Clinical factors associated with patterns of endocrine therapy adherence in premenopausal breast cancer patients.

INTRODUCTION: Patients with hormone receptor positive breast cancer are recommended at least five years of adjuvant endocrine therapy, but adherence to this treatment is often suboptimal. We investigated longitudinal trends in adjuvant endocrine therapy (AET) adherence among premenopausal breast cancer patients and identified clinical characteristics, including baseline comorbidities and non-cancer chronic medication use, associated with AET adherence. METHODS: We included stage I-III premenopausal breast cancer patients diagnosed during 2002-2011 and registered in the Danish Breast Cancer Group clinical database who initiated AET. We used group-based trajectory modeling to describe AET adherence patterns. We also linked patients to Danish population-based registries and fit multinomial logistic models to compute odds ratios (ORs) and 95% confidence intervals (95% CIs) associating clinical characteristics with AET adherence patterns. RESULTS: We identified three adherence patterns among 4,353 women-high adherers (57%), slow decliners (36%), and rapid decliners (6.9%). Women with stage I disease (vs. stage II; OR: 1.9, 95% CI 1.5, 2.5), without chemotherapy (vs. chemotherapy; OR: 4.3, 95% CI 3.0, 6.1), with prevalent comorbid disease (Charlson Comorbidity Index score ≥ 1 vs. 0; OR: 1.6, 95% CI 1.1, 2.3), and with a history of chronic non-cancer medication use (vs. none; OR: 1.3, 95% CI 1.0, 1.8) were more likely to be rapid decliners compared with high adherers. CONCLUSIONS: Women with stage I cancer, no chemotherapy, higher comorbidity burden, and history of chronic non-cancer medication use were less likely to adhere to AET. Taking steps to promote adherence in these groups of women may reduce their risk of recurrence.

Influence of Incomplete Death Information on Cumulative Risk Estimates in United States Claims Data.

Administrative claims databases often do not capture date or fact of death, so studies using these data may inappropriately treat death as a censoring event-equivalent to other withdrawal reasons-rather than a competing event. We examined 1-, 3-, and 5-year inverse-probability-of-treatment-weighted cumulative risks of a composite cardiovascular outcome among 34,527 initiators of telmisartan (exposure) and ramipril (referent) ages ≥55 in Optum claims from 2003 to 2020. Differences in cumulative risks of the cardiovascular endpoint due to censoring of death (cause-specific), as compared to treating death as a competing event (sub-distribution), increased with greater follow-up time and older age, where event and mortality risks were higher. Among ramipril users (selected results), 5-year cause-specific and sub-distribution cumulative risk estimates per 100, respectively, were 16.4 (95% CI 15.3, 17.5) and 16.2 (95% CI 15.1, 17.3) among ages 55-64 (difference=0.2) and were 43.2 (95% CI 41.3, 45.2) and 39.7 (95% CI 37.9, 41.4) among ages ≥75 (difference=3.6). Plasmode simulation results demonstrated the differences in cause-specific versus sub-distribution cumulative risks to increase with increasing mortality rate. We suggest researchers consider the cohort's baseline mortality risk when deciding whether real-world data with incomplete death information can be used without concern.

Biomarkers predictive of a response to extended endocrine therapy in breast cancer: a systematic review and meta-analysis.

PURPOSE: Extension of adjuvant endocrine therapy beyond five years confers only modest survival benefit in breast cancer patients and carries risk of toxicities. This systematic review investigates the role of biomarker tests in predicting the clinical response to an extension of endocrine therapy. METHODS: We searched Ovid MEDLINE, Ovid Embase, Global Index Medicus, and the Cochrane Central Register of Controlled Trials using an iterative approach to identify full-text articles related to breast cancer, endocrine therapy, and biomarkers. RESULTS: Of the 1,217 unique reports identified, five studies were deemed eligible. Four investigated the Breast Cancer Index (BCI) assay in three distinct study populations. These studies consistently showed that BCI score was predictive of response to extended endocrine therapy among 1,946 combined patients, who were predominately non-Hispanic white and postmenopausal. CONCLUSIONS: Evidence in the setting of predictive tests for extended endocrine therapy is sparse. Most relevant studies investigated the use of BCI, but these study populations were largely restricted to a single age, race, and ethnicity group. Future studies should evaluate a variety of biomarkers in diverse populations. Without sufficient evidence, physicians and patients face a difficult decision in balancing the benefits and risks of endocrine therapy extension.

The Population-level Effect of Adjuvant Therapies on Breast Cancer Recurrence: Application of the Trend-in-Trend Design.

PURPOSE: Breast cancer has an average 10-year relative survival reaching 84%. This favorable survival is due, in part, to the introduction of biomarker-guided therapies. We estimated the population-level effect of the introduction of two adjuvant therapies-tamoxifen and trastuzumab-on recurrence using the trend-in-trend pharmacoepidemiologic study design. METHODS: We ascertained data on women diagnosed with nonmetastatic breast cancer who were registered in the Danish Breast Cancer Group clinical database. We used the trend-in-trend design to estimate the population-level effect of the introduction of (1) tamoxifen for postmenopausal women with estrogen receptor (ER)-positive breast cancer in 1982, (2) tamoxifen for premenopausal women diagnosed with ER-positive breast cancer in 1999, and (3) trastuzumab for women <60 years diagnosed with human epidermal growth factor receptor 2-positive breast cancer in 2007. RESULTS: For the population-level effect of the introduction of tamoxifen among premenopausal women diagnosed with ER-positive breast cancer in 1999, the risk of recurrence decreased by nearly one-half (OR = 0.52), consistent with evidence from clinical trials; however, the estimate was imprecise (95% confidence interval [CI] = 0.25, 1.85). We observed an imprecise association between tamoxifen use and recurrence from the time it was introduced in 1982 (OR = 1.24 95% CI = 0.46, 5.11), inconsistent with prior knowledge from clinical trials. For the introduction of trastuzumab in 2007, the estimate was also consistent with trial evidence, though imprecise (OR = 0.51; 95% CI = 0.21, 22.4). CONCLUSIONS: We demonstrated how novel pharmacoepidemiologic analytic designs can be used to evaluate the routine clinical care and effectiveness of therapeutic advancements in a population-based setting while considering some limitations of the approach.

Real-World Risk of Severe Cytopenias in Multiple Myeloma Patients Sequentially Treated with Immunomodulatory Drugs.

INTRODUCTION: Most multiple myeloma (MM) patients experience cytopenias, likely driven by both disease and treatment-related factors. Immunomodulatory agents (IMiDs), which form the backbone of most anti-myeloma regimens, are known to cause higher grade cytopenias. In this context, the impact of sequential IMiD treatments on cytopenia risk is unknown. METHODS: We evaluated the cumulative risks of severe cytopenias following second line of therapy (LOT) initiation in 5,573 MM patients in the Flatiron Health database. Patients for whom both LOTs 1 and 2 contained IMiDs were considered "sequentially exposed"; those for whom neither contained IMiDs were "never exposed." RESULTS: For the neutropenia outcome, compared to the never exposed, the sequentially exposed had the highest 1-year risk (risk difference [RD] 12%), followed by those only recently exposed during LOT 2 (RD 8%), then by those with only past exposure during LOT 1 (RD 5%). A similar pattern was observed for leukopenia, but no meaningful differences were observed for anemia or thrombocytopenia. The associations between sequential exposure, versus never, with neutropenia and leukopenia were even stronger among those with a recent cytopenia history. CONCLUSION: Results suggest that sequential exposure to IMiDs is a risk factor for higher grade cytopenias. These findings have profound clinical implications in choosing newer LOTs with potential risks of cytopenia.

Use of quantitative bias analysis to evaluate single-arm trials with real-world data external controls.

PURPOSE: Use of real-world data (RWD) for external controls added to single-arm trials (SAT) is increasingly prevalent in regulatory submissions. Due to inherent differences in the data-generating mechanisms, biases can arise. This paper aims to illustrate how to use quantitative bias analysis (QBA). METHODS: Advanced non-small cell lung cancer (NSCLC) serves as an example, where many small subsets of patients with molecular tumor subtypes exist. First, some sources of bias that may occur in oncology when comparing RWD to SAT are described. Second, using a hypothetical immunotherapy agent, a dataset is simulated based on expert input for survival analysis of advanced NSCLC. Finally, we illustrate the impact of three biases: missing confounder, misclassification of exposure, and outcome evaluation. RESULTS: For each simulated scenario, bias was induced by removing or adding data; hazard ratios (HRs) were estimated applying conventional analyses. Estimating the bias-adjusted treatment effect and uncertainty required carefully selecting the bias model and bias factors. Although the magnitude of each biased and bias-adjusted HR appeared moderate in all three hypothetical scenarios, the direction of bias was variable. CONCLUSION: These findings suggest that QBA can provide an intuitive framework for bias analysis, providing a key means of challenging assumptions about the evidence. However, the accuracy of bias analysis is itself dependent on correct specification of the bias model and bias factors. Ultimately, study design should reduce bias, but QBA allows us to evaluate the impact of unavoidable bias to assess the quality of the evidence.

Staging and clean room: Constructs designed to facilitate transparency and reduce bias in comparative analyses of real-world data.

PURPOSE: We describe constructs designed to protect the integrity of the results from comparative analyses using real-world data (RWD): staging and clean room. METHODS: Staging involves performing sequential preliminary analyses and evaluating the population size available and potential bias before conducting comparative analyses. A clean room involves restricted access to data and preliminary results, policies governing exploratory analyses and protocol deviations, and audit trail. These constructs are intended to allow decisions about protocol deviations, such as changes to design or model specification, to be made without knowledge of how they might affect subsequent analyses. We describe an example for implementing staging with a clean room. RESULTS: Stage 1 may involve selecting a data source, developing and registering a protocol, establishing a clean room, and applying inclusion/exclusion criteria. Stage 2 may involve attempting to achieve covariate balance, often through propensity score models. Stage 3 may involve evaluating the presence of residual confounding using negative control outcomes. After each stage, check points may be implemented when a team of statisticians, epidemiologists and clinicians masked to how their decisions may affect study outcomes, reviews the results. This review team may be tasked with making recommendations for protocol deviations to address study precision or bias. They may recommend proceeding to the next stage, conducting additional analyses to address bias, or terminating the study. Stage 4 may involve conducting the comparative analyses. CONCLUSIONS: The staging and clean room constructs are intended to protect the integrity and enhance confidence in the results of analyses of RWD.

Monovalent Rotavirus Vaccine Efficacy Against Different Rotavirus Genotypes: A Pooled Analysis of Phase II and III Trial Data.

BACKGROUND: Rotavirus vaccine performance appears worse in countries with high rotavirus genotype diversity. Evidence suggests diminished vaccine efficacy (VE) against G2P[4], which is heterotypic with existing monovalent rotavirus vaccine formulations. Most studies assessing genotype-specific VE have been underpowered and inconclusive. METHODS: We pooled individual-level data from 10 Phase II and III clinical trials of rotavirus vaccine containing G1 and P[8] antigens (RV1) conducted between 2000 and 2012. We estimated VE against both any-severity and severe (Vesikari score ≥11) rotavirus gastroenteritis (RVGE) using binomial and multinomial logistic regression models for non-specific VE against any RVGE, genotype-specific VE, and RV1-typic VE against genotypes homotypic, partially heterotypic, or fully heterotypic with RV1 antigens. We adjusted models for concomitant oral poliovirus and RV1 vaccination and the country's designated child mortality stratum. RESULTS: Analysis included 87 644 infants from 22 countries in the Americas, Europe, Africa, and Asia. For VE against severe RVGE, non-specific VE was 91% (95% confidence interval [CI]: 87-94%). Genotype-specific VE ranged from 96% (95% CI: 89-98%) against G1P[8] to 71% (43-85%) against G2P[4]. RV1-typic VE was 92% (95% CI: 84-96%) against partially heterotypic genotypes but 83% (67-91%) against fully heterotypic genotypes. For VE against any-severity RVGE, non-specific VE was 82% (95% CI: 75-87%). Genotype-specific VE ranged from 94% (95% CI: 86-97%) against G1P[8] to 63% (41-77%) against G2P[4]. RV1-typic VE was 83% (95% CI: 72-90%) against partially heterotypic genotypes but 63% (40-77%) against fully heterotypic genotypes. CONCLUSIONS: RV1 VE is comparatively diminished against fully heterotypic genotypes including G2P[4].

Effect of a FIT-Based Colorectal Cancer Screening Program on Mortality Estimated by the Regression Discontinuity Design.

The fecal immunochemical test (FIT) has been implemented in colorectal cancer (CRC) screening programs, but effect evaluations are lacking. We evaluated the effect of a positive FIT on all-cause and CRC mortality using the regression discontinuity design. The Danish CRC screening program invites all residents 50-74 years old, using a 20-µg hemoglobin/g feces cutoff for colonoscopy referral. In this cohort study, we followed all first-time screening participants from 2014-2019 until 2020. We estimated the local effect of screening results, of just above the cutoff vs. just below, as hazard ratios (HRs) between models fitted at each side of the cutoff. We conducted the analysis within a narrow hemoglobin range (≥17 and <23, n = 16,428) and a wider range (≥14 and <26, n = 35,353). Those screened just above the cutoff had lower all-cause mortality compared with below (HR = 0.87, 95% confidence interval: 0.69; 1.10), estimated from the narrow range. The CRC mortality analysis had few outcomes. In the wider range, those with a FIT just above the cutoff had a lower hazard of CRC mortality compared with just below the cutoff (HR = 0.49, 95% confidence interval: 0.17; 1.41). A FIT result just above the cutoff, leading to referral to colonoscopy, pointed towards reduced all-cause and CRC mortality compared with just below the cutoff.

Prediction of Suicide Attempts Among Persons with Depression: A Population-Based Case Cohort Study.

Studies have highlighted the potential importance of modeling interactions for suicide attempt prediction. This case-cohort study identified risk factors for suicide attempts among persons with depression in Denmark using statistical approaches that do (random forests) or do not model interactions (least absolute shrinkage and selection operator regression [LASSO]). Cases made a non-fatal suicide attempt (n = 6,032) between 1995 and 2015. The comparison subcohort was a 5% random sample of all persons in Denmark on January 1, 1995 (n = 11,963). We used random forests and LASSO for sex-stratified prediction of suicide attempts from demographic variables, psychiatric and somatic diagnoses, and treatments. Poisonings, psychiatric disorders, and medications were important predictors for both sexes. Area under the receiver operating characteristic curve (AUC) values were higher in LASSO models (0.85 [95% CI = 0.84, 0.86] in men; 0.89 [95% CI = 0.88, 0.90] in women) than random forests (0.76 [95% CI = 0.74, 0.78] in men; 0.79 [95% CI = 0.78, 0.81] in women). Automatic detection of interactions via random forests did not result in better model performance than LASSO models that did not model interactions. Due to the complex nature of psychiatric comorbidity and suicide, modeling interactions may not always be the optimal statistical approach to enhancing suicide attempt prediction in high-risk samples.

Longitudinal weight status and academic achievement in elementary schoolchildren in the United States.

BACKGROUND/OBJECTIVES: Childhood overweight and obesity have a well-established negative impact on children's health. Overweight and obesity might also negatively impact children's academic performance, but existing literature on this association is inconclusive. This study uses a longitudinal design in a large, diverse elementary school sample to rigorously test the association between longitudinal weight status and academic achievement. Analyses also investigate modification by sex, race/ethnicity, and cardiorespiratory fitness (CRF). SUBJECTS/METHODS: In a large suburban school district in the United States, 4936 Grade 4 students were recruited. Demographic, course grade, and standardized test data were collected from school records for Grades 3-5, and body mass index and CRF were assessed each year. Students wore accelerometers during the school day for up to 15 days across three semesters (Grade 4 Fall and Spring, Grade 5 Fall) to objectively measure physical activity. Multiple imputation addressed missing data and multilevel analyses controlled for student demographics and clustering within schools. RESULTS: Unadjusted multilevel models found small negative associations between persistent obesity and course grades and standardized test scores, but these associations largely disappeared when controlling for demographic characteristics. Residual associations for math and writing course grades were attenuated when controlling for CRF, though some marginal negative associations for math and writing remained for students who developed obesity during follow-up. There was also evidence of marginal negative associations with course grades for students who developed overweight/obesity. There was no evidence of modification by sex or race/ethnicity. CONCLUSIONS: Results suggest very small associations between weight status and academic achievement that were largely explained by sociodemographic factors and CRF. Evidence of an association between weight status and achievement was stronger among students who developed overweight/obesity. Interventions promoting healthy weight and high CRF remain critical for schools given the link between student health and achievement.

Census Tracts Are Not Neighborhoods: Addressing Spatial Misalignment in Studies Examining the Impact of Historical Redlining on Present-day Health Outcomes.

BACKGROUND: Research examining the effects of historical redlining on present-day health outcomes is often complicated by the misalignment of contemporary census boundaries with the neighborhood boundaries drawn by the US Home Owners' Loan Corporation (HOLC) in the 1930s. Previous studies have used different approaches to assign historical HOLC grades to contemporary geographies, but how well they capture redlining exposure is unknown. METHODS: Our analysis included 7711 residences identified in the Multiple Listing Service database in Atlanta, Georgia (2017-2022). We evaluated the classification of HOLC grade assignment (A, B, C, D, or ungraded) when assigning exposure under four area-level approaches (centroid, majority land area, weighted score, and highest HOLC) compared with using complete address data (gold standard). We additionally compared approaches across three 2020 census geographies (tract, block group, and block). RESULTS: When comparing the use of census tracts to complete address data, sensitivity was highest for the weighted score approach, which correctly identified 77% of residences in truly A-D graded neighborhoods as compared with the majority land area (44%), centroid (54%), and highest HOLC (59%) approaches. Regarding specificity, the majority land area approach best-classified residences in truly ungraded neighborhoods (93%) as compared with the weighted score (65%), centroid (81%), and highest HOLC (54%) approaches. Classification improved regardless of approach when using census block compared with the census tract. CONCLUSIONS: Misclassification of historical redlining exposure is inevitable when using contemporary census geographies rather than complete address data. This study provides a framework for assessing spatial misalignment and selecting an approach for classification.

Tailoring capture-recapture methods to estimate registry-based case counts based on error-prone diagnostic signals.

Surveillance research is of great importance for effective and efficient epidemiological monitoring of case counts and disease prevalence. Taking specific motivation from ongoing efforts to identify recurrent cases based on the Georgia Cancer Registry, we extend recently proposed "anchor stream" sampling design and estimation methodology. Our approach offers a more efficient and defensible alternative to traditional capture-recapture (CRC) methods by leveraging a relatively small random sample of participants whose recurrence status is obtained through a principled application of medical records abstraction. This sample is combined with one or more existing signaling data streams, which may yield data based on arbitrarily non-representative subsets of the full registry population. The key extension developed here accounts for the common problem of false positive or negative diagnostic signals from the existing data stream(s). In particular, we show that the design only requires documentation of positive signals in these non-anchor surveillance streams, and permits valid estimation of the true case count based on an estimable positive predictive value (PPV) parameter. We borrow ideas from the multiple imputation paradigm to provide accompanying standard errors, and develop an adapted Bayesian credible interval approach that yields favorable frequentist coverage properties. We demonstrate the benefits of the proposed methods through simulation studies, and provide a data example targeting estimation of the breast cancer recurrence case count among Metro Atlanta area patients from the Georgia Cancer Registry-based Cancer Recurrence Information and Surveillance Program (CRISP) database.

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.

Impact of hemoglobin A1c level on the association between non-steroidal anti-inflammatory drug use and cardiovascular events in patients with type 2 diabetes: A population-based cohort study.

OBJECTIVE: Non-steroidal anti-inflammatory drugs (NSAIDs) should be used cautiously in patients with type 2 diabetes. We examined whether the cardiovascular risks associated with NSAID use depended on HbA1c level in patients with type 2 diabetes. METHODS: We conducted a population-based cohort study of all adult Danes with a first-time HbA1c measurement ≥48 mmol/mol during 2012-2020 (n = 103 308). We used information on sex, age, comorbidity burden, and drug use to calculate time-varying inverse probability of treatment weights. After applying these weights in a pooled logistic regression, we estimated hazard ratios (HRs) of the association between use of NSAIDs (ibuprofen, naproxen, or diclofenac) and cardiovascular events (a composite of myocardial infarction, ischemic stroke, congestive heart failure, atrial fibrillation or flutter, and all-cause death). We stratified all analyses by HbA1c level (<53 or ≥53 mmol/mol). RESULTS: For ibuprofen use, the HR of a cardiovascular event was 1.53 (95% confidence interval [CI]: 1.34-1.75) in patients with HbA1c <53 and 1.24 (95% CI: 1.00-1.53) in patients with HbA1c ≥53 mmol/mol. For naproxen use, the HR was 1.14 (95% CI: 0.59-2.21) in patients with HbA1c <53 and 1.30 (95% CI: 0.49-3.49) in patients with HbA1c ≥53 mmol/mol. For diclofenac use, the HR was 2.40 (95% CI: 1.62-3.56) in patients with HbA1c <53 and 2.89 (95% CI: 1.65-5.04) in patients with HbA1c ≥53 mmol/mol. CONCLUSIONS: In patients with type 2 diabetes, glycemic dysregulation did not affect the cardiovascular risk associated with NSAID use.

Pragmatic considerations for negative control outcome studies to guide non-randomized comparative analyses: A narrative review.

PURPOSE: This narrative review describes the application of negative control outcome (NCO) methods to assess potential bias due to unmeasured or mismeasured confounders in non-randomized comparisons of drug effectiveness and safety. An NCO is assumed to have no causal relationship with a treatment under study while subject to the same confounding structure as the treatment and outcome of interest; an association between treatment and NCO then reflects the potential for uncontrolled confounding between treatment and outcome. METHODS: We focus on two recently completed NCO studies that assessed the comparability of outcome risk for patients initiating different osteoporosis medications and lipid-lowering therapies, illustrating several ways in which confounding may result. In these studies, NCO methods were implemented in claims-based data sources, with the results used to guide the decision to proceed with comparative effectiveness or safety analyses. RESULTS: Based on this research, we provide recommendations for future NCO studies, including considerations for the identification of confounding mechanisms in the target patient population, the selection of NCOs expected to satisfy required assumptions, the interpretation of NCO effect estimates, and the mitigation of uncontrolled confounding detected in NCO analyses. We propose the use of NCO studies prior to initiating comparative effectiveness or safety research, providing information on the potential presence of uncontrolled confounding in those comparative analyses. CONCLUSIONS: Given the increasing use of non-randomized designs for regulatory decision-making, the application of NCO methods will strengthen study design, analysis, and interpretation of real-world data and the credibility of the resulting real-world evidence.

Risk of psychopathology following traumatic events among immigrants and native-born persons in Denmark.

PURPOSE: Immigrants may have increased risk of mental disorders compared with native-born persons. We aimed to expand the limited research on immigrants' posttraumatic psychopathology related to traumatic experiences in their country of resettlement. METHODS: We obtained data from a cohort of Danish residents with ≥ 1 traumatic event recorded in health and administrative national registries during 1994-2016. We calculated risks of posttraumatic stress disorder (PTSD), depression, and substance use disorders (SUD) within 5 years post-trauma among native-born Danes and immigrants who had been in Denmark for ≥ 10 years at the time of their index trauma (including immigrants overall and immigrants from specific regions). Risks were compared via age- and sex-standardized risk ratios (SRR) with 95% confidence intervals (CI). We restricted to persons with no record of the disorder under investigation in the 10 years pre-trauma, and stratified by non-interpersonal (e.g., transport accidents) versus interpersonal trauma (e.g., assaults). RESULTS: Following non-interpersonal trauma, immigrants were more likely than native-born Danes to be diagnosed with PTSD (SRR = 5.2, 95% CI 4.6, 5.9), about as likely to be diagnosed with depression (SRR = 0.98, 95% CI 0.92, 1.1), and less likely to be diagnosed with SUD (SRR = 0.89, 95% CI 0.82, 0.95). Results were similar following interpersonal trauma, except the SRR for PTSD was reduced in magnitude (SRR = 3.0, 95% CI 1.7, 5.4). There were differences by region of birth. CONCLUSION: Immigrants to Denmark have higher risk of PTSD following traumatic experiences than do native-born Danes, possibly due to the combined influence of adverse pre-, peri-, and/or post-migration experiences.

Fever of Unknown Origin and Incidence of Cancer.

BACKGROUND: Diagnostic tools for determining causes of fever of unknown origin (FUO) have improved over time. We examined if cancer incidence among these patients changed over a 20-year period. METHODS: Population-based cohort study using nationwide Danish registries. We identified individuals diagnosed with FUO (1998-2017) to quantify their excess risk of cancer compared with the general population. Follow-up for cancer started 1 month after FUO. We computed absolute risks and standardized incidence ratios (SIRs) of cancer, and mortality rate ratios adjusted for age, sex, and cancer stage. RESULTS: Among 6620 patients with FUO (46.9% male; median age: 39 years), 343 were diagnosed with cancer (median follow-up: 6.5 years). The 1- to <12-month risk was 1.2%, and the SIR was 2.3 (95% CI, 1.8-2.9). The increased 1- to <12-month SIR was mainly due to an excess of Hodgkin lymphoma (SIR = 41.7) non-Hodgkin lymphoma (SIR = 16.1), myelodysplastic syndrome/chronic myeloproliferative diseases (SIR = 6.0), lower gastrointestinal cancer (SIR = 3.3), and urinary tract cancer (SIR = 2.9). Beyond 1-year follow-up, malignant melanoma, hepatobiliary tract/pancreatic cancer, and brain/CNS/eye cancer were diagnosed more often than expected. The 1- to <12-month cancer SIR attenuated over time, and for the 2013-2017 period we found no excess risk. Patients diagnosed with cancer ≤1 year after FUO had similar mortality to cancer patients without this diagnosis. CONCLUSIONS: Patients with FUO have a higher 1- <12-month cancer SIR; thereafter, the incidence for most cancers equals that of the general population. Decreasing SIRs over time suggests improvements in the initial diagnostic workup for FUO.

Misconceptions About the Direction of Bias From Nondifferential Misclassification.

Measurement error is pervasive in epidemiologic research. Epidemiologists often assume that mismeasurement of study variables is nondifferential with respect to other analytical variables and then rely on the heuristic that "nondifferential misclassification will bias estimates towards the null." However, there are many exceptions to the heuristic for which bias towards the null cannot be assumed. In this paper, we compile and characterize 7 exceptions to this rule and encourage analysts to take a more critical and nuanced approach to evaluating and discussing bias from nondifferential mismeasurement.

Sampling Validation Data to Achieve a Planned Precision of the Bias-Adjusted Estimate of Effect.

Data collected from a validation substudy permit calculation of a bias-adjusted estimate of effect that is expected to equal the estimate that would have been observed had the gold standard measurement been available for the entire study population. In this paper, we develop and apply a framework for adaptive validation to determine when sufficient validation data have been collected to yield a bias-adjusted effect estimate with a prespecified level of precision. Prespecified levels of precision are decided a priori by the investigator, based on the precision of the conventional estimate and allowing for wider confidence intervals that would still be substantively meaningful. We further present an applied example of the use of this method to address exposure misclassification in a study of transmasculine/transfeminine youth and self-harm. Our method provides a novel approach to effective and efficient estimation of classification parameters as validation data accrue, with emphasis on the precision of the bias-adjusted estimate. This method can be applied within the context of any parent epidemiologic study design in which validation data will be collected and modified to meet alternative criteria given specific study or validation study objectives.