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BACKGROUND: Investigators often use claims data to estimate the diagnosis timing of chronic conditions. However, misclassification of chronic conditions is common due to variability in healthcare utilization and in claims history across patients. OBJECTIVE: We aimed to quantify the effect of various Medicare fee-for-service continuous enrollment period and lookback period (LBP) on misclassification of COPD and sample size. METHODS: A stepwise tutorial to classify COPD, based on its diagnosis timing relative to lung cancer diagnosis using the Surveillance Epidemiology and End Results cancer registry linked to Medicare insurance claims. We used 3 approaches varying the LBP and required continuous enrollment (i.e., observability) period between 1 to 5 years. Patients with lung cancer were classified based on their COPD related healthcare utilization into 3 groups: pre-existing COPD (diagnosis at least 3 months before lung cancer diagnosis), concurrent COPD (diagnosis during the -/+ 3months of lung cancer diagnosis), and non-COPD. Among those with 5 years of continuous enrollment, we estimated the sensitivity of the LBP to ascertain COPD diagnosis as the number of patients with pre-existing COPD using a shorter LBP divided by the number of patients with pre-existing COPD using a longer LBP. RESULTS: Extending the LBP from 1 to 5 years increased prevalence of pre-existing COPD from ~ 36% to 51%, decreased both concurrent COPD from ~ 34% to 23% and non-COPD from ~ 29% to 25%. There was minimal effect of extending the required continuous enrollment period beyond one year across various LBPs. In those with 5 years of continuous enrollment, sensitivity of COPD classification (95% CI) increased with longer LBP from 70.1% (69.7% to 70.4%) for one-year LBP to 100% for 5-years LBP. CONCLUSION: The length of optimum LBP and continuous enrollment period depends on the context of the research question and the data generating mechanisms. Among Medicare beneficiaries, the best approach to identify diagnosis timing of COPD relative to lung cancer diagnosis is to use all available LBP with at least one year of required continuous enrollment.
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BACKGROUND: The Hispanic population is the second largest racial/ethnic group in the US, consisting of multiple distinct ethnicities. Ethnicity-specific variations in cancer mortality may be attributed to countries of birth, so we aimed to understand differences in cancer mortality among disaggregated Hispanics by nativity (native- or foreign- born vs. US-born) over 15 years. METHODS: 228,197 Hispanic decedents (Mexican, Puerto Rican [PR], Cuban, and Central or South American) with cancer-related deaths from US death certificates (2003-2017) were analyzed. Seven cancers that contribute significantly to Hispanic male (lung and bronchus, colon and rectum, liver, prostate, and pancreas cancers) and female (lung and bronchus, liver, pancreas, colon and rectum, female breast, and ovary cancers) mortality were selected for analysis. 5-year age-adjusted mortality rates [AAMR (95% CI); per 100,000] and standardized mortality ratios [SMR (95% CI)] using foreign-born as the reference group were calculated. Joinpoint regression analysis was used to model cancer-related mortality trends. RESULTS: Puerto Rico-born PRs, Cuba-born Cubans, and US-born Mexicans had some of the highest cancer death rates among all the Hispanic groups. In general, foreign-born Hispanics had higher cancer mortality rates than US-born, except Mexicans. Overall, US-born and non-US-born (i.e. native- or foreign- born) Hispanic groups experienced decreasing rates of cancer deaths over the years. CONCLUSIONS: We noted vast heterogeneity in mortality rates by nativity across Hispanic groups, a fast-growing diverse US population. IMPACT: Understanding disaggregated patterns and trends in cancer burden can motivate deeper discussion around community health resources, which may improve the health of Hispanics across the US.
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PURPOSE: Randomized trials have found that patients with locoregionally advanced p16+ oropharyngeal squamous cell carcinoma (OPSCC) do not benefit from treatment deintensification, even among favorable risk groups. Although various methods have been used to identify candidates for treatment deintensification, the optimal approach is unknown. METHODS AND MATERIALS: We conducted a multi-institutional cohort study of 444 patients with previously untreated p16+ OPSCC undergoing definitive radiation therapy with or without systemic therapy between 2009 and 2022. We compared the following 2 approaches for identifying candidates for deintensification: (1) favorable versus unfavorable risk, using NRG-HN005 eligibility criteria, and (2) low versus high relative risk of cancer events, using the Head and Neck Cancer Intergroup predictive classifier ("omega score"). We tested differences in outcomes and systemic therapy allocation by risk group using multivariable Cox models, competing event models, and logistic regression, and compared characteristics of hypothetical deintensification trials using the 2 approaches. Progression-free survival events were defined as cancer recurrence (locoregional or distant) or death from any cause. RESULTS: Median follow-up time was 52 months; 120 patients (27.0%) were favorable risk; a different 120 patients had low omega score; 28 patients (6.3%) met both criteria; 184 patients (41.4%) had discordant classification. On ordinal logistic regression, decreasing omega score was associated with a statistically significantly lower odds of receiving intensive therapy (normalized odds ratio, 0.37 per SD; 95% CI, 0.24-0.57), with a greater magnitude than favorable risk group (odds ratio, 0.66; 95% CI, 0.44-0.99). Among patients receiving cisplatin and/or platinum-based induction (n = 374), favorable risk was associated with significantly improved progression-free survival (hazard ratio, 0.59; 95% CI, 0.36-0.99), whereas lower omega score was associated with a significantly decreased relative hazard for cancer events (relative hazard ratio, 0.18; 95% CI, 0.070-0.46). In simulations, selecting patients with low omega scores increased the efficiency of hypothetical noninferiority trials. CONCLUSIONS: Considering patients' relative risk of cancer events can help define optimal populations for treatment deintensification in p16+ OPSCC.
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This cross-sectional study examines poverty, rurality, and the intersection of persistent poverty and rurality on early-onset colorectal cancer survival among adults aged 18 to 49 years.
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Neoplasias Colorretais , Pobreza , População Rural , Humanos , Neoplasias Colorretais/mortalidade , Pobreza/estatística & dados numéricos , Masculino , Feminino , População Rural/estatística & dados numéricos , Adulto , Pessoa de Meia-Idade , Idade de Início , Estados Unidos/epidemiologiaRESUMO
Rationale: Chronic obstructive pulmonary disease (COPD) is a common comorbidity among patients with lung cancer, and an important determinant of their outcomes, however, it is commonly underdiagnosed. Objective: Our objective was to estimate the prevalence of COPD among a cohort of U.S. lung cancer patients, the timing of a COPD diagnosis relative to their lung cancer diagnosis, and the association between an earlier diagnosis of COPD and stage of lung cancer, with consideration of patient sociodemographic modifying factors. Methods: We conducted an analysis of the Medicare-linked Surveillance, Epidemiology, and End Results database including patients aged 68+ years who were diagnosed with lung cancer between 2008 to 2017. Exposure: Prevalence of COPD was identified using claims and subclassified based on the timing of its diagnosis relative to the lung cancer diagnostic episode-"preexisting" if diagnosed > 3 months before lung cancer, and "concurrent" if diagnosed around the same time as the lung cancer (+/-3 months). Outcome: The stage of cancer at diagnosis (early versus late) was the outcome. Results: Among 159,542 patients with lung cancer, 73.5% had COPD. Among those with COPD, 34.4% were diagnosed within 3 months of their lung cancer diagnosis and considered to have "concurrent COPD." We observed a positive association between preexisting COPD diagnosis and early-stage lung cancer (prevalence ratio= 1.27; 95% confidence interval= 1.23-1.30), in adjusted models which were stronger for male, non-Hispanic Black, and Hispanic patients. Conclusions: Seven out of 10 patients with lung cancer have COPD, however, many do not receive their COPD diagnosis until around the time of their lung cancer diagnosis. Among these patients, an early COPD diagnosis may improve early detection of lung cancer.
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BACKGROUND: Internationally, 20% to 50% of cancer is diagnosed through emergency presentation, which is associated with lower survival, poor patient experience, and socioeconomic disparities, but population-based evidence about emergency diagnosis in the United States is limited. We estimated emergency department (ED) involvement in the diagnosis of cancer in a nationally representative population of older US adults, and its association with sociodemographic, clinical, and tumor characteristics. METHODS: We analyzed Surveillance, Epidemiology, and End Results Program-Medicare data for Medicare beneficiaries (≥66 years old) with a diagnosis of female breast, colorectal, lung, and prostate cancers (2008-2017), defining their earliest cancer-related claim as their index date, and patients who visited the ED 0 to 30 days before their index date to have "ED involvement" in their diagnosis, with stratification as 0 to 7 or 8 to 30 days. We estimated covariate-adjusted associations of patient age, sex, race and ethnicity, marital status, comorbidity score, tumor stage, year of diagnosis, rurality, and census-tract poverty with ED involvement using modified Poisson regression. RESULTS: Among 614â748 patients, 23% had ED involvement, with 18% visiting the ED in the 0 to 7 days before their index date. This rate varied greatly by tumor site, with breast cancer at 8%, colorectal cancer at 39%, lung cancer at 40%, and prostate cancer at 7%. In adjusted models, older age, female sex, non-Hispanic Black and Native Hawaiian or Other Pacific Islander race, being unmarried, recent year of diagnosis, later-stage disease, comorbidities, and poverty were associated with ED involvement. CONCLUSIONS: The ED may be involved in the initial identification of cancer for 1 in 5 patients. Earlier, system-level identification of cancer in non-ED settings should be prioritized, especially among underserved populations.
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Neoplasias da Mama , Neoplasias Colorretais , Serviço Hospitalar de Emergência , Neoplasias Pulmonares , Medicare , Neoplasias , Neoplasias da Próstata , Programa de SEER , Idoso , Idoso de 80 Anos ou mais , Feminino , Humanos , Masculino , Fatores Etários , Negro ou Afro-Americano/estatística & dados numéricos , Neoplasias da Mama/diagnóstico , Neoplasias da Mama/epidemiologia , Neoplasias Colorretais/diagnóstico , Neoplasias Colorretais/epidemiologia , Neoplasias Colorretais/etnologia , Comorbidade , Serviço Hospitalar de Emergência/estatística & dados numéricos , Neoplasias Pulmonares/epidemiologia , Neoplasias Pulmonares/diagnóstico , Estado Civil , Medicare/estatística & dados numéricos , Estadiamento de Neoplasias , Neoplasias/epidemiologia , Neoplasias/diagnóstico , Pobreza/estatística & dados numéricos , Neoplasias da Próstata/epidemiologia , Neoplasias da Próstata/diagnóstico , Neoplasias da Próstata/etnologia , Fatores Sexuais , Estados Unidos/epidemiologia , Havaiano Nativo ou Outro Ilhéu do PacíficoRESUMO
PURPOSE: Screening history influences stage at detection, but regular preventive care may also influence breast tumor diagnostic characteristics. Few studies have evaluated healthcare utilization (both screening and primary care) in racially diverse screening-eligible populations. METHODS: This analysis included 2,058 women age 45-74 (49% Black) from the Carolina Breast Cancer Study, a population-based cohort of women diagnosed with invasive breast cancer between 2008 and 2013. Screening history (threshold 0.5 mammograms per year) and pre-diagnostic healthcare utilization (i.e. regular care, based on responses to "During the past ten years, who did you usually see when you were sick or needed advice about your health?") were assessed as binary exposures. The relationship between healthcare utilization and tumor characteristics were evaluated overall and race-stratified. RESULTS: Among those lacking screening, Black participants had larger tumors (5 + cm) (frequency 19.6% vs 11.5%, relative frequency difference (RFD) = 8.1%, 95% CI 2.8-13.5), but race differences were attenuated among screening-adherent participants (10.2% vs 7.0%, RFD = 3.2%, 0.2-6.2). Similar trends were observed for tumor stage and mode of detection (mammogram vs lump). Among all participants, those lacking both screening and regular care had larger tumors (21% vs 8%, RR = 2.51, 1.76-3.56) and advanced (3B +) stage (19% vs 6%, RR = 3.15, 2.15-4.63) compared to the referent category (screening-adherent and regular care). Under-use of regular care and screening was more prevalent in socioeconomically disadvantaged areas of North Carolina. CONCLUSIONS: Access to regular care is an important safeguard for earlier detection. Our data suggest that health equity interventions should prioritize both primary care and screening.
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Neoplasias da Mama , Detecção Precoce de Câncer , Disparidades em Assistência à Saúde , Humanos , Feminino , Neoplasias da Mama/diagnóstico , Neoplasias da Mama/etnologia , Pessoa de Meia-Idade , Idoso , Detecção Precoce de Câncer/estatística & dados numéricos , Disparidades em Assistência à Saúde/estatística & dados numéricos , Disparidades em Assistência à Saúde/etnologia , North Carolina/epidemiologia , Mamografia/estatística & dados numéricos , Aceitação pelo Paciente de Cuidados de Saúde/estatística & dados numéricos , Aceitação pelo Paciente de Cuidados de Saúde/etnologia , Negro ou Afro-Americano/estatística & dados numéricos , Estudos de Coortes , População Branca/estatística & dados numéricos , Programas de Rastreamento/estatística & dados numéricos , Programas de Rastreamento/métodosRESUMO
Immortal time bias is a well-recognized bias in clinical epidemiology but is rarely discussed in environmental epidemiology. Under the target trial framework, this bias is formally conceptualized as a misalignment between the start of study follow-up (time 0) and treatment assignment. This misalignment can occur when attained duration of follow-up is encoded into treatment assignment using minimums, maximums, or averages. The bias can be exacerbated in the presence of time trends commonly found in environmental exposures. Using lung cancer cases from the California Cancer Registry (2000-2010) linked with estimated concentrations of particulate matter less than or equal to 2.5 µm in aerodynamic diameter (PM2.5), we replicated previous studies that averaged PM2.5 exposure over follow-up in a time-to-event model. We compared this approach with one that ensures alignment between time 0 and treatment assignment, a discrete-time approach. In the former approach, the estimated overall hazard ratio for a 5-µg/m3 increase in PM2.5 was 1.38 (95% confidence interval: 1.36, 1.40). Under the discrete-time approach, the estimated pooled odds ratio was 0.99 (95% confidence interval: 0.98, 1.00). We conclude that the strong estimated effect in the former approach was likely driven by immortal time bias, due to misalignment at time 0. Our findings highlight the importance of appropriately conceptualizing a time-varying environmental exposure under the target trial framework to avoid introducing preventable systematic errors.
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Poluentes Atmosféricos , Poluição do Ar , Neoplasias Pulmonares , Humanos , Neoplasias Pulmonares/epidemiologia , Fatores de Tempo , Viés , Material Particulado/efeitos adversos , Modelos de Riscos Proporcionais , Exposição Ambiental/efeitos adversos , Exposição Ambiental/análise , Poluição do Ar/efeitos adversosRESUMO
OBJECTIVE: Lung cancer is the most common cause of cancer-related death in the USA. While most patients are diagnosed following symptomatic presentation, no studies have compared symptoms and physical examination signs at or prior to diagnosis from electronic health records (EHRs) in the USA. We aimed to identify symptoms and signs in patients prior to diagnosis in EHR data. DESIGN: Case-control study. SETTING: Ambulatory care clinics at a large tertiary care academic health centre in the USA. PARTICIPANTS, OUTCOMES: We studied 698 primary lung cancer cases in adults diagnosed between 1 January 2012 and 31 December 2019, and 6841 controls matched by age, sex, smoking status and type of clinic. Coded and free-text data from the EHR were extracted from 2 years prior to diagnosis date for cases and index date for controls. Univariate and multivariable conditional logistic regression were used to identify symptoms and signs associated with lung cancer at time of diagnosis, and 1, 3, 6 and 12 months before the diagnosis/index dates. RESULTS: Eleven symptoms and signs recorded during the study period were associated with a significantly higher chance of being a lung cancer case in multivariable analyses. Of these, seven were significantly associated with lung cancer 6 months prior to diagnosis: haemoptysis (OR 3.2, 95% CI 1.9 to 5.3), cough (OR 3.1, 95% CI 2.4 to 4.0), chest crackles or wheeze (OR 3.1, 95% CI 2.3 to 4.1), bone pain (OR 2.7, 95% CI 2.1 to 3.6), back pain (OR 2.5, 95% CI 1.9 to 3.2), weight loss (OR 2.1, 95% CI 1.5 to 2.8) and fatigue (OR 1.6, 95% CI 1.3 to 2.1). CONCLUSIONS: Patients diagnosed with lung cancer appear to have symptoms and signs recorded in the EHR that distinguish them from similar matched patients in ambulatory care, often 6 months or more before diagnosis. These findings suggest opportunities to improve the diagnostic process for lung cancer.
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Registros Eletrônicos de Saúde , Neoplasias Pulmonares , Adulto , Humanos , Estudos de Casos e Controles , Centros de Atenção Terciária , Neoplasias Pulmonares/diagnóstico , Assistência AmbulatorialRESUMO
OBJECTIVES: Collider bias is a common threat to internal validity in clinical research but is rarely mentioned in informatics education or literature. Conditioning on a collider, which is a variable that is the shared causal descendant of an exposure and outcome, may result in spurious associations between the exposure and outcome. Our objective is to introduce readers to collider bias and its corollaries in the retrospective analysis of electronic health record (EHR) data. TARGET AUDIENCE: Collider bias is likely to arise in the reuse of EHR data, due to data-generating mechanisms and the nature of healthcare access and utilization in the United States. Therefore, this tutorial is aimed at informaticians and other EHR data consumers without a background in epidemiological methods or causal inference. SCOPE: We focus specifically on problems that may arise from conditioning on forms of healthcare utilization, a common collider that is an implicit selection criterion when one reuses EHR data. Directed acyclic graphs (DAGs) are introduced as a tool for identifying potential sources of bias during study design and planning. References for additional resources on causal inference and DAG construction are provided.
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Aceitação pelo Paciente de Cuidados de Saúde , Estudos Retrospectivos , Fatores de Confusão Epidemiológicos , Viés , Métodos EpidemiológicosRESUMO
The diagnosis of lung cancer in ambulatory settings is often challenging due to non-specific clinical presentation, but there are currently no clinical quality measures (CQMs) in the United States used to identify areas for practice improvement in diagnosis. We describe the pre-diagnostic time intervals among a retrospective cohort of 711 patients identified with primary lung cancer from 2012-2019 from ambulatory care clinics in Seattle, Washington USA. Electronic health record data were extracted for two years prior to diagnosis, and Natural Language Processing (NLP) applied to identify symptoms/signs from free text clinical fields. Time points were defined for initial symptomatic presentation, chest imaging, specialist consultation, diagnostic confirmation, and treatment initiation. Median and interquartile ranges (IQR) were calculated for intervals spanning these time points. The mean age of the cohort was 67.3 years, 54.1% had Stage III or IV disease and the majority were diagnosed after clinical presentation (94.5%) rather than screening (5.5%). Median intervals from first recorded symptoms/signs to diagnosis was 570 days (IQR 273-691), from chest CT or chest X-ray imaging to diagnosis 43 days (IQR 11-240), specialist consultation to diagnosis 72 days (IQR 13-456), and from diagnosis to treatment initiation 7 days (IQR 0-36). Symptoms/signs associated with lung cancer can be identified over a year prior to diagnosis using NLP, highlighting the need for CQMs to improve timeliness of diagnosis.
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Introduction: Secondhand and thirdhand tobacco smoke exposure most often occur at home, but little is known about occurrences of in-home cannabis smoking. We ascertained in-home cannabis smoking reported by all cannabis-using (i.e., used in the last 12 months) respondents to the Global Drug Survey (GDS; international-GDS sample), and among U.S. cannabis-using respondents (US-GDS sample). Materials and Methods: We used data collected November 2019-January 2020 for the 2020 GDS, an annual anonymous, cross-sectional survey; respondents were 16+ years old, from 191 countries. We estimated any and daily in-home cannabis smoking in the last 30 days among international-GDS respondents (n=63,797), using mixed effects logistic regression. US-GDS respondents (n=6,580) were weighted to the covariate distribution of the nationally representative 2018 National Survey on Drug Use and Health cannabis-using sample, using inverse odds probability weighting, to make estimates more generalizable to the U.S. cannabis-using population. Results: For the international-GDS cannabis-using respondents, any in-home cannabis smoking was reported by 63.9% of men, 61.9% of women, and 68.6% of nonbinary people; and by age (<25 years old=62.7%, 25-34 years old=65.0%, and 35+ years old=62.8%). Daily in-home cannabis smoking was highest among nonbinary (28.7%) and respondents 35+ years of age (28.0%). For the weighted US-GDS cannabis-using respondents, any in-home cannabis smoking was reported by 49.8% of males and 61.2% of females; and by age (<25 years old=62.6%, 25-34 years old=41.8%, 35+ years old=57.9%). Weighted daily in-home smoking was 23.2% among males and 37.1% among females; by age (<25 years old=34.8%, 25-34 years old=27.8%, and 35+ years old=21.6%). Conclusions: There was high daily cannabis smoking in homes of international-GDS and US-GDS respondents who used cannabis in the last 12 months. In part, due to cannabis legalization, the number of users worldwide has increased over the past decade. Criminal stigma historically associated with cannabis continues to drive those users indoors. In this context, our findings support further investigation of cannabis use behavior to understand how often people are exposed to secondhand and thirdhand cannabis smoke and the consequences of that exposure.
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BACKGROUND: Travel time to treatment facilities may impede the receipt of guideline-concordant treatment (GCT) among patients diagnosed with early-stage non-small cell lung cancer (ES-NSCLC). We investigated the relative contribution of travel time in the receipt of GCT among ES-NSCLC patients. METHODS: We included 22,821 ES-NSCLC patients diagnosed in California from 2006-2015. GCT was defined using the 2016 National Comprehensive Cancer Network guidelines, and delayed treatment was defined as treatment initiation >6 versus ≤6 weeks after diagnosis. Mean-centered driving and public transit times were calculated from patients' residential block group centroid to the treatment facilities. We used logistic regression to estimate risk ratios and 95% confidence intervals (CIs) for the associations between patients' travel time and receipt of GCT and timely treatment, overall and by race/ethnicity and neighborhood socioeconomic status (nSES). RESULTS: Overall, a 15-minute increase in travel time was associated with a decreased risk of undertreatment and delayed treatment. Compared to Whites, among Blacks, a 15-minute increase in driving time was associated with a 24% (95%CI = 8%-42%) increased risk of undertreatment, and among Filipinos, a 15-minute increase in public transit time was associated with a 27% (95%CI = 13%-42%) increased risk of delayed treatment. Compared to the highest nSES, among the lowest nSES, 15-minute increases in driving and public transit times were associated with 33% (95%CI = 16%-52%) and 27% (95%CI = 16%-39%) increases in the risk of undertreatment and delayed treatment, respectively. CONCLUSION: The benefit of GCT observed with increased travel times may be a 'Travel Time Paradox,' and may vary across racial/ethnic and socioeconomic groups.
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Carcinoma Pulmonar de Células não Pequenas , Neoplasias Pulmonares , California/epidemiologia , Carcinoma Pulmonar de Células não Pequenas/epidemiologia , Carcinoma Pulmonar de Células não Pequenas/terapia , Etnicidade , Disparidades em Assistência à Saúde , Humanos , Neoplasias Pulmonares/epidemiologia , Neoplasias Pulmonares/terapia , Classe SocialRESUMO
BACKGROUND: To test whether nomograms developed by NRG Oncology for oropharyngeal squamous cell carcinoma (OPSCC) patients could be validated in an independent population-based sample. METHODS: The authors tested nomograms for estimating progression-free survival (PFS) and overall survival (OS) in patients from the Veterans Health Administration with previously untreated locoregionally advanced OPSCC, diagnosed between 2008 and 2017, managed with definitive radiotherapy with or without adjuvant systemic therapy. Covariates were age, performance status, p16 status, T/N category, smoking history, education history, weight loss, marital status, and anemia. We used multiple imputation to handle missing data and performed sensitivity analyses on complete cases. Validation was assessed via Cox proportional hazards models, log-rank tests, and c-indexes. RESULTS: A total of 4007 patients met inclusion criteria (658 patients had complete data). Median follow-up time was 3.20 years, with 967 progression events and 471 noncancer deaths. Each risk score was associated with poorer outcomes per unit increase (PFS score, hazard ratio [HR], 1.42 [1.37-1.47]; OS score, HR, 1.40 [1.34-1.45]). By risk score quartile, 2-year PFS estimates were 89.2%, 78.5%, 65.8%, and 48.3%; OS estimates were 92.6%, 83.6%, 73.9%, and 51.3%, respectively (P < .01 for all comparisons). C-indices for models of PFS and OS were 0.65 and 0.67, for all patients, respectively (0.69 and 0.73 for complete cases). The nomograms slightly overestimated PFS and OS in the overall cohort but exhibited high agreement in complete cases. CONCLUSIONS: NRG nomograms were effective for predicting PFS and OS for patients with OPSCC, supporting their broader applicability in the OPSCC population undergoing definitive radiotherapy.
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Neoplasias de Cabeça e Pescoço , Neoplasias Orofaríngeas , Veteranos , Humanos , Nomogramas , Neoplasias Orofaríngeas/terapia , Prognóstico , Carcinoma de Células Escamosas de Cabeça e PescoçoRESUMO
PURPOSE: Cancer treatments can paradoxically appear to reduce the risk of noncancer mortality in observational studies, due to residual confounding. Here we introduce a method, Bias Reduction through Analysis of Competing Events (BRACE), to reduce bias in the presence of residual confounding. EXPERIMENTAL DESIGN: BRACE is a novel method for adjusting for bias from residual confounding in proportional hazards models. Using standard simulation methods, we compared BRACE with Cox proportional hazards regression in the presence of an unmeasured confounder. We examined estimator distributions, bias, mean squared error (MSE), and coverage probability. We then estimated treatment effects of high versus low intensity treatments in 36,630 prostate cancer, 4,069 lung cancer, and 7,117 head/neck cancer patients, using the Veterans Affairs database. We analyzed treatment effects on cancer-specific mortality (CSM), noncancer mortality (NCM), and overall survival (OS), using conventional multivariable Cox and propensity score (adjusted using inverse probability weighting) models, versus BRACE-adjusted estimates. RESULTS: In simulations with residual confounding, BRACE uniformly reduced both bias and MSE. In the absence of bias, BRACE introduced bias toward the null, albeit with lower MSE. BRACE markedly improved coverage probability, but with a tendency toward overcorrection for effective but nontoxic treatments. For each clinical cohort, more intensive treatments were associated with significantly reduced hazards for CSM, NCM, and OS. BRACE attenuated OS estimates, yielding results more consistent with findings from randomized trials and meta-analyses. CONCLUSIONS: BRACE reduces bias and MSE when residual confounding is present and represents a novel approach to improve treatment effect estimation in nonrandomized studies.
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Neoplasias , Viés , Estudos de Coortes , Humanos , Masculino , Neoplasias/terapia , Pontuação de Propensão , Modelos de Riscos Proporcionais , Viés de SeleçãoRESUMO
BACKGROUND: Using more recent cancer registry data, we analyzed disparities in hepatocellular carcinoma (HCC) incidence by ethnic enclave and neighborhood socioeconomic status (nSES) among Asian American/Pacific Islander (AAPI) and Hispanic populations in California. METHODS: Primary, invasive HCC cases were identified from the California Cancer Registry during 1988-1992, 1998-2002, and 2008-2012. Age-adjusted incidence rates (per 100,000 population), incidence rate ratios, and corresponding 95% confidence intervals were calculated for AAPI or Hispanic enclave, nSES, and the joint effects of ethnic enclave and nSES by time period (and the combination of the three periods), sex, and race/ethnicity. RESULTS: In the combined time period, HCC risk increased 25% for highest versus lowest quintile of AAPI enclave among AAPI males. HCC risk increased 22% and 56% for lowest versus highest quintile of nSES among AAPI females and males, respectively. In joint analysis, AAPI males living in low nSES areas irrespective of enclave status were at 17% to 43% increased HCC risk compared with AAPI males living in areas of nonenclave/high nSES. HCC risk increased by 22% for Hispanic females living in areas of low nSES irrespective of enclave status and by 19% for Hispanic males living in areas of nonenclave/low nSES compared with their counterparts living in areas of nonenclave/high nSES. CONCLUSIONS: We found significant variation in HCC incidence by ethnic enclave and nSES among AAPI and Hispanic populations in California by sex and time period. IMPACT: Future studies should explore how specific attributes of enclaves and nSES impact HCC risk for AAPI and Hispanic populations.