capture oncologists included in the AMA Physician Masterfile., Methods: Oncologists were identified from three CMS data resources: physician claims, the National Plan and Provider Enumeration System Registry, and the Medicare Data on Provider Practice and Specialty file. CMS files and AMA data were linked using a unique physician identifier. Sensitivity to identify any oncologists, radiation oncologists (ROs), surgical oncologists (SOs), and medical oncologists (MOs) was calculated for individual and combined CMS files. For oncologists in the AMA data not identified as oncologists in the CMS data, their CMS specialty was assessed., Results: Individual CMS files each captured approximately 83% of the 17 934 oncologists in the AMA Masterfile; combined CMS files captured 90.4%. By specialty, combined CMS data captured 98.2% of ROs, 89.3% of MOs, and 70.1% of SOs. For ROs and SOs in the AMA data not identified as oncologists in the CMS data, their CMS specialty was usually similar to the AMA subspecialty; ROs were radiologists and SOs were surgeons., Conclusion: Using combined files from CMS identified most ROs and MOs found in the AMA, but not most SOs. Determining whether to use the AMA data or CMS files for a particular research project will depend on the specific research question and the type of oncologist included in the study., (Published by Oxford University Press 2020. This work is written by US Government employees and is in the public domain in the US.)

Cancer patients receiving Medicaid have worse prognosis. Patients in 14 Surveillance, Epidemiology, and End Results (SEER) cancer registries were linked to national Medicaid enrollment files, 2006-2013, to determine enrollment status during the year before and after diagnosis. A deterministic algorithm based on Social Security number, Medicare Health Insurance Claim number, sex, and date of birth was utilized. Results were compared with an independent linkage of Kentucky-based SEER and Medicaid data. A total 559 484 cancer cases were linked to national Medicaid enrollment files, representing 15-17% of persons with cancer yearly. About 60% of these cases were a complete match on all variables. There was 99% agreement on enrollment status compared with the Kentucky linked data. SEER data were successfully linked to national Medicaid enrollment data. NCI will make the linked data available to researchers, allowing for more detailed assessments of the impact Medicaid enrollment has on cancer diagnosis and outcomes., (Published by Oxford University Press 2020. This work is written by US Government employees and is in the public domain in the US.)

Background: Chemotherapy information in the population-based cancer registries is underascertained and lacks detail. We conducted a pilot study in the Georgia SEER Cancer Registry (GCR) to investigate the feasibility of supplementing chemotherapy information using billing claims from six private oncology practices (OP)., Methods: To assess cancer patients' representativeness from OP, we compared individuals with invasive first primary cancers diagnosed during 2013-2015 in the GCR (cohort 1) with those who had at least one OP claim in the 12 months after diagnosis (cohort 2). To assess completeness of OP claims to capture chemotherapy (yes or no), we further restricted cohort 2 to patients ages 65 years and older enrolled in fee-for-service Medicare Part A and B from the diagnosis date through 12 months follow-up or to the date of death. With Medicare data serving as the gold standard, sensitivity, specificity, and kappa statistics for the receipt of chemotherapy per OP claims were calculated by demographic and clinical characteristics., Results: Cancer patients seeking care in the OP included in our analysis were not representative of the underlying patient population in the GCR. The practices underrepresented minorities and uninsured while overrepresenting females, persons with high socioeconomic status, patients residing outside the metropolitan Atlanta area, and persons with advance staged disease. The ability of practice claims to identify chemotherapy receipt was moderate (76.1% sensitivity) but varied by demographic and clinical characteristics (76.1-83.0%)., Conclusions: Given the limited ability of OP claims to identify chemotherapy receipt, we suggest analyzing these data for hypothesis generation, but inference should be limited to this patient cohort., (Published by Oxford University Press 2020. This work is written by US Government employees and is in the public domain in the US.)

Background: The National Cancer Institute's Surveillance, Epidemiology, and End Results (SEER)-Medicare-linked database was first created almost 30 years ago. Over time, additional data have been added to the SEER-Medicare database, allowing for expanded insights into the delivery of health care across the cancer continuum from screening to end of life., Methods: This article includes an overview of the current SEER-Medicare database, presenting potential users with an introduction to how the data can facilitate innovative epidemiologic and health services research studies. With a focus on the population 65 years and older, this article presents descriptive data on beneficiary demographics, cancer characteristics, service settings, Medicare coverage (eg, Parts A, B, C, and D), and use (number of services or bills) from 2011 to 2015., Results: From 2011 to 2015, 857 056 cancer patients and 601 470 population-based noncancer controls were added to the database. The database includes detailed tumor characteristics and clinical assessments for cancer cases, and demographics and health-care use (eg, hospitals, outpatient facilities, individual providers, hospice, home health-care providers, and pharmacies) for both cases and controls. Although characteristics varied overall between cases and controls, sufficient cancer-specific matched controls are available. Roughly 60% of cases were enrolled in fee for service at cancer diagnosis. The annual average number of claims per case was 60.7 and 92.3 during the year before and after cancer diagnosis, respectively, and 127.5 during the year before death., Conclusions: The large sample size and diverse array of data on cancer patients and noncancer controls in the SEER-Medicare database make it a unique resource for conducting cancer health services research., (Published by Oxford University Press 2020. This work is written by US Government employees and is in the public domain in the US.)

Oral anticancer medications (OAMs) are increasingly utilized. We evaluated the representativeness and completeness of IQVIA, a large aggregator of pharmacy data, for breast cancer, colon cancer, chronic myeloid leukemia, and myeloma cases diagnosed in six Surveillance, Epidemiology, and End Results Program (SEER) registries between 2007 and 2011. Patient's SEER and SEER-Medicare data were linked and compared with IQVIA pharmacy data from 2006 to 2012 for specific OAMs. Overall, 67.6% of SEER cases had a pharmacy claim in IQVIA during the treatment assessment window. This varied by location, race and ethnicity, and insurance status. IQVIA consistently identified fewer cases who received an OAM of interest than SEER-Medicare. The difference was least pronounced for breast cancer agents and most pronounced for myeloma agents. The IQVIA pharmacy database included a large portion of persons in the SEER areas. Future studies should assess receipt of OAMs for other cancer sites and in different SEER registries., (Published by Oxford University Press 2020. This work is written by US Government employees and is in the public domain in the US.)

Purpose: Health-care claims are of increasing utility as a rich, real-world data resource for conducting treatment-related cancer research. However, multiple dynamic coding nomenclatures exist, leading to study variability. To promote increased standardization and reproducibility, the National Cancer Institute (NCI) developed the Cancer Medications Enquiry Database (CanMED)-Healthcare Common Procedure Coding System (HCPCS) within the Observational Research in Oncology Toolbox., Methods: The CanMED-HCPCS includes codes for oncology medications that a) have a US Food and Drug Administration-approved indication for cancer treatment or treatment-related symptom management; b) are present in National Comprehensive Cancer Network guidelines; or c) carry an orphan drug designation for treatment or management of cancer. Included medications and their HCPCS codes were primarily identified based on Center for Medicare and Medicaid Services annual HCPCS Indices (2012-2018). To demonstrate the utility of the CanMED-HCPCS, use of systemic treatment for stage II-IV colorectal cancer patients included in the Surveillance, Epidemiology, and End Results-Medicare data (2007-2013) was assessed., Results: The CanMED-HCPCS (v2018) includes 332 HCPCS codes for cancer-related medications: chemotherapy (156), immunotherapy (74), hormonal therapy (54), and ancillary therapy (48). Observed treatment trends within the NCI Surveillance, Epidemiology, and End Results-Medicare data were as expected; utilization of each treatment type increased with stage, and immunotherapy was largely confined to use among stage IV patients., Conclusion: The CanMED-HCPCS provides a comprehensive resource that can be used by the research community to facilitate systematic identification of medications within claims or electronic health data using the HCPCS nomenclature and greater reproducibility of cancer surveillance and health services research., (Published by Oxford University Press 2020. This work is written by US Government employees and is in the public domain in the US.)

The growing use of oral systemic therapies and transition of some cancer treatments to the outpatient setting makes capturing all cancer case patients more difficult. We aim to develop algorithms to identify potentially missed incident case patients and estimate impact on incidence rates. We reviewed claims from SEER-Medicare 5% noncancer control patient sample to identify potentially missed chronic myeloid leukemia (CML) and bladder case patients based on diagnosis codes, cancer-related treatments, and oncology consultations. Observed rates of definite missed CML and definite and probable missed bladder case patients were calculated and the impact of missed case patients of these two cancers on SEER 65+ incidence rates were estimated. From 2008 to 2015, the algorithm estimated 781 definite CML case patients missed, increasing the number by 10.7%. From 2007 to 2015, the algorithm estimated 4629 definite and 5772 probable bladder case patients missed, increasing the number by 3.8% to 8.1%. Our algorithms offer potential methods for identifying missed case patients and validating the completeness of cancer registries., (Published by Oxford University Press 2020. This work is written by US Government employees and is in the public domain in the US.)

Background: This article describes characteristics of patients receiving home health following an initial cancer diagnosis, comparing those enrolled in Medicare Advantage (MA) and Traditional Medicare (TM), using the newly linked 2010-2014 National Cancer Institute's Surveillance, Epidemiology, and End Results (SEER)-Medicare and home health Outcome and Assessment Information Set (OASIS) data., Methods: We identified SEER-Medicare beneficiaries with at least one OASIS assessment within 3 months of cancer diagnosis in 2010-2014, and summarized their demographic and clinical characteristics. Demographic and diagnostic data were obtained from the SEER-Medicare data, while further details about cognitive status, mood, function, and medical history were obtained from OASIS. We assessed differences between MA and TM beneficiaries using chi-square tests for independence, t-tests, and Kruskal-Wallis tests., Resutls: We identified 104 023 patients who received home health within 3 months of cancer diagnosis: 81 587 enrolled in TM and 22 436 enrolled in MA. TM cancer patients had higher unadjusted rates of home health use than MA patients (16.3% vs 10.3%, P < .001). TM cancer patients receiving home health had more limitations in their cognitive function than their MA counterparts and longer lengths of service (mean = 42.2 days vs 39.4 days, P < .001; median = 27 vs 26 days, interquartile range = 42)., Conclusion: This study demonstrates the large number of cancer patients in the SEER-Medicare-OASIS data and describes characteristics for TM and MA patients. These newly linked data can be used to assess home health care among older patients with cancer., (© The Author(s) 2020. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Cancer treatment studies commonly exclude patients with prior primary cancers due to difficulties in ascertaining for which site treatment is intended. Surveillance, Epidemiology, and End Results-Medicare patients 65 years and older diagnosed with an index colon or rectal cancer (CRC) or female breast cancer (BC) between 2004 and 2013 were included. Chemotherapy, defined as "any chemotherapy" and more restrictively as "chemotherapy with confirmatory diagnoses," was ascertained based on claims data within 6 months of index cancer diagnosis by prior cancer history. Any chemotherapy use was slightly lower among patients with a prior cancer (CRC: no prior = 17.4%, prior = 16.1%; BC: no prior = 12.9%, prior = 12.0%). With confirmatory diagnoses required, estimates were lower, especially among patients with a prior cancer (CRC: no prior = 16.8%, prior = 13.6%; BC: no prior = 12.6%, prior = 11.0%). These findings suggest that patients with prior cancers can be included in studies of chemotherapy use; requiring confirmatory diagnoses can increase treatment assignment confidence., (Published by Oxford University Press 2020. This work is written by US Government employees and is in the public domain in the US.)

Introduction: Physicians are vital to health-care delivery, but assessing their impact on care can be challenging given limited data. Historically, health services researchers have obtained physician characteristics data from the American Medical Association (AMA) Physician Masterfile. The Center for Medicare and Medicaid Services' Medicare Data on Provider Practice and Specialty (MD-PPAS) file was assessed, as an alternative source of physician data, particularly in the context of cancer health services research., Methods: We used physician National Provider Identifiers in the MD-PPAS data (2008-2014) to identify physicians in the AMA data current as of July 18, 2016. Within each source, we grouped physicians into six broad specialty groups. Percent agreement and Cohen's kappa coefficient (k) were calculated for age, sex, specialty, and practice state., Results: Among the 698 202 included physicians, there was excellent agreement for age (percent agreement = 97.7%, k = 0.97) and sex (99.4%, k = 0.99) and good agreement for specialty (86.1%, k = 0.80). Within specialty, using AMA as the reference, agreement was lowest for oncologists (77%). Approximately 85.9% of physicians reported the same practice state in both data sets., Conclusion: Although AMA data have been commonly used to account for physician-level factors in health services research, MD-PPAS data provide researchers with an alternative option depending on study needs. MD-PPAS data may be optimal if nonphysicians, provider utilization, practice characteristics, and/or temporal changes are of interest. In contrast, the AMA data may be optimal if more granular specialty, physician training, and/or a broader inclusion of physicians is of interest., (Published by Oxford University Press 2020. This work is written by US Government employees and is in the public domain in the US.)

Background: Pneumococcal conjugate vaccines (PCVs) have had a well-documented impact on the incidence of invasive pneumococcal disease (IPD). However, declines in IPD due to vaccine-targeted serotypes have been partially offset by increases in IPD due to nonvaccine serotypes (NVTs). The goal of this study was to quantify serotype-specific changes in the incidence of IPD that occurred in different age groups, with or without certain comorbidities, following the introduction of 7-valent pneumococcal conjugate vaccine (PCV7) and 13-valent pneumococcal conjugate vaccine (PCV13) in the childhood vaccination program in Denmark., Methods: We used nationwide surveillance data for IPD and a hierarchical Bayesian regression framework to estimate changes in the incidence of IPD associated with the introduction of PCV7 (2007) and PCV13 (2010) while controlling for serotype-specific epidemic cycles and unrelated secular trends., Results: Following the introduction of PCV7 and PCV13 in children, the net impact of serotype replacement varied considerably by age group and comorbidities. Differences in the magnitude of serotype replacement were due to variations in the incidence of NVTs in the different risk groups before the introduction of PCVs. The relative increases in the incidence of IPD caused by specific NVTs did not differ appreciably between risk groups in the postvaccination period. Serotype replacement offset a greater proportion of the benefit of PCVs in strata in which the NVTs comprised a larger proportion of cases prior to the introduction of the vaccines., Conclusions: These findings could help to predict the impact of next-generation PCVs in specific risk groups., (© The Author(s) 2018. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail: journals.permissions@oup.com.)

The association between a single interpregnancy interval (IPI) and birth outcomes has not yet been explored using matched methods. We modeled the odds of preterm birth, being small for gestational age, and having low birth weight in a second, live-born infant in a cohort of 192,041 sibling pairs born in Western Australia between 1980 and 2010. The association between IPI and birth outcomes was estimated from the interaction between birth order and IPI (with 18-23 months as the reference category), using conditional logistic regression. Matched analysis showed the odds of preterm birth were higher for siblings born following an IPI of <6 months (adjusted interaction odds ratio = 1.22, 95% confidence interval: 1.06, 1.38) compared with those born after an IPI of 18-23 months. There were no significant differences for IPIs of <6 months for other outcomes (small for gestational age or low birth weight). This is the first study to use matched analyses to investigate the association between a single IPI on birth outcomes. IPIs of <6 months were associated with increased odds of preterm birth in second-born infants, although the association is likely smaller than previously estimated by unmatched studies.

While there is a literature on the distribution of food stores across geographic and social space, much of this research uses cross-sectional data. Analyses attempting to understand whether the availability of stores across neighborhoods is associated with diet and/or health outcomes are limited by a lack of understanding of factors that shape the emergence of new stores and the closure of others. We used quarterly data on supermarket and convenience store locations spanning seven years (2006-2012) and tract-level census data in four US cities: Birmingham, Alabama; Chicago, Illinois; Minneapolis, Minnesota; San Francisco, California. A spatial discrete-time survival model was used to identify factors associated with an earlier and/or later closure time of a store. Sales volume was typically the strongest indicator of store survival. We identified heterogeneity in the association between tract-level poverty and racial composition with respect to store survival. Stores in high poverty, non-White tracts were often at a disadvantage in terms of survival length. The observed patterns of store survival varied by some of the same neighborhood sociodemographic factors associated with lifestyle and health outcomes, which could lead to confusion in interpretation in studies of the estimated effects of introduction of food stores into neighborhoods on health., Competing Interests: The authors have no financial or other conflicts of interest to disclose.

Identifying periods of increased vulnerability to air pollution during pregnancy with respect to the development of adverse birth outcomes can improve understanding of possible mechanisms of disease development and provide guidelines for protection of the child. Exposure to air pollution during pregnancy is typically based on the mother's residence at delivery, potentially resulting in exposure misclassification and biasing the estimation of critical windows of pregnancy. In this study, we determined the impact of maternal residential mobility during pregnancy on defining weekly exposure to particulate matter less than or equal to 10 μm in aerodynamic diameter (PM10) and estimating windows of susceptibility to term low birth weight. We utilized data sets from 4 Connecticut birth cohorts (1988-2008) that included information on all residential addresses between conception and delivery for each woman. We designed a simulation study to investigate the impact of increasing levels of mobility on identification of critical windows. Increased PM10 exposure during pregnancy weeks 16-18 was associated with an increased probability of term low birth weight. Ignoring residential mobility when defining weekly exposure had only a minor impact on the identification of critical windows for PM10 and term low birth weight in the data application and simulation study. Identification of critical pregnancy windows was robust to exposure misclassification caused by ignoring residential mobility in these Connecticut birth cohorts.

Background: There has been a dramatic increase in the incidence of sporadic legionnaires' disease in Connecticut since 1999, but the exact reasons for this are unknown. Therefore, there is a growing need to understand the drivers of legionnaires' disease in the community. In this study, we explored the relationship between the natural environment and the spatial and temporal distribution of legionellosis cases in Connecticut., Methods: We used spatial models and time series methods to evaluate factors associated with the increase and clustering of legionellosis in Connecticut. Stream flow, proximity to rivers, and residence in regional watersheds were explored as novel predictors of disease, while controlling for testing intensity and correlates of urbanization., Results: In Connecticut, legionellosis incidence exhibited a strong pattern of spatial clustering. Proximity to several rivers and residence in the corresponding watersheds were associated with increased incidence of the disease. Elevated rainfall and stream flow rate were associated with increases in incidence 2 weeks later., Conclusions: We identified a novel relationship between the natural aquatic environment and the spatial distribution of sporadic cases of legionellosis. These results suggest that natural environmental reservoirs may have a greater influence on the spatial distribution of sporadic legionellosis cases than previously thought., (© The Author 2017. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail: journals.permissions@oup.com.)

Background: Pneumococcal conjugate vaccines (PCVs) are being used worldwide. A key question is whether the impact of PCVs on pneumonia is similar in low- and high-income populations. However, most low-income countries, where the burden of disease is greatest, lack reliable data that can be used to evaluate the impact. Data from middle-income countries that have both low- and high-income subpopulations can provide a proxy measure for the impact of the vaccine in low-income countries., Methods: We evaluated the impact of PCV10 on hospitalizations for all-cause pneumonia in Brazil, a middle-income country with localities that span a broad range of human development index (HDI) levels. We used complementary time series and spatiotemporal methods (synthetic controls and hierarchical Bayesian spatial regression) to test whether the decline in pneumonia hospitalizations associated with vaccine introduction varied across the socioeconomic spectrum., Results: We found that the declines in all-cause pneumonia hospitalizations in children and young and middle-aged adults did not vary substantially across low and high HDI subpopulations. Moreover, the estimated declines seen in infants and young adults were associated with higher levels of uptake of the vaccine at a local level., Conclusions: These results suggest that PCVs have an important impact on hospitalizations for all-cause pneumonia in both low- and high-income populations., (© The Author 2017. Published by Oxford University Press for the Infectious Diseases Society of America.)

The use of pneumococcal conjugate vaccines (PCVs) in children has a strong indirect effect on disease rates in adults. When children are vaccinated with PCVs, other serotypes that are not targeted by the vaccine can increase in frequency (serotype replacement) and reduce the direct and indirect benefits of the vaccine. To understand and predict the likely impacts of serotype replacement, it is important to know how patterns in the transmission of serotypes among children relate to disease rates in adults. We used data on pneumococcal carriage and disease from Navajo Nation children and adults collected before and after the routine use of PCVs (1998-2012). Using regression models within a Bayesian framework, we found that serotype-specific carriage and invasiveness (disease incidence divided by carriage prevalence) had similar patterns in children and adults. Moreover, carriage in children, invasiveness in children, and a serotype-specific random intercept (which captured additional variation associated with the serotypes) could predict the incidence serotype-specific pneumococcal disease in adults 18-39 years of age and those 40 years of age or older in the era of routine use of PCVs. These models could help us predict the effects of future pneumococcal vaccine use in children on disease rates in adults, and the modeling approach developed here could be used to test these findings in other settings., (© The Author 2016. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Background: Pneumococcal conjugate vaccine (PCV) is now recommended for use in adults in the United States. Because vaccination of children with PCVs protects adults from the targeted serotypes, local variations in PCV uptake among children could influence disease patterns in adults., Methods: We obtained ZIP code-level data on invasive pneumococcal disease (IPD) from an active population-based surveillance system in Connecticut (study interval, 1998-2009) and ZIP code-level data on immunization with at least 3 or at least 4 doses of 7-valent PCV (PCV7) from the state immunization registry. We fit logistic regression models to estimate the proportion of IPD cases among adults aged >40 years that were caused by PCV7-targeted serotypes. Covariates included ZIP code-level socioeconomic indicators (eg, percentage of the population that was black and income per capita), the percentage of the population that received 3 or 4 doses of PCV7 (mean centered), and a linear spline to control for the average rate of decline across all ZIP codes., Results: ZIP codes that had a higher proportion of children that did not complete the 4-dose PCV7 series had a higher proportion of adult IPD cases caused by PCV7 serotypes., Conclusions: Local variations in PCV uptake (and receipt of the booster dose) might influence the effectiveness of PCVs in preventing pneumococcal disease in adults., (© The Author 2015. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail journals.permissions@oup.com.)

Numerous studies have investigated the relationship between the built environment and physical activity. However these studies assume that these relationships are invariant over space. In this study, we introduce a novel method to analyze the association between access to recreational facilities and exercise allowing for spatial heterogeneity. In addition, this association is studied before and after controlling for crime, a variable that could explain spatial heterogeneity of associations. We use data from the Chicago site of the Multi-Ethnic Study of Atherosclerosis of 781 adults aged 46 years and over. A spatially varying coefficient Tobit regression model is implemented in the Bayesian setting to allow for the association of interest to vary over space. The relationship is shown to vary over Chicago, being positive in the south but negative or null in the north. Controlling for crime weakens the association in the south with little change observed in northern Chicago. The results of this study indicate that spatial heterogeneity in associations of environmental factors with health may vary over space and deserve further exploration.

Background: Respiratory syncytial virus (RSV) is a major cause of respiratory infections among young children and can lead to severe disease among some infants. Infants at high risk for severe RSV infection receive monthly injections of a prophylactic monoclonal antibody during the RSV season based on national guidelines. We considered whether a reduced-dose schedule tailored to the local RSV season in the continental United States would provide adequate protection., Methods: Hospitalization data for 1942 counties across 38 states from 1997 to 2009 were obtained from the State Inpatient Databases (Agency for Healthcare Research and Quality). We assessed the timing of RSV epidemics at the county and state levels using a 2-stage hierarchical Bayesian change point model. We used a simple summation approach to estimate the fraction of RSV cases that occur during the window of protection provided by initiating RSV prophylaxis during different weeks of the year., Results: The timing of RSV epidemic onset varied significantly at the local level. Nevertheless, the national recommendations for initiation of prophylaxis provided near-optimal coverage of the RSV season in most of the continental United States. Reducing from 5 to 4 monthly doses (with a later initiation) provides near-optimal coverage (<5% decrease in coverage) in most settings. Earlier optimal dates for initiating 4 doses of prophylaxis were associated with being farther south and east, higher population density, and having a higher percentage of the population that was black or Hispanic., Conclusions: A 4-dose schedule of prophylactic injections timed with local RSV epidemics could provide protection comparable to 5 doses and could be considered as a way to improve the cost-effectiveness of prophylaxis., (© The Author 2015. Published by Oxford University Press on behalf of the Infectious Diseases Society of America. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.)

In reproductive epidemiology, there is a growing interest to examine associations between air pollution exposure during pregnancy and the risk of preterm birth (PTB). One important research objective is to identify critical periods of exposure and estimate the associated effects at different stages of pregnancy. However, population studies have reported inconsistent findings. This may be due to limitations from the standard analytic approach of treating PTB as a binary outcome without considering time-varying exposures together over the course of pregnancy. To address this research gap, we present a Bayesian hierarchical model for conducting a comprehensive examination of gestational air pollution exposure by estimating the joint effects of weekly exposures during different vulnerable periods. Our model also treats PTB as a time-to-event outcome to address the challenge of different exposure lengths among ongoing pregnancies. The proposed model is applied to a dataset of geocoded birth records in the Atlanta metropolitan area between 1999-2005 to examine the risk of PTB associated with gestational exposure to ambient fine particulate matter [Formula: see text]m in aerodynamic diameter (PM[Formula: see text]). We find positive associations between PM[Formula: see text] exposure during early and mid-pregnancy, and evidence that associations are stronger for PTBs occurring around week 30., (© The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Cancer recurrence and disease-free survival are key outcomes for measuring the burden of illness, assessing the quality of cancer care, and informing decisions about increasingly costly cancer therapies. Yet information about recurrence is not collected in cancer registries or other population-based data sources. To address the lack of population-based recurrence information, researchers are increasingly using algorithms applied to health claims to infer recurrence. However, the validity of these approaches has not been comprehensively evaluated. In this commentary, we review existing studies and discuss options for improving the availability of recurrence data. We found that the validity of claims-based approaches appears promising in small, single institution studies, but larger population-based studies have identified substantial limitations with using claims to identify recurrence. With the increasing availability of health data, there are potential options that can be implemented to enhance information about recurrence. These options include design of software for the electronic medical record that enables rapid and standardized reporting of recurrence, use of electronic pathology reports to facilitate streamlined collection of recurrence by cancer registries, and mandates by insurers to require reporting of recurrence on health claims submitted by physicians. All of these options will require that governmental agencies, health insurers, professional societies, and other groups recognize the importance of population-based recurrence data and determine that this information is a priority for assessing cancer outcomes and costs., (Published by Oxford University Press 2015. This work is written by (a) US Government employee(s) and is in the public domain in the US.)

The literature on food stores, neighborhood poverty, and race/ethnicity is mixed and lacks methods of accounting for complex spatial and temporal clustering of food resources. We used quarterly data on supermarket and convenience store locations from Nielsen TDLinx (Nielsen Holdings N.V., New York, New York) spanning 7 years (2006-2012) and census tract-based neighborhood sociodemographic data from the American Community Survey (2006-2010) to assess associations between neighborhood sociodemographic characteristics and food store distributions in the Metropolitan Statistical Areas (MSAs) of 4 US cities (Birmingham, Alabama; Chicago, Illinois; Minneapolis, Minnesota; and San Francisco, California). We fitted a space-time Poisson regression model that accounted for the complex spatial-temporal correlation structure of store locations by introducing space-time random effects in an intrinsic conditionally autoregressive model within a Bayesian framework. After accounting for census tract-level area, population, their interaction, and spatial and temporal variability, census tract poverty was significantly and positively associated with increasing expected numbers of supermarkets among tracts in all 4 MSAs. A similar positive association was observed for convenience stores in Birmingham, Minneapolis, and San Francisco; in Chicago, a positive association was observed only for predominantly white and predominantly black tracts. Our findings suggest a positive association between greater numbers of food stores and higher neighborhood poverty, with implications for policy approaches related to food store access by neighborhood poverty., (© The Author 2014. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Gallstones and cholecystectomy may be related to digestive system cancer through inflammation, altered bile flux, and changes in metabolic hormone levels. Although gallstones are recognized causes of gallbladder cancer, associations with other cancers of the digestive system are poorly established. We used the Surveillance, Epidemiology, and End Results (SEER)-Medicare linked database (1992-2005), which includes 17 cancer registries that cover approximately 26% of the US population, to identify first primary cancers (n = 236,850) occurring in persons aged ≥66 years and 100,000 cancer-free population-based controls frequency-matched by calendar year, age, and gender. Odds ratios and 95% confidence intervals were calculated using logistic regression analysis, adjusting for the matching factors. Gallstones and cholecystectomy were associated with increased risk of noncardia gastric cancer (odds ratio (OR) = 1.21 (95% confidence interval (CI): 1.11, 1.32) and OR = 1.26 (95% CI: 1.13, 1.40), respectively), small-intestine carcinoid (OR = 1.27 (95% CI: 1.01, 1.60) and OR = 1.78 (95% CI: 1.41, 2.25)), liver cancer (OR = 2.35 (95% CI: 2.18, 2.54) and OR = 1.26 (95% CI: 1.12, 1.41)), and pancreatic cancer (OR = 1.24 (95% CI: 1.16, 1.31) and OR = 1.23 (95% CI: 1.15, 1.33)). Colorectal cancer risk associated with gallstones and cholecystectomy decreased with increasing distance from the common bile duct (P-trend < 0.001). Hence, gallstones and cholecystectomy are associated with the risk of cancers occurring throughout the digestive tract.

Colorectal cancer is the third most common cancer in the United States and Canada. Given the high incidence and increased survival of colorectal cancer patients, prevalence is increasing over time in both countries. Using MEDLINE, we conducted a systematic review of the literature published between 2000 and 2010 to describe patterns of colorectal cancer care. Specifically we examined data sources used to obtain treatment information and compared patterns of cancer-directed initial care, post-diagnostic surveillance care, and end-of-life care among colorectal cancer patients diagnosed in the United States and Canada. Receipt of initial treatment for colorectal cancer was associated with the anatomical position of the tumor and extent of disease at diagnosis, in accordance with consensus-based guidelines. Overall, care trends were similar between the United States and Canada; however, we observed differences with respect to data sources used to measure treatment receipt. Differences were also present between study populations within country, further limiting direct comparisons. Findings from this review will allow researchers, clinicians, and policy makers to evaluate treatment receipt by patient, clinical, or system characteristics and identify emerging trends over time. Furthermore, comparisons between health-care systems in the United States and Canada can identify disparities in care, allow the evaluation of different models of care, and highlight issues regarding the utility of existing data sources to estimate national patterns of care.

Colorectal cancer is the second most common cancer in women and the third most common in men worldwide. In this study, we used MEDLINE to conduct a systematic review of existing literature published in English between 2000 and 2010 on patterns of colorectal cancer care. Specifically, this review examined 66 studies conducted in Europe, Australia, and New Zealand to assess patterns of initial care, post-diagnostic surveillance, and end-of-life care for colorectal cancer. The majority of studies in this review reported rates of initial care, and limited research examined either post-diagnostic surveillance or end-of-life care for colorectal cancer. Older colorectal cancer patients and individuals with comorbidities generally received less surgery, chemotherapy, or radiotherapy. Patients with lower socioeconomic status were less likely to receive treatment, and variations in patterns of care were observed by patient demographic and clinical characteristics, geographical location, and hospital setting. However, there was wide variability in data collection and measures, health-care systems, patient populations, and population representativeness, making direct comparisons challenging. Future research and policy efforts should emphasize increased comparability of data systems, promote data standardization, and encourage collaboration between and within European cancer registries and administrative databases.

Cancer is a major component of health-care expenditures in most developed countries. The costs of cancer care are expected to increase due to rising incidence (as the population ages) and increasing use of targeted anticancer therapies. However, epidemiological analysis of patterns of care may be required prior to empirically well-grounded cost analyses. Additionally, comparisons of care between health-care delivery systems and countries can identify opportunities to improve practice. They can also increase understanding of patient outcomes and economic consequences of differences in policies related to cancer screening, treatment, and programs of care. In this study, we compared patterns of colorectal cancer treatment during the first year following diagnosis in two cohorts of elderly patients from some areas of Italy and the United States using cancer registry linked to administrative data. We evaluated hospital use, initial treatments (surgery, chemotherapy, and radiation), and timeliness of surgery and adjuvant therapy, taking into account patient characteristics and clinical features, such as stage at diagnosis and the cancer subsite. We observed greater use of adjuvant chemotherapy in stage III and IV colon cancer patients and adjuvant therapy in all stages of rectal cancer patients in the US cohort. We found a higher rate of open surgeries in the Italian cohort, a similar rate of hospitalization, but a higher number of hospital days in the Italian cohort. However, in spite of structural differences between the United States and Italy in health-care organization and delivery as well as in data collection, patterns of care and the timing of care in the year after diagnosis are generally similar among patients within stage of disease at diagnosis. Comparative studies of the costs associated with patterns of cancer care will be important for future research.

Cancer is an important cause of morbidity in the elderly, and many medical conditions and treatments influence cancer risk. The Surveillance, Epidemiology, and End Results (SEER)-Medicare database can be used to conduct population-based case-control studies that elucidate the etiology of cancer among the US elderly. SEER-Medicare links data on malignancies ascertained through SEER cancer registries to claims from Medicare, the US government insurance program for people over age 65 years. Under one approach described herein, elderly cancer cases are ascertained from SEER data (1987-2005). Matched controls are selected from a 5% random sample of Medicare beneficiaries. Risk factors of interest, including medical conditions and procedures, are identified by using linked Medicare claims. Strengths of this design include the ready availability of data, representative sampling from the US elderly population, and large sample size (e.g., under one scenario: 1,176,950 cases, including 221,389 prostate cancers, 185,853 lung cancers, 138,041 breast cancers, and 124,442 colorectal cancers; and 100,000 control subjects). Limitations reflect challenges in exposure assessment related to Medicare claims: restricted range of evaluable risk factors, short time before diagnosis/selection for ascertainment, and inaccuracies in claims. With awareness of limitations, investigators have in SEER-Medicare data a valuable resource for epidemiologic research on cancer etiology.

Background: Both the United States and Canada offer government-financed health insurance for the elderly, but few studies have compared care at the end of life for cancer patients between the two systems., Methods: We identified care for non-small cell lung cancer (NSCLC) patients who died of cancer at age 65 years and older during 1999-2003. Patients were identified from US Surveillance, Epidemiology, and End Results (SEER)-Medicare data (N = 13,533) and the Ontario Cancer Registry (N = 8100). Health claims during the last 5 months of life identified chemotherapy and emergency room use, hospitalizations, and supportive care. We estimated rates per person-months (PM) for short-term survivors (died <6 months after diagnosis) and longer-term survivors (died ≥6 months after diagnosis), adjusting for demographic differences. To test whether monthly rates in Ontario were statistically significantly different from the United States, standardized differences were computed, and a 99% confidence interval (CI) was constructed to account for the multiple tests performed. All statistical tests were two-sided., Results: Rates of chemotherapy use were statistically significantly higher for SEER-Medicare patients than Ontario patients in every month before death (short-term survivors at 5 months before death: SEER-Medicare, 33.2 patients per 100 PM vs Ontario, 9.5 per 100 PM, rate difference = 23.7 per 100 PM, 99% CI = 18.3 to 29.1 per 100 PM, P < .001; longer-term survivors at 5 months before death: SEER-Medicare, 24.4 patients per 100 PM vs Ontario, 14.5 per 100 PM, rate difference = 9.9 per 100 PM, 99% CI = 7.7 to 12.1 per 100 PM, P <. 001). During the last 30 days of life, fewer SEER-Medicare than Ontario patients were hospitalized (short-term survivors, 49.9 vs 78.6 patients per 100 PM, rate difference = 28.6 per 100 PM, 95% CI = 22.9 to 34.4 per 100 PM, P <. 001; longer-term survivors, 44.1 vs 67.1 patients per 100 PM, rate difference = 23.0 per 100 PM, 95% CI = 18.5 to 27.5 per 100 PM, P < .001)., Conclusions: NSCLC patients in both Ontario and the United States used extensive end-of-life care. Limited availability of hospice care in Ontario and differing attitudes between the United States and Ontario regarding end-of-life care may explain the differences in practice patterns.

Background: Despite reports of increases in the cost of cancer treatment, little is known about how costs of cancer treatment have changed over time and what services have contributed to the increases., Methods: We used data from the Surveillance, Epidemiology, and End Results (SEER)-Medicare linked database for 306,709 persons aged 65 and older and diagnosed with breast, lung, colorectal, or prostate cancer between 1991 and 2002 to assess the number of patients assigned to initial cancer care, from 2 months before diagnosis to 12 months after diagnosis, and mean annual Medicare payments for this care according to cancer type and type of treatment. Mutually exclusive treatment categories were cancer-related surgery, chemotherapy, radiation therapy, and other hospitalizations during the period of initial cancer care. Linear regression models were used to assess temporal trends in the percentage of patients receiving treatment and costs for those treated. We extrapolated our results based on the SEER data to the US Medicare population to estimate national Medicare payments by cancer site and treatment category. All statistical tests were two-sided., Results: For patients diagnosed in 2002, Medicare paid an average of $39,891 for initial care for each lung cancer patient, $41 134 for each colorectal cancer patient, and $20,964 for each breast cancer patient, corresponding to inflation-adjusted increases from 1991 of $7139, $5345, and $4189, respectively. During the same interval, the mean Medicare payment for initial care for prostate cancer declined by $196 to $18261 in 2002. Costs for any hospitalization accounted for the largest portion of payments for all cancers. Chemotherapy use increased markedly for all cancers between 1991 and 2002, as did radiation therapy use (except for colorectal cancers). Total 2002 Medicare payments for initial care for these four cancers exceeded $6.7 billion, with colorectal and lung cancers being the most costly overall., Conclusions: The statistically significant increase in costs of initial cancer treatment reflects more patients receiving surgery and adjuvant therapy and rising prices for these treatments. These trends are likely to continue in the near future, although more efficient targeting of costly therapies could mitigate the overall economic impact of this trend.

Background: Timely estimates of the costs of care for cancer patients are an important element in the formulation of national cancer programs and policies. We estimated net costs of care for elderly cancer patients in the United States for the 18 most prevalent cancers and for all other tumor sites combined., Methods: We used Surveillance, Epidemiology, and End Results-Medicare files to identify 718,907 cancer patients and 1,623,651 noncancer control subjects. Within each tumor site, noncancer control subjects were matched to patients by sex, age group, geographic location, and phase of care (ie, initial, continuing, and last year of life). Costs of care were estimated for each phase by use of Medicare claims data from January 1, 1999, through December 31, 2003. Per-patient net costs of care were applied to the 5-year survival of cancer patients by phase of care to estimate 5-year costs of care and extrapolated to the elderly US Medicare population diagnosed with cancer in 2004., Results: Across tumor sites, mean net costs of care were highest in the initial and last year of life phases of care and lowest in the continuing phase. Mean 5-year net costs varied widely, from less than $20,000 for patients with breast cancer or melanoma of the skin to more than $40,000 for patients with brain or other nervous system, esophageal, gastric, or ovarian cancers or lymphoma. For elderly cancer patients diagnosed in 2004, aggregate 5-year net costs of care to Medicare were estimated to be approximately $21.1 billion. Costs to Medicare were highest for lung, colorectal, and prostate cancers, reflecting underlying incidence, stage distribution at diagnosis, survival, and phase-specific costs for these tumor sites., Conclusions: The costs of cancer care to Medicare are substantial and vary by tumor site, phase of care, stage at diagnosis, and survival.

Background: Although costs of medical care for cancer have been investigated extensively, patient time costs associated with cancer care have rarely been estimated systematically. In this study, we estimated patient time costs associated with cancer care in patients aged 65 years and older in the United States., Methods: We identified 763,527 patients with breast, colorectal, corpus uteri, gastric, head and neck, lung, melanoma of the skin, ovary, prostate, renal, and urinary bladder cancers from linked Surveillance, Epidemiology, and End Results-Medicare files and 1,145,159 noncancer control subjects among Medicare enrollees who were matched by sex, age-group, and geographic location. Frequency of service use was calculated by category for patients and control subjects using Medicare claims data from 1995 to 2001. For each service category, time estimates were combined with service frequency and an hourly value of patient time. Net patient time costs were summed in the initial, continuing, and last-year-of-life phases of care for each tumor site. Net time cost estimates for the initial phase of care were applied to national estimates of numbers of new cancers in 2005 to obtain national time costs for the initial phase of care., Results: Net patient time costs during the initial phase of care ranged from 271 dollars (95% confidence interval [CI] = 213 dollars to 329 dollars) and 842 dollars (95% CI = 806 dollars to 878 dollars) for melanoma of the skin and prostate cancer, respectively, to 5348 dollars (95% CI = 4978 dollars to 5718 dollars) and 5605 dollars (95% CI = 5273 dollars to 5937 dollars) for gastric and ovarian cancers, respectively. Net patient time costs for care during the last year of life ranged from 1509 dollars (95% CI = 1343 dollars to 1675 dollars) for melanoma of the skin to 7799 dollars (95% CI = 7433 dollars to 8165 dollars), 7435 dollars (95% CI = 7207 dollars to 7663 dollars), and 7388 dollars (95% CI = 7018 dollars to 7758 dollars) for gastric, lung, and ovarian cancers, respectively. In 2005, patient time costs for the initial phase of care were 2.3 billion dollars., Conclusions: Patient time costs for cancer care in the United States are substantial and vary by tumor site and phase of care, likely reflecting differences in stage at diagnosis and availability and intensity of treatment.

Background: Strong associations between provider (i.e., hospital or surgeon) procedure volumes and patient outcomes have been demonstrated for many types of cancer operation. We performed a population-based cohort study to examine these associations for ovarian cancer resections., Methods: We used the Surveillance, Epidemiology, and End Results (SEER)-Medicare linked database to identify 2952 patients aged 65 years or older who had surgery for a primary ovarian cancer diagnosed from 1992 through 1999. Hospital- and surgeon-specific procedure volumes were ascertained based on the number of claims submitted during the 8-year study period. Primary outcome measures were mortality at 60 days and 2 years after surgery, and overall survival. Length of hospital stay was also examined. Patient age at diagnosis, race, marital status, comorbid illness, cancer stage, and median income and population density in the area of residence were used to adjust for differences in case mix. All P values are two-sided., Results: Neither hospital- nor surgeon-specific procedure volume was statistically significantly associated with 60-day mortality following primary ovarian cancer resection. However, differences by hospital volume were seen with 2-year mortality; patients treated at the low-, intermediate-, and high-volume hospitals had 2-year mortality rates of 45.2% (95% confidence interval [CI] = 42.1% to 48.4%), 41.1% (95% CI = 38.1% to 44.3%), and 40.4% (95% CI = 37.4% to 43.4%), respectively. The inverse association between hospital procedure volume and 2-year mortality was statistically significant both before (P = .011) and after (P = .006) case-mix adjustment but not after adjustment for surgeon volume. Two-year mortality for patients treated by low-, intermediate-, and high-volume surgeons was 43.2% (95% CI = 40.7% to 45.8%), 42.9% (95% CI = 39.5% to 46.4%), and 39.5% (95% CI = 36.0% to 43.2%), respectively; there was no association between 2-year mortality and surgeon procedure volume, with or without case-mix adjustment. After case-mix adjustment, neither hospital volume (P = .031) nor surgeon volume (P = .062) was strongly associated with overall survival., Conclusion: Hospital- and surgeon-specific procedure volumes are not strong predictors of survival outcomes following surgery for ovarian cancer among women aged 65 years or older.