Characteristics and outcomes of COVID-19 patients with and without asthma from the United States, South Korea, and Europe.

Objective: Large international comparisons describing the clinical characteristics of patients with COVID-19 are limited. The aim of the study was to perform a large-scale descriptive characterization of COVID-19 patients with asthma.Methods: We included nine databases contributing data from January to June 2020 from the US, South Korea (KR), Spain, UK and the Netherlands. We defined two cohorts of COVID-19 patients ('diagnosed' and 'hospitalized') based on COVID-19 disease codes. We followed patients from COVID-19 index date to 30 days or death. We performed descriptive analysis and reported the frequency of characteristics and outcomes in people with asthma defined by codes and prescriptions.Results: The diagnosed and hospitalized cohorts contained 666,933 and 159,552 COVID-19 patients respectively. Exacerbation in people with asthma was recorded in 1.6-8.6% of patients at presentation. Asthma prevalence ranged from 6.2% (95% CI 5.7-6.8) to 18.5% (95% CI 18.2-18.8) in the diagnosed cohort and 5.2% (95% CI 4.0-6.8) to 20.5% (95% CI 18.6-22.6) in the hospitalized cohort. Asthma patients with COVID-19 had high prevalence of comorbidity including hypertension, heart disease, diabetes and obesity. Mortality ranged from 2.1% (95% CI 1.8-2.4) to 16.9% (95% CI 13.8-20.5) and similar or lower compared to COVID-19 patients without asthma. Acute respiratory distress syndrome occurred in 15-30% of hospitalized COVID-19 asthma patients.Conclusion: The prevalence of asthma among COVID-19 patients varies internationally. Asthma patients with COVID-19 have high comorbidity. The prevalence of asthma exacerbation at presentation was low. Whilst mortality was similar among COVID-19 patients with and without asthma, this could be confounded by differences in clinical characteristics. Further research could help identify high-risk asthma patients.[Box: see text]Supplemental data for this article is available online at https://doi.org/10.1080/02770903.2021.2025392 .

Characteristics and outcomes of 627 044 COVID-19 patients living with and without obesity in the United States, Spain, and the United Kingdom.

BACKGROUND: A detailed characterization of patients with COVID-19 living with obesity has not yet been undertaken. We aimed to describe and compare the demographics, medical conditions, and outcomes of COVID-19 patients living with obesity (PLWO) to those of patients living without obesity. METHODS: We conducted a cohort study based on outpatient/inpatient care and claims data from January to June 2020 from Spain, the UK, and the US. We used six databases standardized to the OMOP common data model. We defined two non-mutually exclusive cohorts of patients diagnosed and/or hospitalized with COVID-19; patients were followed from index date to 30 days or death. We report the frequency of demographics, prior medical conditions, and 30-days outcomes (hospitalization, events, and death) by obesity status. RESULTS: We included 627 044 (Spain: 122 058, UK: 2336, and US: 502 650) diagnosed and 160 013 (Spain: 18 197, US: 141 816) hospitalized patients with COVID-19. The prevalence of obesity was higher among patients hospitalized (39.9%, 95%CI: 39.8-40.0) than among those diagnosed with COVID-19 (33.1%; 95%CI: 33.0-33.2). In both cohorts, PLWO were more often female. Hospitalized PLWO were younger than patients without obesity. Overall, COVID-19 PLWO were more likely to have prior medical conditions, present with cardiovascular and respiratory events during hospitalization, or require intensive services compared to COVID-19 patients without obesity. CONCLUSION: We show that PLWO differ from patients without obesity in a wide range of medical conditions and present with more severe forms of COVID-19, with higher hospitalization rates and intensive services requirements. These findings can help guiding preventive strategies of COVID-19 infection and complications and generating hypotheses for causal inference studies.

COVID-19 in patients with autoimmune diseases: characteristics and outcomes in a multinational network of cohorts across three countries.

OBJECTIVE: Patients with autoimmune diseases were advised to shield to avoid coronavirus disease 2019 (COVID-19), but information on their prognosis is lacking. We characterized 30-day outcomes and mortality after hospitalization with COVID-19 among patients with prevalent autoimmune diseases, and compared outcomes after hospital admissions among similar patients with seasonal influenza. METHODS: A multinational network cohort study was conducted using electronic health records data from Columbia University Irving Medical Center [USA, Optum (USA), Department of Veterans Affairs (USA), Information System for Research in Primary Care-Hospitalization Linked Data (Spain) and claims data from IQVIA Open Claims (USA) and Health Insurance and Review Assessment (South Korea). All patients with prevalent autoimmune diseases, diagnosed and/or hospitalized between January and June 2020 with COVID-19, and similar patients hospitalized with influenza in 2017-18 were included. Outcomes were death and complications within 30 days of hospitalization. RESULTS: We studied 133 589 patients diagnosed and 48 418 hospitalized with COVID-19 with prevalent autoimmune diseases. Most patients were female, aged ≥50 years with previous comorbidities. The prevalence of hypertension (45.5-93.2%), chronic kidney disease (14.0-52.7%) and heart disease (29.0-83.8%) was higher in hospitalized vs diagnosed patients with COVID-19. Compared with 70 660 hospitalized with influenza, those admitted with COVID-19 had more respiratory complications including pneumonia and acute respiratory distress syndrome, and higher 30-day mortality (2.2-4.3% vs 6.32-24.6%). CONCLUSION: Compared with influenza, COVID-19 is a more severe disease, leading to more complications and higher mortality.

Estimation of adverse drug reaction reporting in Iran: Correction for underreporting.

PROPOSE: Underreporting of Adverse Drug Reactions (ADRs) reduces the sensitivity of pharmacovigilance systems. We described ADR reporting and its trend from 1999 to 2017 and estimated the ADR underreporting in the Iranian Pharmacovigilance Center. METHODS: We expressed the number of ADR reporting per inhabitants and admissions and their possible trends. Finally, ADR underreporting percentages were estimated by three approaches: prospective studies, literature review, stratification of the country; and the trend of the proportion of ADR per inhabitants was corrected. RESULTS: The proportion of ADR reporting was 15.3 per 100 000 inhabitants (95% CI: 15.2, 15.8) and 10.0 per 100 000 admissions (95% CI: 9.8, 10.2) in 2017, and its trend was increasing with 16.3% average change per annum during 19 years. The median of estimated percentages of underreporting was 76.0% (IQR: 64.32-81.35). After the correction, the mean proportion of ADR reporting for 19 years reached from 5.87 to 10.33 per 100 000 inhabitants. CONCLUSIONS: The trend of ADRs reporting has been increasing over the 19 years but is still low. This study showed a considerable underreporting of ADR, and about one of four detected ADRs were reported to the pharmacovigilance center from 1999 to 2017.

Fasting Versus Nonfasting and Low-Density Lipoprotein Cholesterol Accuracy.

BACKGROUND: Recent recommendations favoring nonfasting lipid assessment may affect low-density lipoprotein cholesterol (LDL-C) estimation. The novel method of LDL-C estimation (LDL-CN) uses a flexible approach to derive patient-specific ratios of triglycerides to very low-density lipoprotein cholesterol. This adaptability may confer an accuracy advantage in nonfasting patients over the fixed approach of the classic Friedewald method (LDL-CF). METHODS: We used a US cross-sectional sample of 1 545 634 patients (959 153 fasting ≥10-12 hours; 586 481 nonfasting) from the second harvest of the Very Large Database of Lipids study to assess for the first time the impact of fasting status on novel LDL-C accuracy. Rapid ultracentrifugation was used to directly measure LDL-C content (LDL-CD). Accuracy was defined as the percentage of LDL-CD falling within an estimated LDL-C (LDL-CN or LDL-CF) category by clinical cut points. For low estimated LDL-C (<70 mg/dL), we evaluated accuracy by triglyceride levels. The magnitude of absolute and percent differences between LDL-CD and estimated LDL-C (LDL-CN or LDL-CF) was stratified by LDL-C and triglyceride categories. RESULTS: In both fasting and nonfasting samples, accuracy was higher with the novel method across all clinical LDL-C categories (range, 87%-94%) compared with the Friedewald estimation (range, 71%-93%; P≤0.001). With LDL-C <70 mg/dL, nonfasting LDL-CN accuracy (92%) was superior to LDL-CF accuracy (71%; P<0.001). In this LDL-C range, 19% of fasting and 30% of nonfasting patients had differences ≥10 mg/dL between LDL-CF and LDL-CD, whereas only 2% and 3% of patients, respectively, had similar differences with novel estimation. Accuracy of LDL-C <70 mg/dL further decreased as triglycerides increased, particularly for Friedewald estimation (range, 37%-96%) versus the novel method (range, 82%-94%). With triglycerides of 200 to 399 mg/dL in nonfasting patients, LDL-CN <70 mg/dL accuracy (82%) was superior to LDL-CF (37%; P<0.001). In this triglyceride range, 73% of fasting and 81% of nonfasting patients had ≥10 mg/dL differences between LDL-CF and LDL-CD compared with 25% and 20% of patients, respectively, with LDL-CN. CONCLUSIONS: Novel adaptable LDL-C estimation performs better in nonfasting samples than the fixed Friedewald estimation, with a particular accuracy advantage in settings of low LDL-C and high triglycerides. In addition to stimulating further study, these results may have immediate relevance for guideline committees, laboratory leadership, clinicians, and patients. CLINICAL TRIAL REGISTRATION: URL: https://www.clinicaltrials.gov. Unique identifier: NCT01698489.

RE: "An Estimation of the Risk of Pseudotumor Cerebri Among Users of the Levonorgestrel Intrauterine Device".

The current letter to the editor describes some of the limitations of Valenzuela et al.'s study on the association between levonorgestrel-releasing intrauterine system use and pseudotumor cerebri/idiopathic intracranial hypertension and further reinforces the authors' interpretations of the findings.

White rice intake and incidence of type-2 diabetes: analysis of two prospective cohort studies from Iran.

BACKGROUND: Refined grains and white rice have been associated with elevated risk of type 2 diabetes mellitus (T2DM). In this study, we sought to quantify the effect of white rice intake on incident T2DM in two prospective population-based cohort studies from Iran, where white rice is one of the main staple. METHODS: We used follow-up data from 9,182 participants from Golestan Cohort Study (GCS, 2004-2007, conducted mainly in rural areas) and 2,173 from Tehran Lipid and Glucose Study (TLGS, 2004-2006) who did not have T2DM and other chronic diseases at baseline. Diet was assessed using validated food frequency questionnaires. Multivariable logistic regression models were used to estimate adjusted odds ratios (ORs) for incident T2DM. RESULTS: We documented 902 new cases of T2DM in GCS and 81 in TLGS. Age-standardized cumulative incidence of T2DM was 9.9% in Golestan and 8.0% in Tehran. Daily white rice intake was significantly higher among residents of Tehran compared to Golestan (median daily intake: 250 vs. 120 grams; P-value < 0.001). After adjustment for potential confounders, there was no significant association between daily white rice intake and incident T2DM in GCS. In TLGS, the adjusted OR (95% confidence interval (CI)) was 2.1 (1.1, 3.9) comparing participants with daily white rice intake of >250 grams/day to those with <250. CONCLUSIONS: We observed an increased lieklihood of T2DM associated with high white rice intake among residents of Tehran and no association in Golestan. Our findings, if further supported by other studies, have important public health implications especially for countries where white rice is a major staple and diabetes is increasing rapidly incidence is high. Further research is needed to investigate lack of an association between lower levels of white rice intake and T2DM.

Does Metformin Reduce Cancer Risks? Methodologic Considerations.

The substantial burden of cancer and diabetes and the association between the two conditions has been a motivation for researchers to look for targeted strategies that can simultaneously affect both diseases and reduce their overlapping burden. In the absence of randomized clinical trials, researchers have taken advantage of the availability and richness of administrative databases and electronic medical records to investigate the effects of drugs on cancer risk among diabetic individuals. The majority of these studies suggest that metformin could potentially reduce cancer risk. However, the validity of this purported reduction in cancer risk is limited by several methodological flaws either in the study design or in the analysis. Whether metformin use decreases cancer risk relies heavily on the availability of valid data sources with complete information on confounders, accurate assessment of drug use, appropriate study design, and robust analytical techniques. The majority of the observational studies assessing the association between metformin and cancer risk suffer from methodological shortcomings and efforts to address these issues have been incomplete. Future investigations on the association between metformin and cancer risk should clearly address the methodological issues due to confounding by indication, prevalent user bias, and time-related biases. Although the proposed strategies do not guarantee a bias-free estimate for the association between metformin and cancer, they will reduce synthesis of and reporting of erroneous results.

A framework for understanding an open scientific community using automated harvesting of public artifacts.

Background: The Observational Health Data Sciences and Informatics (OHDSI) community has emerged as a leader in observational research on real-world clinical data for promoting evidence for healthcare and decision-making. The community has seen rapid growth in publications, citations, and the number of authors. Components of its successful uptake have been attributed to an open science and collaborative culture for research and development. Investigating the adoption of OHDSI as a field of study provides an opportunity to understand how communities embrace new ideas, onboard new members, and enhance their impact. Objective: To track, study, and evaluate an open scientific community's growth and impact. Method: We present a modern architecture leveraging open application programming interfaces to capture publicly available data (PubMed, YouTube, and EHDEN) on open science activities (publication, teaching, and engagement). Results: Three interactive dashboard were implemented for each publicly available artifact (PubMed, YouTube, and EHDEN). Each dashboard provides longitudinal summary analysis and has a searchable table, which differs in the available features related to each public artifact. Conclusion: We discuss the insights enabled by our approach to monitor the growth and impact of the OHDSI community by capturing artifacts of learning, teaching, and creation. We share the implications for different users based on their functional needs. As other scientific networks adopt open-source frameworks, our framework serves as a model for tracking the growth of their community, driving the perception of their development, engaging their members, and attaining higher impact.

Research protocol for an observational health data analysis to assess the applicability of randomized controlled trials focusing on newly diagnosed metastatic prostate cancer using real-world data: PIONEER IMI's "big data for better outcomes" program.

Background: Metastatic prostate cancer (PCa) constitutes ~5% of all new PCa diagnoses in Western countries. For most cases, primary consideration should be given to systemic therapies as the first-line approach based on evidence from randomized controlled trials (RCTs). Despite the importance of RCTs as the pinnacle of evidence in modern medicine, concerns have been raised about their applicability to real-life scenarios. These trials often feature participants who are younger with better performance statuses and prognoses compared to their real-world counterparts. The PIONEER project falls under the Innovative Medicine Initiative's (IMI) "Big Data for Better Outcomes" initiative, aimed at revolutionizing PCa care in Europe. The central focus lies in improving cancer-related outcomes, enhancing health system efficiency, and elevating the quality of health and social care. This study endeavours to evaluate the generalizability of RCT findings concerning newly diagnosed metastatic PCa. Methods: A systematic review of the literature will be conducted to compile patient characteristics from RCTs addressing this subject within the past decade. To create a real-world benchmark, patients with recently diagnosed metastatic PCa from a network of population-based databases will serve as a comparison group. The objective is to assess the applicability of RCT results in two ways. First, a comparison will be made between the characteristics of patients with newly diagnosed metastatic PCa enroled in RCTs and those with the same condition included in our databases which might represent the real-world setting. Second, an evaluation will be undertaken to determine the proportion of real-world patients with newly diagnosed metastatic PCa who meet the criteria for RCT enrolment. This study will rely on extensive observational data, primarily sourced from population-based registries, electronic health records, and insurance claims data. The study cohort is established upon routinely gathered healthcare data, meticulously mapped to the Observational Medical Outcomes Partnership Common Data Model.

The Impact of the COVID-19 Pandemic on Incidence and Short-Term Survival for Common Solid Tumours in the United Kingdom: A Cohort Analysis.

Purpose: The COVID-19 pandemic profoundly affected healthcare systems and patients. There is a need to comprehend the collateral effects of the pandemic on non-communicable diseases. We examined the impact of the pandemic on short-term survival for common solid tumours, including breast, colorectal, head and neck, liver, lung, oesophageal, pancreatic, prostate, and stomach cancer in the UK. Methods: This was a population-based cohort study of electronic health records from the UK primary care Clinical Practice Research Datalink GOLD database. In sum, 12,259,744 eligible patients aged ≥18 years with ≥1 year's history identified from January 2000 to December 2022 were included. We estimated age-standardised incidence and short-term (one- and two-year) survival for several common cancers from 2000 to 2019 (in five-year strata) and compared these to 2020-2022 using the Kaplan-Meier method. Results: Incidence decreased for most cancers in 2020 and recovered to different extents in 2021-2022. Short-term survival improved for most cancers between 2000 and 2019, but then declined, albeit minimally, for those diagnosed in 2020-2022. This was most pronounced for colorectal cancer, with one-year survival falling from 78.8% (95% CI 78%-79.6%) in 2015-2019 to 77% (95% CI 75.6-78.3%) for those diagnosed in 2020-2022. Conclusion: Short-term survival for many cancers was impacted, albeit minimally, by the pandemic in the UK, with reductions in survivorship from colorectal cancer equivalent to returning to the mortality seen in the first decade of the 2000s. While data on longer-term survival are needed to fully comprehend the impact of COVID-19 on cancer care, our findings illustrate the need for an urgent and substantial commitment from the UK National Health Service to address the existing backlog in cancer screening and diagnostic procedures to improve cancer care and mortality.

Predictive Models for Assessing Patients' Response to Treatment in Metastatic Prostate Cancer: A Systematic Review.

Background and objective: The treatment landscape of metastatic prostate cancer (mPCa) has evolved significantly over the past two decades. Despite this, the optimal therapy for patients with mPCa has not been determined. This systematic review identifies available predictive models that assess mPCa patients' response to treatment. Methods: We critically reviewed MEDLINE and CENTRAL in December 2022 according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses statement. Only quantitative studies in English were included with no time restrictions. The quality of the included studies was assessed using the PROBAST tool. Data were extracted following the Checklist for Critical Appraisal and Data Extraction for Systematic Reviews criteria. Key findings and limitations: The search identified 616 citations, of which 15 studies were included in our review. Nine of the included studies were validated internally or externally. Only one study had a low risk of bias and a low risk concerning applicability. Many studies failed to detail model performance adequately, resulting in a high risk of bias. Where reported, the models indicated good or excellent performance. Conclusions and clinical implications: Most of the identified predictive models require additional evaluation and validation in properly designed studies before these can be implemented in clinical practice to assist with treatment decision-making for men with mPCa. Patient summary: In this review, we evaluate studies that predict which treatments will work best for which metastatic prostate cancer patients. We found that existing studies need further improvement before these can be used by health care professionals.

Research Protocol for an Observational Health Data Analysis on the Adverse Events of Systemic Treatment in Patients with Metastatic Hormone-sensitive Prostate Cancer: Big Data Analytics Using the PIONEER Platform.

Combination therapies in metastatic hormone-sensitive prostate cancer (mHSPC), which include the addition of an androgen receptor signaling inhibitor and/or docetaxel to androgen deprivation therapy, have been a game changer in the management of this disease stage. However, these therapies come with their fair share of toxicities and side effects. The goal of this observational study is to report drug-related adverse events (AEs), which are correlated with systemic combination therapies for mHSPC. Determining the optimal treatment option requires large cohorts to estimate the tolerability and AEs of these combination therapies in "real-life" patients with mHSPC, as provided in this study. We use a network of databases that includes population-based registries, electronic health records, and insurance claims, containing the overall target population and subgroups of patients defined by unique certain characteristics, demographics, and comorbidities, to compute the incidence of common AEs associated with systemic therapies in the setting of mHSPC. These data sources are standardised using the Observational Medical Outcomes Partnership Common Data Model. We perform the descriptive statistics as well as calculate the AE incidence rate separately for each treatment group, stratified by age groups and index year. The time until the first event is estimated using the Kaplan-Meier method within each age group. In the case of episodic events, the anticipated mean cumulative counts of events are calculated. Our study will allow clinicians to tailor optimal therapies for mHSPC patients, and they will serve as a basis for comparative method studies.

Similar Risk of Kidney Failure among Patients with Blinding Diseases Who Receive Ranibizumab, Aflibercept, and Bevacizumab: An Observational Health Data Sciences and Informatics Network Study.

PURPOSE: To characterize the incidence of kidney failure associated with intravitreal anti-VEGF exposure; and compare the risk of kidney failure in patients treated with ranibizumab, aflibercept, or bevacizumab. DESIGN: Retrospective cohort study across 12 databases in the Observational Health Data Sciences and Informatics (OHDSI) network. SUBJECTS: Subjects aged ≥ 18 years with ≥ 3 monthly intravitreal anti-VEGF medications for a blinding disease (diabetic retinopathy, diabetic macular edema, exudative age-related macular degeneration, or retinal vein occlusion). METHODS: The standardized incidence proportions and rates of kidney failure while on treatment with anti-VEGF were calculated. For each comparison (e.g., aflibercept versus ranibizumab), patients from each group were matched 1:1 using propensity scores. Cox proportional hazards models were used to estimate the risk of kidney failure while on treatment. A random effects meta-analysis was performed to combine each database's hazard ratio (HR) estimate into a single network-wide estimate. MAIN OUTCOME MEASURES: Incidence of kidney failure while on anti-VEGF treatment, and time from cohort entry to kidney failure. RESULTS: Of the 6.1 million patients with blinding diseases, 37 189 who received ranibizumab, 39 447 aflibercept, and 163 611 bevacizumab were included; the total treatment exposure time was 161 724 person-years. The average standardized incidence proportion of kidney failure was 678 per 100 000 persons (range, 0-2389), and incidence rate 742 per 100 000 person-years (range, 0-2661). The meta-analysis HR of kidney failure comparing aflibercept with ranibizumab was 1.01 (95% confidence interval [CI], 0.70-1.47; P = 0.45), ranibizumab with bevacizumab 0.95 (95% CI, 0.68-1.32; P = 0.62), and aflibercept with bevacizumab 0.95 (95% CI, 0.65-1.39; P = 0.60). CONCLUSIONS: There was no substantially different relative risk of kidney failure between those who received ranibizumab, bevacizumab, or aflibercept. Practicing ophthalmologists and nephrologists should be aware of the risk of kidney failure among patients receiving intravitreal anti-VEGF medications and that there is little empirical evidence to preferentially choose among the specific intravitreal anti-VEGF agents. FINANCIAL DISCLOSURES: Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Clinical Characterization of Patients Diagnosed with Prostate Cancer and Undergoing Conservative Management: A PIONEER Analysis Based on Big Data.

BACKGROUND: Conservative management is an option for prostate cancer (PCa) patients either with the objective of delaying or even avoiding curative therapy, or to wait until palliative treatment is needed. PIONEER, funded by the European Commission Innovative Medicines Initiative, aims at improving PCa care across Europe through the application of big data analytics. OBJECTIVE: To describe the clinical characteristics and long-term outcomes of PCa patients on conservative management by using an international large network of real-world data. DESIGN, SETTING, AND PARTICIPANTS: From an initial cohort of >100 000 000 adult individuals included in eight databases evaluated during a virtual study-a-thon hosted by PIONEER, we identified newly diagnosed PCa cases (n = 527 311). Among those, we selected patients who did not receive curative or palliative treatment within 6 mo from diagnosis (n = 123 146). OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Patient and disease characteristics were reported. The number of patients who experienced the main study outcomes was quantified for each stratum and the overall cohort. Kaplan-Meier analyses were used to estimate the distribution of time to event data. RESULTS AND LIMITATIONS: The most common comorbidities were hypertension (35-73%), obesity (9.2-54%), and type 2 diabetes (11-28%). The rate of PCa-related symptomatic progression ranged between 2.6% and 6.2%. Hospitalization (12-25%) and emergency department visits (10-14%) were common events during the 1st year of follow-up. The probability of being free from both palliative and curative treatments decreased during follow-up. Limitations include a lack of information on patients and disease characteristics and on treatment intent. CONCLUSIONS: Our results allow us to better understand the current landscape of patients with PCa managed with conservative treatment. PIONEER offers a unique opportunity to characterize the baseline features and outcomes of PCa patients managed conservatively using real-world data. PATIENT SUMMARY: Up to 25% of men with prostate cancer (PCa) managed conservatively experienced hospitalization and emergency department visits within the 1st year after diagnosis; 6% experienced PCa-related symptoms. The probability of receiving therapies for PCa decreased according to time elapsed after the diagnosis.

Genetic variants in sex hormone metabolic pathway genes and risk of esophageal squamous cell carcinoma.

In China, esophageal cancer is the fourth leading cause of cancer death where essentially all cases are histologically esophageal squamous cell carcinoma (ESCC), in contrast to esophageal adenocarcinoma in the West. Globally, ESCC is 2.4 times more common among men than women and recently it has been suggested that sex hormones may be associated with the risk of ESCC. We examined the association between genetic variants in sex hormone metabolic genes and ESCC risk in a population from north central China with high-incidence rates. A total of 1026 ESCC cases and 1452 controls were genotyped for 797 unique tag single-nucleotide polymorphisms (SNPs) in 51 sex hormone metabolic genes. SNP-, gene- and pathway-based associations with ESCC risk were evaluated using unconditional logistic regression adjusted for age, sex and geographical location and the adaptive rank truncated product (ARTP) method. Statistical significance was determined through use of permutation for pathway- and gene-based associations. No associations were observed for the overall sex hormone metabolic pathway (P = 0.14) or subpathways (androgen synthesis: P = 0.30, estrogen synthesis: P = 0.15 and estrogen removal: P = 0.19) with risk of ESCC. However, six individual genes (including SULT2B1, CYP1B1, CYP3A7, CYP3A5, SHBG and CYP11A1) were significantly associated with ESCC risk (P < 0.05). Our examination of genetic variation in the sex hormone metabolic pathway is consistent with a potential association with risk of ESCC. These positive findings warrant further evaluation in relation to ESCC risk and replication in other populations.

Variation in PAH-related DNA adduct levels among non-smokers: the role of multiple genetic polymorphisms and nucleotide excision repair phenotype.

Polycyclic aromatic hydrocarbons (PAHs) likely play a role in many cancers even in never-smokers. We tried to find a model to explain the relationship between variation in PAH-related DNA adduct levels among people with similar exposures, multiple genetic polymorphisms in genes related to metabolic and repair pathways, and nucleotide excision repair (NER) capacity. In 111 randomly selected female never-smokers from the Golestan Cohort Study in Iran, we evaluated 21 SNPs in 14 genes related to xenobiotic metabolism and 12 SNPs in eight DNA repair genes. NER capacity was evaluated by a modified comet assay, and aromatic DNA adduct levels were measured in blood by32P-postlabeling. Multivariable regression models were compared by Akaike's information criterion (AIC). Aromatic DNA adduct levels ranged between 1.7 and 18.6 per 10(8) nucleotides (mean: 5.8 ± 3.1). DNA adduct level was significantly lower in homozygotes for NAT2 slow alleles and ERCC5 non-risk-allele genotype, and was higher in the MPO homozygote risk-allele genotype. The sum of risk alleles in these genes significantly correlated with the log-adduct level (r = 0.4, p < 0.001). Compared with the environmental model, adding Phase I SNPs and NER capacity provided the best fit, and could explain 17% more of the variation in adduct levels. NER capacity was affected by polymorphisms in the MTHFR and ERCC1 genes. Female non-smokers in this population had PAH-related DNA adduct levels three to four times higher than smokers and occupationally-exposed groups in previous studies, with large inter-individual variation which could best be explained by a combination of Phase I genes and NER capacity.

Research protocol to identify progression and death amongst patients with metastatic hormone-sensitive prostate cancer treated with available treatments: PIONEER IMI's "big data for better outcomes" program.

Androgen deprivation therapy-based with or without first-generation anti-androgens, was the standard of care for patients with metastatic hormone-sensitive prostate cancer (mHSPC) for decades. However, the development of docetaxel chemotherapy and new androgen receptor-targeted agents, abiraterone acetate and prednisolone, apalutamide , enzalutamide and darolutamide (in combination with docetaxel chemotherapy) has proven that combination of treatments is more effective. Recently, intensification therapy, so-called "triplets", have emerged in the armamentarium of mHSPC treatment. Metastatic disease is a clinical state that remains poorly understood. The optimal diagnostic and management of patients with mHSPC are changing thanks to the development of new imaging techniques and therapies. The primary objective of this study is to develop and validate a predictive model for the occurrence of symptomatic progression, initiation of new treatments and death amongst patients with mHSPC treated with one of the approved treatment plans, on characteristics present at admission.

Reproducible variability: assessing investigator discordance across 9 research teams attempting to reproduce the same observational study.

OBJECTIVE: Observational studies can impact patient care but must be robust and reproducible. Nonreproducibility is primarily caused by unclear reporting of design choices and analytic procedures. This study aimed to: (1) assess how the study logic described in an observational study could be interpreted by independent researchers and (2) quantify the impact of interpretations' variability on patient characteristics. MATERIALS AND METHODS: Nine teams of highly qualified researchers reproduced a cohort from a study by Albogami et al. The teams were provided the clinical codes and access to the tools to create cohort definitions such that the only variable part was their logic choices. We executed teams' cohort definitions against the database and compared the number of subjects, patient overlap, and patient characteristics. RESULTS: On average, the teams' interpretations fully aligned with the master implementation in 4 out of 10 inclusion criteria with at least 4 deviations per team. Cohorts' size varied from one-third of the master cohort size to 10 times the cohort size (2159-63 619 subjects compared to 6196 subjects). Median agreement was 9.4% (interquartile range 15.3-16.2%). The teams' cohorts significantly differed from the master implementation by at least 2 baseline characteristics, and most of the teams differed by at least 5. CONCLUSIONS: Independent research teams attempting to reproduce the study based on its free-text description alone produce different implementations that vary in the population size and composition. Sharing analytical code supported by a common data model and open-source tools allows reproducing a study unambiguously thereby preserving initial design choices.

Significant variation in the concentration of carcinogenic polycyclic aromatic hydrocarbons in yerba maté samples by brand, batch, and processing method.

Drinking maté, common in southern South America, may increase the risk of esophageal squamous cell carcinoma (ESCC). In 2006, we found high but variable polycyclic aromatic hydrocarbon (PAH) content in commercial yerba maté samples from eight Brazilian brands. The PAH content of new samples from the same brands, purchased in 2008, and four brands from a single manufacturer processed in different ways, obtained in 2010, were quantified to determine whether PAH concentration was still high, whether PAH content variation was brand specific, and whether processing method affects PAH content of commercial yerba maté. Concentrations of individual PAHs were quantified using gas chromatography/mass spectrometry with deuterated PAHs as internal standards. Median total PAH concentration was 1500 ng/g (range: 625-3710 ng/g) and 1090 ng/g (621-1990 ng/g) in 2008 and 2010 samples, respectively. Comparing 2006 and 2008 samples, some brands had high PAH concentrations in both years, while PAH concentration changed considerably in others. Benzo[a]pyrene concentrations ranged from 11.9 to 99.3 ng/g and 5.11 to 21.0 ng/g in 2008 and 2010 samples, respectively. The 2010 sample processed without touching smoke had the lowest benzo[a]pyrene content. These results support previous findings of very high total and carcinogenic PAH concentrations in yerba maté, perhaps contributing to the high incidence of ESCC in southern South America. The large PAH content variation by brand, batch, and processing method suggests it may be possible to reduce the content of carcinogenic PAHs in commercial yerba maté, making it a healthier beverage.