Characterizing Fit-for-Purpose Real-World Data: An Assessment of a Mother-Infant Linkage in the Japan Medical Data Center Claims Database.

Purpose: Observational postapproval safety studies are needed to inform medication safety during pregnancy. Real-world databases can be valuable for supporting such research, but fitness for regulatory purpose must first be vetted. Here, we demonstrate a fit-for-purpose assessment of the Japan Medical Data Center (JMDC) claims database for pregnancy safety regulatory decision-making. Patients and Methods: The Duke-Margolis framework considers a database's fitness for regulatory purpose based on relevancy (capacity to answer the research question based on variable availability and a sufficiently sized, representative population) and quality (ability to validly answer the research question based on data completeness and accuracy). To assess these considerations, we examined descriptive characteristics of infants and pregnancies among females ages 12-55 years in the JMDC between January 2005 and March 2022. Results: For relevancy, we determined that critical data fields (maternal medications, infant major congenital malformations, covariates) are available. Family identification codes permitted linkage of 385,295 total mother-infant pairs, 57% of which were continuously enrolled during pregnancy. The prevalence of specific congenital malformation subcategories and maternal medical conditions were representative of the general population, but preterm births were below expectations (3.6% versus 5.6%) in this population. For quality, our methods are expected to accurately identify the complete set of mothers and infants with a shared health insurance plan. However, validity of gestational age information was limited given the high proportion (60%) of missing live birth delivery codes coupled with suppression of infant birth dates and inaccessibility of disease codes with gestational week information. Conclusion: The JMDC may be well suited for descriptive studies of pregnant people in Japan (eg, comorbidities, medication usage). More work is needed to identify a method to assign pregnancy onset and delivery dates so that in utero medication exposure windows can be defined more precisely as needed for many regulatory postapproval pregnancy safety studies.

Impact of lifestyle and socioeconomic position on use of non-steroidal anti-inflammatory drugs: A population-based cohort study.

PURPOSE: Lifestyle and socioeconomic position may confound the link between non-steroidal anti-inflammatory drugs (NSAIDs) and cardiovascular events, if associated with NSAID use. We examined this association. METHODS: We conducted a cohort study of all adult first-time responders to the Danish National Health Surveys of 2010, 2013, or 2017 without an NSAID prescription within 3 months before survey completion (n = 407 395). Study exposures were weight, smoking status, alcohol consumption, binge drinking frequency, physical activity level, marital status, highest achieved level of education, income, and employment status. We used a Cox model to compute hazard ratios of time to first redemption of an NSAID prescription and a cumulative odds model to compute odds ratios (ORs) of redeeming one additional NSAID prescription in the year after survey completion. RESULTS: Total follow-up time was 1 931 902 years. The odds of redeeming one additional NSAID prescription in the year after survey completion varied within all categories of lifestyle and socioeconomic position. The largest ORs were observed within categories of weight (1.70, 95% CI: 1.65-1.74 for obesity vs. normal weight), smoking status (1.24, 95% CI: 1.21-1.27 for current vs. never use), and education (1.44, 95% CI: 1.39-1.49 for primary or other vs. university or higher education). The Cox model showed consistent results. CONCLUSIONS: Markers of unhealthy lifestyle and low socioeconomic position were associated with initiation and prolonged NSAID use. Consideration of lifestyle and socioeconomic markers as potential confounders in NSAID studies is therefore recommended.

Estimating the Unknown: Greater Racial and Ethnic Disparities in COVID-19 Burden After Accounting for Missing Race and Ethnicity Data.

BACKGROUND: Black, Hispanic, and Indigenous persons in the United States have an increased risk of SARS-CoV-2 infection and death from COVID-19, due to persistent social inequities. However, the magnitude of the disparity is unclear because race/ethnicity information is often missing in surveillance data. METHODS: We quantified the burden of SARS-CoV-2 notification, hospitalization, and case fatality rates in an urban county by racial/ethnic group using combined race/ethnicity imputation and quantitative bias analysis for misclassification. RESULTS: The ratio of the absolute racial/ethnic disparity in notification rates after bias adjustment, compared with the complete case analysis, increased 1.3-fold for persons classified Black and 1.6-fold for those classified Hispanic, in reference to classified White persons. CONCLUSIONS: These results highlight that complete case analyses may underestimate absolute disparities in notification rates. Complete reporting of race/ethnicity information is necessary for health equity. When data are missing, quantitative bias analysis methods may improve estimates of racial/ethnic disparities in the COVID-19 burden.

Measuring the missing: greater racial and ethnic disparities in COVID-19 burden after accounting for missing race/ethnicity data.

Black, Hispanic, and Indigenous persons in the United States have an increased risk of SARS-CoV-2 infection and death from COVID-19, due to persistent social inequities. The magnitude of the disparity is unclear, however, because race/ethnicity information is often missing in surveillance data. In this study, we quantified the burden of SARS-CoV-2 infection, hospitalization, and case fatality rates in an urban county by racial/ethnic group using combined race/ethnicity imputation and quantitative bias-adjustment for misclassification. After bias-adjustment, the magnitude of the absolute racial/ethnic disparity, measured as the difference in infection rates between classified Black and Hispanic persons compared to classified White persons, increased 1.3-fold and 1.6-fold respectively. These results highlight that complete case analyses may underestimate absolute disparities in infection rates. Collecting race/ethnicity information at time of testing is optimal. However, when data are missing, combined imputation and bias-adjustment improves estimates of the racial/ethnic disparities in the COVID-19 burden.

Quantitative bias analysis for study and grant planning.

PURPOSE: Epidemiologists often think about the balance between study error and cost-efficiency in terms of study design and strategies to reduce random error. We less often consider cost-efficiencies in terms of dealing with systematic errors that arise within a study, such as in deciding how to measure study variables and misclassification implications. METHODS: Given the information used to inform a study size calculation, the expected study data can be simulated during study planning, and the impact of anticipated biases can be estimated using quantitative bias analysis. This would allow investigators and stakeholders to identify areas where better data collection through more valid instruments is critical and where additional investment will not yield strong validity benefits. This could promote better use of study resources and help increase investigators' chances of funding by demonstrating they have thought through biases and have a plan for mitigating the impact. RESULTS: We demonstrate how this would work with a practical example using the relationship between smoking during pregnancy as measured on birth certificates and incident breast cancer. CONCLUSIONS: We show that although exposure sensitivity would likely be poor, spending more money to get a better smoking measure is unlikely to yield more valid estimates.

Perspectives on the Future of Epidemiology: A Framework for Training.

Over the past century, the field of epidemiology has evolved and adapted to changing public health needs. Challenges include newly emerging public health concerns across broad and diverse content areas, new methods, and vast data sources. We recognize the need to engage and educate the next generation of epidemiologists and prepare them to tackle these issues of the 21st century. In this commentary, we suggest a skeleton framework upon which departments of epidemiology should build their curriculum. We propose domains that include applied epidemiology, biological and social determinants of health, communication, creativity and ability to collaborate and lead, statistical methods, and study design. We believe all students should gain skills across these domains to tackle the challenges posed to us. The aim is to train smart thinkers, not technicians, to embrace challenges and move the expanding field of epidemiology forward.

Prediction of Sex-Specific Suicide Risk Using Machine Learning and Single-Payer Health Care Registry Data From Denmark.

Importance: Suicide is a public health problem, with multiple causes that are poorly understood. The increased focus on combining health care data with machine-learning approaches in psychiatry may help advance the understanding of suicide risk. Objective: To examine sex-specific risk profiles for death from suicide using machine-learning methods and data from the population of Denmark. Design, Setting, and Participants: A case-cohort study nested within 8 national Danish health and social registries was conducted from January 1, 1995, through December 31, 2015. The source population was all persons born or residing in Denmark as of January 1, 1995. Data were analyzed from November 5, 2018, through May 13, 2019. Exposures: Exposures included 1339 variables spanning domains of suicide risk factors. Main Outcomes and Measures: Death from suicide from the Danish cause of death registry. Results: A total of 14 103 individuals died by suicide between 1995 and 2015 (10 152 men [72.0%]; mean [SD] age, 43.5 [18.8] years and 3951 women [28.0%]; age, 47.6 [18.8] years). The comparison subcohort was a 5% random sample (n = 265 183) of living individuals in Denmark on January 1, 1995 (130 591 men [49.2%]; age, 37.4 [21.8] years and 134 592 women [50.8%]; age, 39.9 [23.4] years). With use of classification trees and random forests, sex-specific differences were noted in risk for suicide, with physical health more important to men's suicide risk than women's suicide risk. Psychiatric disorders and possibly associated medications were important to suicide risk, with specific results that may increase clarity in the literature. Generally, diagnoses and medications measured 48 months before suicide were more important indicators of suicide risk than when measured 6 months earlier. Individuals in the top 5% of predicted suicide risk appeared to account for 32.0% of all suicide cases in men and 53.4% of all cases in women. Conclusions and Relevance: Despite decades of research on suicide risk factors, understanding of suicide remains poor. In this study, the first to date to develop risk profiles for suicide based on data from a full population, apparent consistency with what is known about suicide risk was noted, as well as potentially important, understudied risk factors with evidence of unique suicide risk profiles among specific subpopulations.

Quality of Maternal Height and Weight Data from the Revised Birth Certificate and Pregnancy Risk Assessment Monitoring System.

BACKGROUND: The 2003 revision of the US Standard Certificate of Live Birth (birth certificate) and Pregnancy Risk Assessment Monitoring System (PRAMS) are important for maternal weight research and surveillance. We examined quality of prepregnancy body mass index (BMI), gestational weight gain, and component variables from these sources. METHODS: Data are from a PRAMS data quality improvement study among a subset of New York City and Vermont respondents in 2009. We calculated mean differences comparing prepregnancy BMI data from the birth certificate and PRAMS (n = 734), and gestational weight gain data from the birth certificate (n = 678) to the medical record, considered the gold standard. We compared BMI categories (underweight, normal weight, overweight, obese) and gestational weight gain categories (below, within, above recommendations), classified by different sources, using percent agreement and the simple κ statistic. RESULTS: For most maternal weight variables, mean differences between the birth certificate and PRAMS compared with the medical record were less than 1 kg. Compared with the medical record, the birth certificate classified similar proportions into prepregnancy BMI categories (agreement = 89%, κ = 0.83); PRAMS slightly underestimated overweight and obesity (agreement = 84%, κ = 0.73). Compared with the medical record, the birth certificate overestimated gestational weight gain below recommendations and underestimated weight gain within recommendations (agreement = 81%, κ = 0.69). Agreement varied by maternal and pregnancy-related characteristics. CONCLUSIONS: Classification of prepregnancy BMI and gestational weight gain from the birth certificate or PRAMS was mostly similar to the medical record but varied by maternal and pregnancy-related characteristics. Efforts to understand how misclassification influences epidemiologic associations are needed.

Cohort profile: Study of Transition, Outcomes and Gender (STRONG) to assess health status of transgender people.

PURPOSE: The Study of Transition, Outcomes and Gender (STRONG) was initiated to assess the health status of transgender people in general and following gender-affirming treatments at Kaiser Permanente health plans in Georgia, Northern California and Southern California. The objectives of this communication are to describe methods of cohort ascertainment and data collection and to characterise the study population. PARTICIPANTS: A stepwise methodology involving computerised searches of electronic medical records and free-text validation of eligibility and gender identity was used to identify a cohort of 6456 members with first evidence of transgender status (index date) between 2006 and 2014. The cohort included 3475 (54%) transfeminine (TF), 2892 (45%) transmasculine (TM) and 89 (1%) members whose natal sex and gender identity remained undetermined from the records. The cohort was matched to 127 608 enrollees with no transgender evidence (63 825 women and 63 783 men) on year of birth, race/ethnicity, study site and membership year of the index date. Cohort follow-up extends through the end of 2016. FINDINGS TO DATE: About 58% of TF and 52% of TM cohort members received hormonal therapy at Kaiser Permanente. Chest surgery was more common among TM participants (12% vs 0.3%). The proportions of transgender participants who underwent genital reconstruction surgeries were similar (4%-5%) in the two transgender groups. Results indicate that there are sufficient numbers of events in the TF and TM cohorts to further examine mental health status, cardiovascular events, diabetes, HIV and most common cancers. FUTURE PLANS: STRONG is well positioned to fill existing knowledge gaps through comparisons of transgender and reference populations and through analyses of health status before and after gender affirmation treatment. Analyses will include incidence of cardiovascular disease, mental health, HIV and diabetes, as well as changes in laboratory-based endpoints (eg, polycythemia and bone density), overall and in relation to gender affirmation therapy.

Longitudinal assessment of concurrent changes in left ventricular ejection fraction and left ventricular myocardial tissue characteristics after administration of cardiotoxic chemotherapies using T1-weighted and T2-weighted cardiovascular magnetic resonance.

BACKGROUND: In a murine anthracycline-related cardiotoxicity model, increases in cardiovascular magnetic resonance myocardial contrast-enhanced T1-weighted signal intensity are associated with myocellular injury and decreases with left ventricular ejection fraction. We sought to determine whether T1- and T2-weighted measures of signal intensity associate with decreases in left ventricular ejection fraction in human subjects receiving potentially cardiotoxic chemotherapy. METHODS AND RESULTS: In 65 individuals with breast cancer (n=51) or a hematologic malignancy (n=14), we measured left ventricular volumes, ejection fraction, and contrast-enhanced T1-weighted and T2-weighted signal intensity before and 3 months after initiating potentially cardiotoxic chemotherapy using blinded, unpaired analysis of cardiovascular magnetic resonance images. Participants were aged 51 ± 12 years, of whom 55% received an anthracycline, 38% received a monoclonal antibody, and 6% received an antimicrotubule agent. Overall, left ventricular ejection fraction decreased from 57 ± 6% to 54 ± 7% (P<0.001) because of an increase in end-systolic volume (P<0.05). T1-weighted signal intensities also increased from 14.1 ± 5.1 to 15.9 ± 6.8 (P<0.05), with baseline values trending higher among individuals who received chemotherapy before study enrollment (P=0.06). Changes in T1-weighted signal intensity did not differ within the 17 LV myocardial segments (P=0.97). Myocardial edema quantified from T2-weighted images did not change significantly after 3 months (P=0.70). CONCLUSIONS: Concordant with previous animal studies, cardiovascular magnetic resonance measures of contrast-enhanced T1-weighted signal intensity occur commensurate with small but significant left ventricular ejection fraction declines 3 months after the receipt of potentially cardiotoxic chemotherapy. These data indicate that changes in T1-weighted signal intensity may serve as an early marker of subclinical injury related to the administration of potentially cardiotoxic chemotherapy in human subjects.

Persistent geographical disparities in the use of primary percutaneous coronary intervention in 120 European regions: exploring the variation.

AIMS: Large inequalities in the use of primary percutaneous interventions (PPCI) for ST-elevation myocardial infarction (STEMI) are evident. In order to understand how we can help to implement best practice for STEMI patients, we investigated the variation in PPCI utilisation in 120 regions in 10 EU countries and the association with economic, organisational and demographic characteristics. METHODS AND RESULTS: We performed an ecological study using mixed effects regression models in the following 10 countries: Austria, Belgium, Denmark, England and Wales, Germany, Italy, Portugal, Spain, Sweden, and Northern Ireland. The main finding was the annual number of PPCI per million inhabitants from 2003 through 2008. Overall, the annual increase in PPCI utilisation was 1.15 (95% CI: 1.12, 1.19) per million per year. Regional-level rates varied from 0.74 (95% CI: 0.42, 1.30) to 1.90 (95 % CI: 1.01, 3.55) per million per year. At a regional level, significant positive associations with PPCI utilisation were the number of physicians per 100,000 inhabitants; the number of nurses and midwives per 100,000 inhabitants; and the proportion of the region's population aged 50 to <70 years. At a country level, significant positive associations with utilisation were the year of STEMI treatment, population density per km2; number of general hospital beds per 100,000 inhabitants; and the number of physicians per 100,000 inhabitants. CONCLUSIONS: Between 2003 and 2008, PPCI utilisation increased significantly in the ten European countries studied, but there was a great variation within country regions. Regional variation in PPCI rates were associated with both demographic and supply factors, revealing substantial opportunities to improve PPCI utilisation across Europe at national and regional levels.

Hospitalization with acute exacerbation of chronic obstructive pulmonary disease and associated health resource utilization: a population-based Danish cohort study.

OBJECTIVE: Health resource utilization (HRU) and outcomes associated with acute exacerbation of chronic obstructive pulmonary disease (AECOPD) are not well described. Therefore, a population-based cohort study was conducted to characterize patients hospitalized with AECOPD with regard to HRU, mortality, recurrence, and predictors of readmission with AECOPD. METHODS: Using Danish healthcare databases, this study identified COPD patients with at least one AECOPD hospitalization between 2005-2009 in Northern Denmark. Hospitalized AECOPD patients' HRU, in-hospital mortality, 30-day, 60-day, 90-day, and 180-day post-discharge mortality and recurrence risk, and predictors of readmission with AECOPD in the year following study inclusion were characterized. RESULTS: This study observed 6612 AECOPD hospitalizations among 3176 prevalent COPD patients. Among all AECOPD hospitalizations, median length of stay was 6 days (interquartile range [IQR] 3-9 days); 5 days (IQR 3-9) among those without ICU stay and 11 days (IQR 7-20) among the 8.6% admitted to the ICU. Mechanical ventilation was provided to 193 (2.9%) and non-invasive ventilation to 479 (7.2%) admitted patients. In-hospital mortality was 5.6%. Post-discharge mortality was 4.2%, 7.8%, 10.5%, and 17.4% at 30, 60, 90, and 180 days, respectively. Mortality and readmission risk increased with each AECOPD hospitalization experienced in the first year of follow-up. Readmission at least twice in the first year of follow-up was observed among 286 (9.0%) COPD patients and was related to increasing age, male gender, obesity, asthma, osteoporosis, depression, myocardial infarction, diabetes I and II, any malignancy, and hospitalization with AECOPD or COPD in the prior year. LIMITATIONS: The study included only hospitalized AECOPD patients among prevalent COPD patients. Furthermore, information was lacking on clinical variables. CONCLUSION: These findings indicate that AECOPD hospitalizations are associated with substantial mortality and risk of recurrence.

Correcting for exposure misclassification using survival analysis with a time-varying exposure.

PURPOSE: Survival analysis is increasingly being used in perinatal epidemiology to assess time-varying risk factors for various pregnancy outcomes. Here we show how quantitative correction for exposure misclassification can be applied to a Cox regression model with a time-varying dichotomous exposure. METHODS: We evaluated influenza vaccination during pregnancy in relation to preterm birth among 2267 non-malformed infants whose mothers were interviewed as part of the Slone Birth Defects Study during 2006 through 2011. The hazard of preterm birth was modeled using a time-varying exposure Cox regression model with gestational age as the time-scale. The effect of exposure misclassification was then modeled using a probabilistic bias analysis that incorporated vaccination date assignment. The parameters for the bias analysis were derived from both internal and external validation data. RESULTS: Correction for misclassification of prenatal influenza vaccination resulted in an adjusted hazard ratio (AHR) slightly higher and less precise than the conventional analysis: Bias-corrected AHR 1.04 (95% simulation interval, 0.70-1.52); conventional AHR, 1.00 (95% confidence interval, 0.71-1.41). CONCLUSIONS: Probabilistic bias analysis allows epidemiologists to assess quantitatively the possible confounder-adjusted effect of misclassification of a time-varying exposure, in contrast with a speculative approach to understanding information bias.

Use of penicillin and other antibiotics and risk of multiple sclerosis: a population-based case-control study.

A 2006 study from the United Kingdom found that penicillin use may decrease the risk of multiple sclerosis (MS). To confirm this finding, the authors conducted a nationwide case-control study in Denmark, using the Danish Multiple Sclerosis Registry to identify 3,259 patients with MS onset from 1996 to 2008, and selected 10 population controls per case (n = 32,590), matched on sex and age. Through the National Prescription Database, prescriptions for antibiotics redeemed from 1995 to 2008 and before the date of first MS symptom/index date were identified. Conditional logistic regression analysis was used to compute odds ratios associating antibiotic use with MS occurrence. In total, 1,922 patients (59%) redeemed penicillin prescriptions before the index date and 2,292 (70%) redeemed any type of antibiotic prescription. Penicillin use was associated with an increased risk of MS (odds ratio = 1.21, 95% confidence interval: 1.10, 1.27). Use of any type of antibiotic was similarly associated with an increased risk of MS (odds ratio = 1.41, 95% confidence interval: 1.29, 1.53). The odds ratios for different types of antibiotics ranged between 1.08 and 1.83. Thus, this study found that penicillin use and use of other antibiotics were similarly associated with increased risk of MS, suggesting that the underlying infections may be causally associated with MS.

CYP2D6 inhibition and breast cancer recurrence in a population-based study in Denmark.

BACKGROUND: Cytochrome P450 2D6 (CYP2D6) inhibition reduces the concentration of 4-hydroxylated tamoxifen metabolites, but the clinical relevance remains uncertain. METHODS: We conducted a large case-control study nested in the population of 11 251 women aged 35-69 years at diagnosis of stage I-III breast cancer between 1985 and 2001 on Denmark's Jutland Peninsula and registered with the Danish Breast Cancer Cooperative Group. We identified 541 recurrent or contralateral breast cancers among women with estrogen receptor-positive (ER+) disease treated with tamoxifen for at least 1 year and 300 cancers in women with ER-negative (ER-) disease never treated with tamoxifen. We matched one control subject per case patient on ER status, menopausal status, stage, calendar time, and county, genotyped the CYP2D6*4 allele to assess genetic inhibition, and ascertained prescription history to assess drug-drug inhibition. We estimated the odds ratio (OR), associating CYP2D6 inhibition with breast cancer recurrence and adjusted for potential confounding with logistic regression. To address bias from incomplete information on CYP2D6 function, we used Monte Carlo simulation to complete a record-level probabilistic bias analysis. All statistical tests were two-sided. RESULTS: The frequency of the CYP2D6*4 minor allele was 24% in case patients with ER+ tumors, 23% in case patients with ER- tumors, and 22% each in control subjects with ER+ and ER- tumors. In women with ER+ tumors, the associations of one functional allele with recurrence (OR = 0.99; 95% confidence interval = 0.76 to 1.3) and no functional allele with recurrence (OR = 1.4; 95% confidence interval = 0.84 to 2.3) were near null, as were those for women with ER- tumors. The near-null associations persisted when evaluated by intake of medications, by combining genotype with medication history, in the probabilistic bias analysis, or by restricting the analysis to women with ER expression confirmed by re-assay. CONCLUSION: The association between CYP2D6 inhibition and recurrence in tamoxifen-treated patients is likely null or small.

Under utilization of surveillance mammography among older breast cancer survivors.

BACKGROUND: Annual surveillance mammography is recommended for follow-up of women with a history of breast cancer. We examined surveillance mammography among breast cancer survivors who were enrolled in integrated healthcare systems. METHODS: Women in this study were 65 or older when diagnosed with early stage invasive breast cancer (N = 1,762). We assessed mammography use during 4 years of follow-up, using generalized estimating equations to account for repeated measurements. RESULTS: Eighty-two percent had mammograms during the first year after treatment; the percentage declined to 68.5% in the fourth year of follow-up. Controlling for age and comorbidity, women who were at higher risk of recurrence by being diagnosed at stage II or receiving breast-conserving surgery (BCS) without radiation therapy were less likely to have yearly mammograms (compared to stage I, odds ratio [OR] for stage IIA 0.72, confidence interval [CI] 0.59, 0.87, OR for stage IIB 0.75, CI 0.57, 1.0; compared to BCS with radiation, OR 0.58, CI 0.43, 0.77). Women with visits to a breast cancer surgeon or oncologist were more likely to receive mammograms (OR for breast cancer surgeon 6.0, CI 4.9, 7.4, OR for oncologist 7.4, CI 6.1, 9.0). CONCLUSIONS: Breast cancer survivors who are at greater risk of recurrence are less likely to receive surveillance mammograms. Women without a visit to an oncologist or breast cancer surgeon during a year have particularly low rates of mammography. Improvements to surveillance care for breast cancer survivors may require active participation by primary care physicians and improvements in cancer survivorship programs by healthcare systems.

Automated inter-rater reliability assessment and electronic data collection in a multi-center breast cancer study.

BACKGROUND: The choice between paper data collection methods and electronic data collection (EDC) methods has become a key question for clinical researchers. There remains a need to examine potential benefits, efficiencies, and innovations associated with an EDC system in a multi-center medical record review study. METHODS: A computer-based automated menu-driven system with 658 data fields was developed for a cohort study of women aged 65 years or older, diagnosed with invasive histologically confirmed primary breast cancer (N = 1859), at 6 Cancer Research Network sites. Medical record review with direct data entry into the EDC system was implemented. An inter-rater and intra-rater reliability (IRR) system was developed using a modified version of the EDC. RESULTS: Automation of EDC accelerated the flow of study information and resulted in an efficient data collection process. Data collection time was reduced by approximately four months compared to the project schedule and funded time available for manuscript preparation increased by 12 months. In addition, an innovative modified version of the EDC permitted an automated evaluation of inter-rater and intra-rater reliability across six data collection sites. CONCLUSION: Automated EDC is a powerful tool for research efficiency and innovation, especially when multiple data collection sites are involved.

Effectiveness of adjuvant tamoxifen therapy among older women with early stage breast cancer.

To investigate the effectiveness of adjuvant tamoxifen in older women with early-stage breast cancer. Between 1997 and 1999, women > or = 65 years old at diagnosis with stage I-IIIa breast cancer were recruited from four geographic regions of the United States and followed prospectively for 5 years after diagnosis. Data sources included tumor registries, medical records review, and telephone interviews. The primary end points were breast cancer-specific and overall survival ascertained by matching identifying data with the National Death Index and Social Security Administration master death file. Tamoxifen prescription was operationalized as tamoxifen prescribed by 6 months after diagnosis. Survival analysis was undertaken using Kaplan-Meier curves and Cox proportional hazards modeling. We studied 689 women whose average age was 74.2 years at diagnosis (SD = 6.3, range 65-96 years). The median follow-up was 67 months (range 3.5-88 months). Of the 689 patients, 519 (76%) were prescribed tamoxifen. The 5-year breast cancer-specific survival was 93% (95% CI = 90-95) and 89% (95% CI = 83-94) for the ever tamoxifen and never tamoxifen groups, respectively. The ratio of adjusted breast cancer mortality hazards was 0.61 (95% CI = 0.31-1.12) for the ever tamoxifen group versus the never tamoxifen group. Similarly, the 5-year overall survival was 81% (95% CI = 76-85) and 70% (95% CI = 61-78) for the ever tamoxifen and never tamoxifen groups, respectively, with an adjusted hazard ratio of 0.53 (95% CI = 0.37-0.77). Adjuvant tamoxifen is associated with improvement in 5-year breast cancer-specific and overall survival in older women with early-stage breast cancer.

Breast cancer treatment of older women in integrated health care settings.

PURPOSE: A substantial literature describes age-dependent variations in breast cancer treatment, showing that older women are less likely to receive standard treatment than younger women. We sought to identify patient and tumor characteristics associated with the nonreceipt of standard primary tumor and systemic adjuvant therapies. PATIENTS AND METHODS: We studied 1,859 women age 65 years or older with stage I and II breast cancer diagnosed between 1990 and 1994 who were cared for in six geographically dispersed community-based health care systems. We collected demographic, tumor, treatment, and comorbidity data from electronic data sources, including cancer registry, administrative, and clinical databases, and from subjects' medical records. RESULTS: Women 75 years of age or older and women with higher comorbidity indices were more likely to receive nonstandard primary tumor therapy, to not receive axillary lymph node dissection, and to not receive radiation therapy after breast-conserving surgery (BCS). Asian women were less likely to receive BCS, and African American women were less likely to be prescribed tamoxifen. Although nonreceipt of most therapies was associated with a lower baseline risk of recurrence, an important minority of high-risk women (16% to 30%) did not receive guideline therapies. CONCLUSION: Age is an independent risk factor for nonreceipt of effective cancer therapies, even when comorbidity and risk of recurrence are taken into account. Information regarding treatment effectiveness in this age group and tools that allow physicians and patients to estimate the benefits versus the risks of therapies, taking into account age and comorbidity burden, are critically needed.