Breast density and risk of breast cancer: masking and detection bias.

Breast density is associated with risk of breast cancer (BC) diagnosis, impacting risk prediction tools and patient notification policies. Density affects mammography sensitivity and may influence screening intensity. Therefore, the observed association between density and BC diagnosis may not reflect the relationship between density and disease risk. We investigate the association between breast density and BC risk using data sourced from 33,542 women in the Breast Cancer Surveillance Consortium, 2000-2018. We estimated mammogram sensitivity and rates of screening mammography among dense (BI-RADS c, d) and non-dense (BI-RADS a, b) breasts. We used Kaplan-Meier estimates to summarize the relative risks of BC diagnosis (RRdx) by density and fit a natural history model to estimate the relative risks of BC onset (RRonset) given density-specific sensitivities. RRdx for dense versus non-dense breasts was 1.80 (95% CI 1.46 to 2.57). Based on estimated screening sensitivities of 0.88 and .78 for non-dense and dense breasts, respectively, RRonset was 1.73 (95% CI 1.43 to 2.25). Sensitivity analyses suggested higher breast density is robustly associated with increased risk of BC onset, similar in magnitude to the increased risk of BC diagnosis. These finding support laws requiring notifications to women with dense breasts of their increased BC risk.

Healthcare system engagement and algorithm-identified cancer incidence following initiation of a new medication.

PURPOSE: Implausibly high algorithm-identified cancer incidence within a new user study after medication initiation may result from increased healthcare utilization (HU) around initiation ("catch-up care") that increases diagnostic opportunity. Understanding the relationships between HU prior to and around initiation and subsequent cancer rates and timing is important to avoiding protopathic bias. METHODS: We identified a cohort of 417 458 Medicare beneficiaries (2007-2014) aged ≥66 initiating an antihypertensive (AHT) after ≥180 days of non-use. Initiators were stratified into groups of 0, 1, 2-3, and ≥4 outpatient visits (OV) 60-360 days before initiation. We calculated algorithm-identified colorectal cancer (aiCRC) rates stratified by OVs and time since AHT initiation: (0-90, 91-180, 181-365, 366-730, and 731+ days). We summarized HU -360/+60 days around AHT initiation by aiCRC timing: (0-29, 30-89, 90-179, and ≥180 days). RESULTS: AiCRC incidence (311 per 100 000 overall) peaked in the first 0-90 days, was inversely associated with HU before initiation, and stabilized ≥180 days after AHT initiation. Catch-up care was greatest among persons with aiCRCs identified <30 days in follow-up. Catch-up care magnitude decreased as time to the aiCRC date increased, with aiCRCs identified ≥180 days after AHT initiation exhibiting similar HU compared with the full cohort. CONCLUSION: Lower HU before-and increased HU around AHT initiation-seem to drive excess short-term aiCRC incidence. Person-time and case accrual should only begin when incidence stabilizes. When comparison groups within a study differ by HU, outcome-detection bias may exist. Similar observations may exist in other settings when typical HU is delayed (e.g., cancer screening during SARS-CoV-2).

The relationship between prior psychiatric diagnosis and brain cancer diagnosis in the U.S. military health system.

PURPOSE: Prior research suggested the increased likelihood of brain cancer diagnosis following certain psychiatric diagnoses. This association may result from detection bias or suggest an early sign for brain cancer. This study investigated whether psychiatric illness may be an early manifestation of brain cancer while considering potential effects of detection bias. METHODS: This case-control study used the data from the Department of Defense's Central Cancer Registry and the Military Health System Data Repository. Four cancer-free controls and one negative-outcome control (cancers not associated with psychiatric illness) were matched to each brain cancer case diagnosed from 1998 to 2013 by age, sex, race, and military status. The groups were compared in the likelihood of having a pre-existing psychiatric diagnosis using conditional logistic regression. RESULTS: We found a significant association of psychiatric illnesses with brain cancer (Odds Ratio (OR) = 2.63, 95% confidence interval (CI) = 2.18-3.16) and other cancers (OR = 1.80, 95% CI = 1.49-2.19), compared to non-cancer controls. The association was stronger for psychiatric diagnoses within three months before cancer (brain cancer: OR = 26.77, 95% CI = 15.40-46.53; other cancers: OR = 4.12, 95% CI = 1.96-8.65). The association with psychiatric disorders within 3 months were higher for small brain tumors (OR = 128.32, 95% CI = 17.28-952.92 compared to non-cancer controls) while the OR was 2.79 for other cancers (95% CI = 0.86-8.99 compared to non-cancer controls). CONCLUSION: Our findings suggest an association between diagnosed psychiatric illnesses and subsequent brain cancer diagnosis, which may not be solely explained by detection bias. Psychiatric illness might be a sign for early detection of brain cancer beyond the potential effects of detection bias.

Lung cancer symptom appraisal, help-seeking and diagnosis - rapid systematic review of differences between patients with and without a smoking history.

BACKGROUND: Lung cancer is the leading cause of cancer death in the world. A significant minority of lung cancer patients have never smoked (14% in the UK, and ranging from 10% to 25% worldwide). Current evidence suggests that never-smokers encounter delays during the diagnostic pathway, yet it is unclear how their experiences and reasons for delayed diagnoses differ from those of current and former smokers. This rapid review assessed literature about patient experiences in relation to symptom awareness and appraisal, help-seeking, and the lung cancer diagnostic pathway, comparing patients with and without a smoking history. METHODS: MEDLINE, PsychINFO and Google Scholar were searched for studies (2010-2020) that investigated experiences of the pathway to diagnosis for patients with and without a smoking history. Findings are presented using a narrative synthesis. RESULTS: Analysis of seven quantitative and three qualitative studies revealed that some delays during symptom appraisal and diagnosis are unique to never-smokers. Due to the strong link between smoking and lung cancer, and low awareness of non-smoking related lung cancer risk factors and symptoms, never-smokers do not perceive themselves to be at risk. Never-smokers are also likely to evaluate their experiences in comparison with other non-smoking related cancers, where prognosis is likely better, potentially leading to lower satisfaction with healthcare. CONCLUSION: Never-smokers appear to have different experiences in relation to symptom appraisal and diagnosis. However, evidence in relation to help-seeking, and what is driving diagnostic delays for never-smoker patients specifically is lacking.

Assessing the risk of performance and detection bias in Cochrane reviews as a joint domain is less accurate compared to two separate domains.

BACKGROUND: Initially, the Cochrane risk of bias (RoB) tool had a domain for "blinding of participants, personnel and outcome assessors". In the 2011 tool, the assessment of blinding was split into two domains: blinding of participants and personnel (performance bias) and blinding of outcome assessors (detection bias). The aims of this study were twofold; first, to analyze the frequency of usage of the joint blinding domain (a single domain for performance and detection bias), and second, to assess the proportion of adequate assessments made in the joint versus single RoB domains for blinding by comparing whether authors' RoB judgments were supported by explanatory comments in line with the Cochrane Handbook recommendations. METHODS: We extracted information about the assessment of blinding from RoB tables (judgment, comment, and whether it was specified which outcome type; e.g., objective, subjective) of 729 Cochrane reviews published in 2015-2016. In the Cochrane RoB tool, judgment (low, unclear or high risk) needs to be accompanied by a transparent comment, in which authors provide a summary justifying RoB judgment, to ensure transparency in how these judgments were reached. We reassessed RoB based on the supporting comments reported in Cochrane RoB tables, in line with instructions from the Cochrane Handbook. Then, we compared our new assessments to judgments made by Cochrane authors. We compared the frequency of adequate judgments in reviews with two separate domains for blinding versus those with a joint domain for blinding. RESULTS: The total number of assessments for performance bias was 6918, with 8656 for detection bias and 3169 for the joint domain. The frequency of adequate assessments was 74% for performance bias, 78% for detection bias, and 59% for the joint domain. The lowest frequency of adequate assessments was found when Cochrane authors judged low risk - 47% in performance bias, 62% in detection bias, and 31% in the joint domain. The joint domain and detection bias domain had a similar proportion of specified outcome types (17% and 18%, respectively). CONCLUSIONS: Splitting joint RoB assessment about blinding into two domains was justified because the frequency of adequate judgments was higher in separate domains. Specification of outcome types in RoB domains should be further scrutinized.

Expected-value bias in routine third-trimester growth scans.

OBJECTIVES: Operators performing fetal growth scans are usually aware of the gestational age of the pregnancy, which may lead to expected-value bias when performing biometric measurements. We aimed to evaluate the incidence of expected-value bias in routine fetal growth scans and assess its impact on standard biometric measurements. METHODS: We collected prospectively full-length video recordings of routine ultrasound growth scans coupled with operator eye tracking. Expected value was defined as the gestational age at the time of the scan, based on the estimated due date that was established at the dating scan. Expected-value bias was defined as occurring when the operator looked at the measurement box on the screen during the process of caliper adjustment before saving a measurement. We studied the three standard biometric planes on which measurements of head circumference (HC), abdominal circumference (AC) and femur length (FL) are obtained. We evaluated the incidence of expected-value bias and quantified the impact of biased measurements. RESULTS: We analyzed 272 third-trimester growth scans, performed by 16 operators, during which a total of 1409 measurements (354 HC, 703 AC and 352 FL; including repeat measurements) were obtained. Expected-value bias occurred in 91.4% of the saved standard biometric plane measurements (85.0% for HC, 92.9% for AC and 94.9% for FL). The operators were more likely to adjust the measurements towards the expected value than away from it (47.7% vs 19.7% of measurements; P < 0.001). On average, measurements were corrected by 2.3 ± 5.6, 2.4 ± 10.4 and 3.2 ± 10.4 days of gestation towards the expected gestational age for the HC, AC, and FL measurements, respectively. Additionally, we noted a statistically significant reduction in measurement variance once the operator was biased (P = 0.026). Comparing the lowest and highest possible estimated fetal weight (using the smallest and largest biased HC, AC and FL measurements), we noted that the discordance, in percentage terms, was 10.1% ± 6.5%, and that in 17% (95% CI, 12-21%) of the scans, the fetus could be considered as small-for-gestational age or appropriate-for-gestational age if using the smallest or largest possible measurements, respectively. Similarly, in 13% (95% CI, 9-16%) of scans, the fetus could be considered as large-for-gestational age or appropriate-for-gestational age if using the largest or smallest possible measurements, respectively. CONCLUSIONS: During routine third-trimester growth scans, expected-value bias frequently occurs and significantly changes standard biometric measurements obtained. © 2019 the Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of the International Society of Ultrasound in Obstetrics and Gynecology.

Deep learning COVID-19 detection bias: accuracy through artificial intelligence.

BACKGROUND: Detection of COVID-19 cases' accuracy is posing a conundrum for scientists, physicians, and policy-makers. As of April 23, 2020, 2.7 million cases have been confirmed, over 190,000 people are dead, and about 750,000 people are reported recovered. Yet, there is no publicly available data on tests that could be missing infections. Complicating matters and furthering anxiety are specific instances of false-negative tests. METHODS: We developed a deep learning model to improve accuracy of reported cases and to precisely predict the disease from chest X-ray scans. Our model relied on convolutional neural networks (CNNs) to detect structural abnormalities and disease categorization that were keys to uncovering hidden patterns. To do so, a transfer learning approach was deployed to perform detections from the chest anterior-posterior radiographs of patients. We used publicly available datasets to achieve this. RESULTS: Our results offer very high accuracy (96.3%) and loss (0.151 binary cross-entropy) using the public dataset consisting of patients from different countries worldwide. As the confusion matrix indicates, our model is able to accurately identify true negatives (74) and true positives (32); this deep learning model identified three cases of false-positive and one false-negative finding from the healthy patient scans. CONCLUSIONS: Our COVID-19 detection model minimizes manual interaction dependent on radiologists as it automates identification of structural abnormalities in patient's CXRs, and our deep learning model is likely to detect true positives and true negatives and weed out false positive and false negatives with > 96.3% accuracy.

Evidence-based recommendations for blinding in surgical trials.

RATIONALE: Blinding reduces performance and detection bias in randomized controlled trials (RCT). There is evidence that lack of blinding leads to overestimation of treatment effects in pharmacological trials. Since surgical trials use interventions with a physical component, blinding is often complicated. The aim of this study was to analyze, in general and abdominal surgery RCT, the status of blinding, the potential for blinding, and the influence of blinding on outcomes. METHODS: A systematic search of the literature in CENTRAL, MEDLINE, and Web of Science was conducted to identify RCT with a surgical intervention, starting in 1996, the year when the first CONSORT statement was published. Information on general study characteristics and blinding methods was extracted. The presence or absence of blinding of the study contributors-patients, surgeons, data collectors, outcome assessors, and data analysts-was analyzed. The association of blinding with the trial outcome was investigated for every study contributor. RESULTS: Out of 29,119 articles, 378 RCT were included in the analysis. These investigated a total of 62,522 patients, of whom 15,025 were blinded (24.0%). Contributors could have been blinded in far more trials, as the potential for blinding measures ranged from 69% for outcome assessors to 98% for data analysts. If blinding of surgeons would have been possible but had not been performed, this was associated with more significant trial outcomes (OR 13.670; 95% CI 1.308 to 142.840; p = 0.0289). DISCUSSION: The potential of blinding, an important quality measure in surgical RCT, has not been exhausted. This study summarizes the existing evidence on blinding in surgical trials and gives evidence-based recommendations for the use of blinding in future surgical trials. SYSTEMATIC REVIEW REGISTRATION: PROSPERO 2015:CRD42015026837.

Pay for performance program reduces treatment needed diabetic retinopathy - a nationwide matched cohort study in Taiwan.

BACKGROUND: Pay-for-Performance programs have shown improvement in indicators monitoring adequacy and target achievement in diabetic care. However, less is known regarding the impact of this program on the occurrence and long-term effects of diabetic retinopathy. The objective of this study was to determine the effect of pay-for-performance program on the development of treatment needed for diabetic retinopathy in type 2 diabetes patients. METHODS: We conducted a nationwide retrospective cohort study with a matching design using the Taiwan National Health Insurance Research Database from 2000 to 2012. The outcome was defined as the treatment needed diabetic retinopathy. We matched Pay-for-Performance and non-Pay-for-Performance groups for age, gender, year diabetes was diagnosed and study enrollment, and duration of follow-up. RESULTS: A total of 9311 patients entered the study cohort, of whom 2157 were registered in the Pay-for-Performance group and 7154 matched in the non-Pay-for-Performance group. The incidence of treatment needed diabetic retinopathy was not significantly different in two groups. However, the incidence of treatment needed diabetic retinopathy was significantly different if restricted the non-Pay-for-Performance group who had at least 1 eye examination or optical coherence tomography within 1 year (adjusted hazard ratio, 0.78; 95% confidence interval, 0.64-0.94). CONCLUSIONS: Pay-for-Performance is valuable in preventing the development of treatment needed diabetic retinopathy, which could be attributed to the routine eye examination required in the Pay-for-Performance program. We could improve our diabetic care by promoting eye health education and patient awareness on the importance of regular examinations.

Evidence for Detection Bias by Medication Use in a Cohort Study of Breast Cancer Survivors.

In previous studies, we found modestly decreased and increased risks of second breast cancer events with the use of statins and antibiotics, respectively, after adjustment for surveillance mammography. We evaluated detection bias by comparing receipt of surveillance mammography among users of these 2 disparate classes of medication. Adult women diagnosed with early-stage breast cancer during 1990-2008 (n = 3,965) while enrolled in an integrated health-care plan (Group Health Cooperative; Washington State) were followed for up to 10 years in the Commonly Used Medications and Breast Cancer Outcomes (COMBO) Study. Categories of antibiotic use included infrequent (1-3 dispensings/12 months) and frequent (≥4 dispensings/12 months) use, and categories of statin use included less adherent (1 dispensing/6 months) and adherent (≥2 dispensings/6 months). We examined associations between medication use and surveillance mammography using multivariable generalized estimating equations and evaluated the impact of adjusting for surveillance within Cox proportional hazard models. Frequent antibiotic users were less likely to receive surveillance mammography (odds ratio (OR) = 0.90, 95% confidence interval (CI): 0.82, 0.99) than were nonusers; no association was found among infrequent users (OR = 0.96, 95% CI: 0.90, 1.03). Adherent statin use was associated with more surveillance compared with nonuse (OR = 1.11, 95% CI: 1.01, 1.25), but less adherent statin use was not (OR = 1.03, 95% CI: 0.81, 1.31). No difference in associations between medications of interest and second breast cancer events was observed when surveillance was removed from otherwise adjusted models. The influence of detection bias by medication use warrants further exploration.

The temporal relationship between diabetes and cancer: A population-based study.

BACKGROUND: Diabetes is associated with an increased risk of several cancers; however, greater detection of cancer around the time of diabetes diagnosis may partly contribute to this relationship. The goal of the current study was to explore the temporal relationship between diabetes and cancer incidence. METHODS: The authors conducted a retrospective, population-based cohort study of >1 million adults living in Ontario, Canada to evaluate the association between diabetes diagnosis and the incidence of cancer in 3 time periods: within the 10 years before a diabetes diagnosis, within the first 3 months after a diabetes diagnosis, and from 3 months to 10 years after a diabetes diagnosis. RESULTS: Individuals with diabetes were significantly more likely to have been diagnosed with cancer within the 10 years before a diabetes diagnosis compared with individuals without diabetes (odds ratio, 1.23; 95% confidence interval [95% CI], 1.19-1.27). Cancer incidence also was found to be significantly higher in individuals with diabetes within the 3-month period after a diabetes diagnosis (hazard ratio, 1.62; 95% CI, 1.52-1.74), whereas the risk was not found to be elevated in the later period (hazard ratio, 0.97; 95% CI, 0.95-0.98). Similar trends were noted for individual cancers. CONCLUSIONS: The results demonstrated that individuals with diabetes had a significantly higher risk of most cancers, which was limited to the time periods before and immediately after a diabetes diagnosis. The highest risk period was observed within the first 3 months after a diabetes diagnosis, suggesting a partial role of detection bias in the apparent relationship between diabetes and cancer. Cancer 2016. © 2016 American Cancer Society. Cancer 2016;122:2731-2738. © 2016 American Cancer Society.

Comparison of diagnostic evaluations for cough among initiators of angiotensin converting enzyme inhibitors and angiotensin receptor blockers.

PURPOSE: Differential diagnostic evaluation associated with a drug may bias effect estimates because of an increased detection of preclinical outcomes. Persistent cough is a common side effect with angiotensin-converting enzyme inhibitors (ACEI), and we hypothesized that ACEI initiators would undergo more diagnostic evaluations, potentially leading to diagnosis of preclinical lung cancer. We compared the incidence of cough-related diagnostic evaluations and lung cancer among ACEI versus angiotensin receptor blockers (ARB) initiators. METHODS: Using a 20% sample of Medicare claims 2007-2012, we identified initiators of ACEI or ARB, age 66-99 years. Incidence of diagnostic evaluation and lung cancer were compared using adjusted Cox models. Monthly probabilities of workup were compared using proportion differences. RESULTS: There were 342 611 and 108 116 ACEI and ARB initiators, respectively. Monthly probability of chest X-rays ranged from minimum 4.7% to maximum 21.2% in the 6 months pre and post-initiation. Differences in incidence of diagnostic procedures in the 6 months after initiation were only minimal (chest X-rays hazard ratio (HR) = 1.12; 95% CI: 1.10-1.14), chest-MRI (0.86, 95% CI: 0.74-0.99), CT-scans (1.09, 95% CI: 0.99-1.18) or bronchoscopies (1.03, 95% CI: 0.83-1.29). Proportion differences for chest X-rays peaked in the month pre-initiation (8.4%, 95% CI: 8.1-8.6) but negligible thereafter. There was no difference in the incidence of lung cancer among ACEI versus ARB initiators (HR = 0.99, 95% CI: 0.84-1.16). CONCLUSION: Results indicate minimal differential chest workup after ACEI versus ARB initiation and no difference in lung cancer incidence, but suggest differential workup in the month before the first recorded prescription. The latter may reflect drug use before the first observed pharmacy claim or increased workup before initiation of ACEI therapy. Copyright © 2016 John Wiley & Sons, Ltd.

Cataract Surgery and Incidence of Retinal Vascular Occlusion: Population-Based Cohort Study Using a Target Trial Emulation Framework.

BACKGROUND: Previous studies suggested an association between cataract surgery and retinal vascular occlusion. However, the association may be attributable to detection bias because postoperative monitoring may be more frequent for those who receive cataract surgery than for those who do not. DESIGN: Population-based cohort study using target trial emulation framework. METHODS: We included patients with cataract aged 50 years and older receiving cataract surgery or non-surgical interventions identified from the Taiwan National Health Insurance Research Database between 2003 and 2018, matched by propensity score. The primary outcome was retinal vascular occlusion. Cox proportional hazards models were used to compare surgery and control groups. Additional analyses were restricted to patients who had undergone fundoscopic examination within 6 months prior to cataract surgery to address the issue of detection bias. RESULTS: We included 577,129 cataract surgery and control pairs. We found the hazard ratio (HR) for retinal vascular occlusion after cataract surgery was 1.23 (95% confidence interval (CI): 1.17-1.29), compared with the control group. Secondary outcome analyses yielded similar results for retinal artery occlusion (HR: 1.13, 95% CI: 1.02-1.26) and retinal vein occlusion (HR: 1.26, 95% CI: 1.20-1.33). However, no risk of retinal vascular occlusion was observed among patients who had received fundoscopic examinations (HR: 1.06, 95% CI: 0.98-1.15) at baseline. CONCLUSIONS: Our study underscored the importance of conducting complete baseline fundoscopic examinations before cataract surgery to clarify whether postoperative conditions are due to patients' underlying diseases or unintended complications of cataract surgery.

An easily implemented single-visit survey method for intermittently available and imperfectly detectable wildlife applied to the Florida east coast diamondback terrapin (Malaclemys terrapin tequesta).

Single-visit surveys of plots are often used for estimating the abundance of species of conservation concern. Less-than-perfect availability and detection of individuals can bias estimates if not properly accounted for. We developed field methods and a Bayesian model that accounts for availability and detection bias during single-visit visual plot surveys. We used simulated data to test the accuracy of the method under a realistic range of generating parameters and applied the method to Florida's east coast diamondback terrapin in the Indian River Lagoon system, where they were formerly common but have declined in recent decades. Simulations demonstrated that the method produces unbiased abundance estimates under a wide range of conditions that can be expected to occur in such surveys. Using terrapins as an example we show how to include covariates and random effects to improve estimates and learn about species-habitat relationships. Our method requires only counting individuals during short replicate surveys rather than keeping track of individual identity and is simple to implement in a variety of point count settings when individuals may be temporarily unavailable for observation. We provide examples in R and JAGS for implementing the model and to simulate and evaluate data to validate the application of the method under other study conditions.

Diabetes is not an independent risk factor for hepatocellular carcinoma.

BACKGROUND: It is controversial whether diabetes is a risk factor for hepatocellular carcinoma (HCC) in countries with high prevalence of viral hepatitis such as Taiwan. METHODS: From the Taiwanese National Health Insurance, 1 000 000 insurants were randomly selected for the study. Among them, 494 080 men and 502 841 women without HCC were followed from 2003 until 2005. Relative risks were estimated taking into account alcohol-related diagnoses, chronic liver disease, potential HCC detection examinations and other covariates. RESULTS: The diabetes patients were more likely to receive examinations of abdominal sonography, HBsAg, anti-HCV and alpha-fetoprotein. Multivariable-adjusted relative risk (95% confidence interval) was not significant for diabetes as a risk factor for HCC in either men or women: 0.932 (0.788-1.101) for men and 1.158 (0.968-1.386) for women. While comparing diabetes duration <1, 1-3 and ≥ 3 years to non-diabetes individuals, the respective relative risks were 1.043 (0.751-1.448), 0.945 (0.738-1.209) and 0.901 (0.744-1.091) for men; and were 0.950 (0.610-1.480), 1.169 (0.884-1.546) and 1.189 (0.974-1.452) for women. For both sexes, age, alcohol-related diagnoses, chronic liver disease and potential detection bias were significantly associated with higher risk, but dyslipidemia and stroke a lower risk. In addition, chronic obstructive pulmonary disease was associated with a lower risk and sulfonylurea a higher risk in men. Models that did not consider alcohol-related diagnoses, chronic liver disease and potential detection bias would result in spurious association between diabetes and HCC. CONCLUSIONS: Diabetes is not an independent risk factor for HCC after considering the effects of alcohol-related diagnoses, chronic liver disease and potential detection bias.

Risk of cancer versus risk of cancer diagnosis? Accounting for diagnostic bias in predictions of breast cancer risk by race and ethnicity.

OBJECTIVES: Cancer risk prediction may be subject to detection bias if utilization of screening is related to cancer risk factors. We examine detection bias when predicting breast cancer risk by race/ethnicity. METHODS: We used screening and diagnosis histories from the Breast Cancer Surveillance Consortium to estimate risk of breast cancer onset and calculated relative risk of onset and diagnosis for each racial/ethnic group compared with non-Hispanic White women. RESULTS: Of 104,073 women aged 40-54 receiving their first screening mammogram at a Breast Cancer Surveillance Consortium facility between 2000 and 2018, 10.2% (n = 10,634) identified as Asian, 10.9% (n = 11,292) as Hispanic, and 8.4% (n = 8719) as non-Hispanic Black. Hispanic and non-Hispanic Black women had slightly lower screening frequencies but biopsy rates following a positive mammogram were similar across groups. Risk of cancer diagnosis was similar for non-Hispanic Black and White women (relative risk vs non-Hispanic White = 0.90, 95% CI 0.65 to 1.14) but was lower for Asian (relative risk = 0.70, 95% CI 0.56 to 0.97) and Hispanic women (relative risk = 0.82, 95% CI 0.62 to 1.08). Relative risks of disease onset were 0.78 (95% CI 0.68 to 0.88), 0.70 (95% CI 0.59 to 0.83), and 0.95 (95% CI 0.84 to 1.09) for Asian, Hispanic, and non-Hispanic Black women, respectively. CONCLUSIONS: Racial/ethnic differences in mammography and biopsy utilization did not induce substantial detection bias; relative risks of disease onset were similar to or modestly different than relative risks of diagnosis. Asian and Hispanic women have lower risks of developing breast cancer than non-Hispanic Black and White women, who have similar risks.

Influence of abstinence on automatic detection bias to gaming cues in individuals with Internet gaming disorder: Evidence from visual mismatch negativity.

Internet gaming disorder (IGD) has been classified by the DSM-5 as a condition for further study, and many studies have shown that the occurrence and maintenance of IGD and the automatic detection bias to gaming cues of individuals with IGD may be significantly related. However, whether abstinence, a common intervention method in behavioral addiction, can adjust the automatic detection bias in individuals with IGD and its underlying neural mechanisms is unclear. In this study, we investigated the effects of 7 days of abstinence from gaming on automatic detection bias, negative affect and craving in individuals with IGD with event-related potential technology. A total of 50 IGD subjects were recruited in this study and randomly divided into abstinence and control groups. Visual mismatch negativity (vMMN) was induced using a standard-deviant reversed oddball paradigm, and differences in automatic detection bias, negative affect, and craving between the two groups were recorded and compared at baseline, day 3, and day 7. The results showed that compared with baseline, vMMN, negative affect and craving were significantly enhanced on day 3 and significantly diminished on day 7 in the abstinence group but not in the control group, and the changes in vMMN were significantly correlated with changes in negative affect and craving in both groups. This study demonstrates that abstinence can restore automatic detection bias in individuals with IGD and that abstinence has to last for 7 days to have a significant effect, while recovery may be related to the negative affect and craving.

Inadequate reporting of adjudicators in open-label trials of anticancer drugs between 2017 and 2021: a methodological review.

OBJECTIVES: In open-label trials, the details of the adjudicators are essential to evaluate the risk of detection bias. We aimed to describe how the adjudicators of progression-free survival (PFS) and objective response rate (ORR) have been reported in open-label trials of anticancer drugs. STUDY DESIGN AND SETTING: A literature search was conducted using MEDLINE via PubMed. We included open-label, parallel-group superiority randomized trials that investigated the PFS and ORR of anticancer drugs for solid tumors. After screening based on the titles and abstracts, 200 articles were randomly selected from 2017 to 2021. The researchers independently checked the eligibility and collected the adjudicators' information in the protocol, registry, and original article. RESULTS: One hundred fifty five studies reported the PFS and ORR. Approximately half of the studies did not report adjudicators (47.7% in PFS and 47.6% in ORR) in the published articles. The inconsistency between the protocol/registry and the published article was 31.0% for PFS and 33.5% for ORR. The prespecified outcomes were not reported in 5.2% of the studies evaluating PFS and 4.5% evaluating ORR. CONCLUSION: This methodological review found that adjudicators were poorly and inconsistently reported between the protocol/registry and the final publication in open-label trials of anticancer drugs.

A Latent Disease Model to Reduce Detection Bias in Cancer Risk Prediction Studies.

In studies of cancer risk, detection bias arises when risk factors are associated with screening patterns, affecting the likelihood and timing of diagnosis. To eliminate detection bias in a screened cohort, we propose modeling the latent onset of cancer and estimating the association between risk factors and onset rather than diagnosis. We apply this framework to estimate the increase in prostate cancer risk associated with black race and family history using data from the SELECT prostate cancer prevention trial, in which men were screened and biopsied according to community practices. A positive family history was associated with a hazard ratio (HR) of prostate cancer onset of 1.8, lower than the corresponding HR of prostate cancer diagnosis (HR = 2.2). This result comports with a finding that men in SELECT with a family history were more likely to be biopsied following a positive PSA test than men with no family history. For black race, the HRs for onset and diagnosis were similar, consistent with similar patterns of screening and biopsy by race. If individual screening and diagnosis histories are available, latent disease modeling can be used to decouple risk of disease from risk of disease diagnosis and reduce detection bias.

Tuberculosis-associated depression: a population-based cohort study of people immigrating to British Columbia, Canada, 1985-2015.

PURPOSE: To estimate the risk of tuberculosis (TB)-associated depression. A second aim was to estimate the extent to which any increased risk of depression among TB patients may be mediated by the length of hospital length stay (LOS) METHODS: Retrospective cohort study of linked healthcare claims and public health surveillance data. Our primary outcome, time-to-depression, was analyzed using Cox proportional hazards (PH) regressions. Causal mediation analysis was used to estimate the natural direct and indirect effect of TB mediated by hospital LOS. RESULTS: Among 755,836 participants (52.2% female, median age=35 years, median follow-up=8.75 years), 2295 were diagnosed with TB (exposure), and 128,963 were diagnosed with depression (outcome). We observed a covariate-adjusted hazard ratio (aHR) of 1.24 (95% CI, 1.14-1.34) for depression by TB. The total effect of TB on depression was decomposed into a natural direct effect of TB of aHR=1.11 (95% CI, 1.02-1.21) and an indirect effect through hospital LOS of aHR=1.11 (95% CI, 1.10-1.12), indicating that TB's total effect was mediated by 50% (95% CI, 35-82%) through hospital LOS. CONCLUSIONS: TB patients had a 24% higher risk of developing depression. TB's effect was mediated substantially by hospital LOS, requiring further study. Depression screening among TB patients is warranted.