Search

The influence of socioeconomic status (SES) on access to standard chemotherapy and/or monoclonal antibody therapy, and associated secular trends, relative survival, and excess mortality, among diffuse large B-cell lymphoma (DLBCL) patients is not clear. We conducted a Hong Kong population-based cohort study and identified adult patients with histologically diagnosed DLBCL between 2000 and 2018. We examined the association of SES levels with the odds and the secular trends of receipt of chemotherapy and/or rituximab. Additionally, we estimated the long-term relative survival by SES utilizing Hong Kong life tables. Among 4017 patients with DLBCL, 2363 (58.8%) patients received both chemotherapy and rituximab and 740 (18.4%) patients received chemotherapy alone, while 1612 (40.1%) and 914 (22.8%) patients received no rituximab or chemotherapy, respectively. On multivariable analysis, low SES was associated with lesser use of chemotherapy (odd ratio [OR] 0.44; 95% CI 0.34–0.57) and rituximab (OR 0.41; 95% CI 0.32–0.52). The socioeconomic disparity for either treatment showed no secular trend of change. Additionally, patients with low SES showed increased excess mortality, with a hazard ratio of 2.34 (95% CI 1.67–3.28). Improving survival outcomes for patients with DLBCL requires provision of best available medical care and securing access to treatment regardless of patients’ SES.

The management regarding metastatic colorectal cancer throughout Europe is not well known.To draw a European comparison of the management and prognosis of metastatic colorectal cancers.Factors associated with chemotherapy administration were identified through logistic regressions. Net survival was estimated and crude probabilities of death related to cancer and other causes using a flexible cumulative hazard model.Among the 13 227 patients with colorectal cancer diagnosed between 2010 and 2013 in cancer registries from 10 European countries, 3140 were metastatic. 62% of metastatic patients received chemotherapy. Compared to Spain, the related adjusted odds ratios ranged from 0.7 to 4.0 (P0.001) according to country. The 3-year net survival by country ranged between 16% and 37%. The survival gap between countries diminished from 21% to 10% when adjusting for chemotherapy, age and sex. Geographical differences in the crude probability of death related to cancer were large for patients70 or ≥80 years at diagnosis.Heterogeneity in the application of European guidelines partly explain these differences. General health between populations, accessibility to a reference centre, or provision of health care could also be involved. Further population-based studies are warranted to disentangle between these possible explanations.

Aim Even though most pregnancies are uneventful, occasionally complications do occur. Gestational diabetes is linked to an increased risk of adverse pregnancy outcomes. Early identification of women at risk of experiencing adverse outcomes, ideally through a single blood test, would facilitate early intervention. Plasma glycated CD59 (pGCD59) is an emerging biomarker which has shown promise in identifying hyperglycaemia during pregnancy and has been associated with the risk of delivering an LGA infant. The aim of this study was to explore the ability of the first- and second-trimester pGCD59 to predict adverse pregnancy outcomes. Methods This was a prospective study of 378 pregnant women. Samples for pGCD59 were taken at the first antenatal visit and at the time of the 2 h 75 g OGTT (24–28 weeks of gestation). Adjusted receiver operating characteristic curves were used to evaluate the ability of pGCD59 to predict maternal and neonatal outcomes. Results First-trimester pGCD59 levels were higher in women with gestational diabetes who delivered a macrosomic infant (4.2 ± 0.7 vs. 3.5 ± 1.0 SPU, p p = 0.01) compared to women with GDM that did not experience these outcomes. Second-trimester pGCD59 levels were higher in women that developed polyhydramnios (2.9 ± 0.4 vs. 2.5 ± 1.1 SPU, p = 0.03). First- and second-trimester pGCD59 predicted pregnancy-induced hypertension with good accuracy (AUC:0.85, 95%CI:0.78–0.91; AUC: 0.80, 95%CI: 0.73–0.88, respectively) and neonatal hypoglycaemia with fair to good accuracy (AUC:0.77, 95%CI: 0.54–0.99, AUC:0.81, 95%CI:0.62–0.99). Conclusions This study has shown that pGCD59 has the potential to predict adverse pregnancy outcomes. Prospective studies with a larger number of cases are necessary to fully explore and validate the potential of this emerging biomarker in predicting adverse pregnancy outcomes.

The aim of this study was to evaluate the ability of second trimester plasma glycated CD59 (pGCD59), a novel biomarker, to predict the results of the 2 h 75 g oral glucose tolerance test at 24-28 weeks of gestation, employing the 2013 World Health Organisation criteria. This was a prospective study of 378 pregnant women. The ability of pGCD59 to predict gestational diabetes (GDM) was assessed using adjusted ROC curves for maternal age, BMI, maternal ethnicity, parity, previous GDM, and family history of diabetes. The pGCD59 levels were significantly higher in women with GDM compared to women with normal glucose tolerance (p = 0.003). The pGCD59 generated an adjusted AUC for identifying GDM cases of 0.65 (95%CI: 0.58-0.71, p < 0.001). The pGCD59 predicted GDM status diagnosed by a fasting glucose value of 5.1 mmol/L with an adjusted AUC of 0.74 (95%CI: 0.65-0.81, p < 0.001). Analysis of BMI subgroups determined that pGCD59 generated the highest AUC in the 35 kg/m2 ≤ BMI < 40 kg/m2 (AUC: 0.84 95%CI: 0.69-0.98) and BMI ≥ 40 kg/m2 (AUC: 0.96 95%CI: 0.86-0.99) categories. This study found that second trimester pGCD59 is a fair predictor of GDM status diagnosed by elevated fasting glucose independent of BMI and an excellent predictor of GDM in subjects with a very high BMI.

Miguel Angel Luque-Fernandez is supported by a Miguel Servet I Investigator award (Grant CP17/00206) and a project grant EU-FEDER-FIS PI-18/01593 from the Instituto de Salud Carlos III, Madrid, Spain. Danilo Alvares is supported by the National Fund for Scientific and Technological Development (FONDECYT, Chile) grant number 11190018., Cancer survival represents one of the main indicators of interest in cancer epidemiology. However, the survival of cancer patients can be affected by several factors, such as comorbidities, that may interact with the cancer biology. Moreover, it is interesting to understand how different cancer sites and tumour stages are affected by different comorbidities. Identifying the comorbidities that affect cancer survival is thus of interest as it can be used to identify factors driving the survival of cancer patients. This information can also be used to identify vulnerable groups of patients with comorbidities that may lead to worst prognosis of cancer. We address these questions and propose a principled selection and evaluation of the effect of comorbidities on the overall survival of cancer patients. In the first step, we apply a Bayesian variable selection method that can be used to identify the comorbidities that predict overall survival. In the second step, we build a general Bayesian survival model that accounts for time-varying effects. In the third step, we derive several posterior predictive measures to quantify the effect of individual comorbidities on the population overall survival. We present applications to data on lung and colorectal cancers from two Spanish population-based cancer registries. The proposed methodology is implemented with a combination of the R-packages mombf and rstan. We provide the code for reproducibility at https://github.com/migariane/ BayesVarImpComorbiCancer., Miguel Servet I Investigator award CP17/00206 EU-FEDER-FIS PI-18/01593, Instituto de Salud Carlos III, Comision Nacional de Investigacion Cientifica y Tecnologica (CONICYT) CONICYT FONDECYT 11190018

Background Colorectal cancer (CRC) is the most frequently diagnosed cancer in Spain. Socioeconomic inequalities in cancer survival are not documented in Spain. We aim to study the association of socioeconomic inequalities with overall mortality and survival among CRC patients in southern Spain. Methods We conducted a multilevel population-based cohort study, including CRC cases for the period 2011-2013. The study time-to-event outcome was death, and the primary exposure was CRC patients' socioeconomic status assessed by the Spanish deprivation index at the census tract level. We used a mixed-effects flexible hazard model, including census tract as a random intercept, to derive overall survival estimates by deprivation. Results Among 3589 CRC patients and 12,148 person-years at risk (pyr), 964 patients died before the end of the follow-up. Mortality by deprivation showed the highest mortality rate for the most deprived group (96.2 per 1000 pyr, 95% CI: 84.0-110.2). After adjusting for sex, age, cancer stage, and the area of residence, the most deprived had a 60% higher excess mortality risk than the less deprived group (excess mortality risk ratio: 1.6, 95% CI: 1.1-2.3). Conclusions We found a consistent association between deprivation and CRC excess mortality and survival. The reasons behind these inequalities need further investigation in order to improve equality cancer outcomes in all social groups.

We developed a predictive score system for 30-day mortality after palliative radiotherapy by using predictors from routine electronic medical record. Patients with metastatic cancer receiving first course palliative radiotherapy from 1 July, 2007 to 31 December, 2017 were identified. 30-day mortality odds ratios and probabilities of the death predictive score were obtained using multivariable logistic regression model. Overall, 5,795 patients participated. Median follow-up was 39.6 months (range, 24.5–69.3) for all surviving patients. 5,290 patients died over a median 110 days, of whom 995 (17.2%) died within 30 days of radiotherapy commencement. The most important mortality predictors were primary lung cancer (odds ratio: 1.73, 95% confidence interval: 1.47–2.04) and log peripheral blood neutrophil lymphocyte ratio (odds ratio: 1.71, 95% confidence interval: 1.52–1.92). The developed predictive scoring system had 10 predictor variables and 20 points. The cross-validated area under curve was 0.81 (95% confidence interval: 0.79–0.82). The calibration suggested a reasonably good fit for the model (likelihood-ratio statistic: 2.81, P = 0.094), providing an accurate prediction for almost all 30-day mortality probabilities. The predictive scoring system accurately predicted 30-day mortality among patients with stage IV cancer. Oncologists may use this to tailor palliative therapy for patients.

Background Numerous studies have analysed the effect of comorbidity on cancer outcomes, but evidence on the association between multimorbidity and short-term mortality among colorectal cancer patients is limited. We aimed to assess this association and the most frequent patterns of multimorbidity associated with a higher short-term mortality risk among colorectal cancer patients in Spain. Methods Data were obtained from two Spanish population-based cancer registries and electronic health records. We estimated the unadjusted cumulative incidence of death by comorbidity status at 6 months and 1 year. We used a flexible parametric model to derive the excess mortality hazard ratios (HRs) for multimorbidity after adjusting for sex, age at diagnosis, cancer stage and treatment. We estimated the adjusted cumulative incidence of death by comorbidity status and identified multimorbidity patterns. Results Among the study participants, 1,048 cases were diagnosed with cancers of the colon and rectum, 2 cases with cancer of the anus with overlapping sites of the rectum and 11 cases with anal adenocarcinomas but treated as colorectal cancer patients. Among 1,061 colorectal cancer patients, 171 (16.2%) died before 6 months, 246 (23.3%) died before the 1-year follow-up, and 324 (30.5%) had multimorbidity. Patients with multimorbidity had two times higher mortality risk than those without comorbidities at 6 months (adjusted HR: 2.04; 95% confidence interval [CI]: 1.30–3.20, p = 0.002). The most frequent multimorbidity pattern was congestive heart failure + diabetes. However, patients with rheumatologic disease + diabetes had two times higher 1-year mortality risk than those without comorbidities (HR: 2.23; 95% CI: 1.23–4.07, p = 0.008). Conclusions Multimorbidity was a strong independent predictor of short-term mortality at 6 months and 1 year among the colorectal cancer patients in Spain. The identified multimorbidity pattern was consistent. Our findings might help identify patients at a higher risk for poor cancer and treatment outcomes M.A.L.F. received support from the Instituto de Salud Carlos III, Madrid, Spain (grant/award no. CP17/ 00206-EU-FEDER), and M.J.S. received support from the Andalusian Department of Health (grant no. PI0152/2017)

Background Cancer treatment and outcomes can be influenced by tumor characteristics, patient overall health status, and comorbidities. While previous studies have analyzed the influence of comorbidity on cancer outcomes, limited information is available regarding factors associated with the increased prevalence of comorbidities and multimorbidity among patients with colorectal cancer in Spain. Patients and methods This cross-sectional study obtained data from all colorectal cancer cases diagnosed in two Spanish provinces in 2011 from two population-based cancer registries and electronic health records. We calculated the prevalence of comorbidities according to patient and tumor factors, identified factors associated with an increased prevalence of comorbidity and multimorbidity, analyzed the association between comorbidities and time-to-surgery, and developed an interactive web application (https://comcor.netlify.com/). Results The most common comorbidities were diabetes (23.6%), chronic obstructive pulmonary disease (17.2%), and congestive heart failure (14.5%). Among all comorbidities, 52% of patients were diagnosed at more advanced stages (stage III/IV). Patients with advanced age, restricted performance status or who were disabled, obese, and smokers had a higher prevalence of multimorbidity. Patients with multimorbidity had a longer time-to-surgery than those without comorbidity (17 days, 95% confidence interval: 3-29 days). Conclusion We identified a consistent pattern of factors associated with a higher prevalence of comorbidities and multimorbidity at diagnosis and an increased time-to-surgery among patients with colorectal cancer with multimorbidity in Spain. This pattern may provide insights for further etiological and preventive research and help to identify patients at a higher risk for poorer cancer outcomes and suboptimal treatment.

Simple Summary Diffuse large B-cell (DLBCL) and follicular lymphoma (FL) account for most non-Hodgkin lymphoma diagnoses: around 35% and 20% in England, respectively. Despite the vast contrast in survival between the subtypes, similar socioeconomic inequalities in survival have persisted over the past two decades, possibly due to the presence of comorbidities. The aim of our study was to assess the association between socioeconomic status and survival from DLBCL or FL accounting for patient and health system characteristics. We found that, for both DLBCL and FL, the most deprived patients had a higher excess mortality hazard compared to the least deprived, regardless of the comorbidity status. Our results show the need for the current framework of the National Health Service to improve the survival of DLBCL and FL patients in the most deprived areas of England, and further consideration is needed for patient-tailored management plans amongst patients with comorbidities or multimorbidities. Abstract (1) Background: Socioeconomic inequalities of survival in patients with lymphoma persist, which may be explained by patients’ comorbidities. We aimed to assess the association between comorbidities and the survival of patients diagnosed with diffuse large B-cell (DLBCL) or follicular lymphoma (FL) in England accounting for other socio-demographic characteristics. (2) Methods: Population-based cancer registry data were linked to Hospital Episode Statistics. We used a flexible multilevel excess hazard model to estimate excess mortality and net survival by patient’s comorbidity status, adjusted for sociodemographic, economic, and healthcare factors, and accounting for the patient’s area of residence. We used the latent normal joint modelling multiple imputation approach for missing data. (3) Results: Overall, 15,516 and 29,898 patients were diagnosed with FL and DLBCL in England between 2005 and 2013, respectively. Amongst DLBCL and FL patients, respectively, those in the most deprived areas showed 1.22 (95% confidence interval (CI): 1.18–1.27) and 1.45 (95% CI: 1.30–1.62) times higher excess mortality hazard compared to those in the least deprived areas, adjusted for comorbidity status, age at diagnosis, sex, ethnicity, and route to diagnosis. (4) Conclusions: Deprivation is consistently associated with poorer survival among patients diagnosed with DLBCL or FL, after adjusting for co/multimorbidities. Comorbidities and multimorbidities need to be considered when planning public health interventions targeting haematological malignancies in England.

ObjectivesWe aimed to assess the association between multimorbidity and deprivation on short-term mortality among patients with diffuse large B-cell (DLBCL) and follicular lymphoma (FL) in England.SettingThe association of multimorbidity and socioeconomic deprivation on survival among patients diagnosed with DLBCL and FL in England between 2005 and 2013. We linked the English population-based cancer registry with electronic health records databases and estimated adjusted mortality rate ratios by multimorbidity and deprivation status. Using flexible hazard-based regression models, we computed DLBCL and FL standardised mortality risk by deprivation and multimorbidity at 1 year.ResultsOverall, 41 422 patients aged 45–99 years were diagnosed with DLBCL or FL in England during 2005–2015. Most deprived patients with FL with multimorbidities had three times higher hazard of 1-year mortality (HR: 3.3, CI 2.48 to 4.28, pConclusionsMultimorbidity, deprivation and their combination are strong and independent predictors of an increased short-term mortality risk among patients with DLBCL and FL in England. Public health measures targeting the reduction of multimorbidity among most deprived patients with DLBCL and FL are needed to reduce the short-term mortality gap.

The main purpose of many medical studies is to estimate the effects of a treatment or exposure on an outcome. However, it is not always possible to randomize the study participants to a particular treatment, therefore observational study designs may be used. There are major challenges with observational studies; one of which is confounding. Controlling for confounding is commonly performed by direct adjustment of measured confounders; although, sometimes this approach is suboptimal due to modeling assumptions and misspecification. Recent advances in the field of causal inference have dealt with confounding by building on classical standardization methods. However, these recent advances have progressed quickly with a relative paucity of computational-oriented applied tutorials contributing to some confusion in the use of these methods among applied researchers. In this tutorial, we show the computational implementation of different causal inference estimators from a historical perspective where new estimators were developed to overcome the limitations of the previous estimators (ie, nonparametric and parametric g-formula, inverse probability weighting, double-robust, and data-adaptive estimators). We illustrate the implementation of different methods using an empirical example from the Connors study based on intensive care medicine, and most importantly, we provide reproducible and commented code in Stata, R, and Python for researchers to adapt in their own observational study. The code can be accessed at https://github.com/migariane/Tutorial_Computational_Causal_Inference_Estimators.

MALF was supported by the Spanish National Health Institute Carlos III (Instituto de Salud Carlos III -ISCIII), Miguel Servet--I Investigator Grant/Award Number CP17/00206--EU--FEDER., Objective We evaluated the temporal trend in gender ratios of first and last authors in the field of oncological research published in major general medical and oncology journals and examined the gender pattern in coauthorship. Design We conducted a retrospective study in PubMed using the R package RISmed. We retrieved original research articles published in four general medical journals and six oncology specialty journals. These journals were selected based on their impact factors and popularity among oncologists. We identified the names of first and last authors from 1 January 2002 to 31 December 2019. The gender of the authors was identified and validated using the Gender API database (https:// gender-​api. com/). Primary and secondary outcome measures The percentages of first and last authors by gender and the gender ratios (male to female) and temporal trends in gender ratios of first and last authors were determined. Results We identified 34 624 research articles, in which 32 452 had the gender of both first and last authors identified. Among these 11 650 (33.6%) had women as the first author and 7908 (22.8%) as the last author, respectively. The proportion of female first and last authors increased from 26.6% and 16.2% in 2002, to 32.9% and 27.5% in 2019, respectively. However, the gender ratio (male to female) of first and last authors decreased by 1.5% and 2.6% per year, respectively, which were statistically significant (first author: incidence rate ratio (IRR) 0.98, 95% CI 0.97 to 1.00; last author: IRR 0.97, 95% CI 0.96 to 0.99). Male first and last authorship was the most common combination. Male–female and female– female pairs increased by 2.0% and 5.0%, respectively (IRR 1.02, 95% CI 1.01 to 1.03 and IRR 1.05, 95% CI 1.04 to 1.06, respectively). Conclusions The continued under-representation of women means that more efforts to address parity for advancement of women in academic oncology are needed., Spanish National Health Institute Carlos III (Instituto de Salud Carlos III -ISCIII) CP17/00206--EU--FEDER

M.A.L.F. received support from the Instituto de Salud Carlos III, Madrid, Spain (grant/award no. CP17/00206-EU-FEDER). This work was supported by the Instituto de Salud Carlos III, Madrid, Spain [EU-FEDER-FIS PI-18/01593], the Consortium for Biomedical Research in Epidemiology and Public Health (CIBER en Epidemiologia y Salud Publica), the Cancer Epidemiological Surveillance Subprogram (VICA) from the Instituto de Salud Carlos III, Madrid, Spain, and the Andalusian Department of Health [PI-0152/2017]. The funders had no role in the design and conduct of the study, data collection, management, analysis, and interpretation of the data, the preparation, review, or approval of the manuscript or the decision to submit the manuscript for publication., Aim: Chronic diseases often occur simultaneously and tend to be associated with adverse health outcomes, but limited research has been undertaken to understand their role in lung cancer mortality. Therefore, this study aims to describe the prevalence and patterns of having one (comorbidity) or ≥ 2 chronic diseases (multimorbidity) among lung cancer patients in Spain, and to examine the association between comorbidity or multimorbidity and short-term mortality risk at six months after cancer diagnosis. Methods: In this population-based cohort study, data were drawn from two Spanish population-based cancer registries, Girona and Granada, and electronic health records. We identified 1259 adult lung cancer patients, diagnosed from 1st January 2011 to 31st December 2012. We identified the most common patterns of individual comorbidities and their pairwise correlations. We used a flexible parametric modelling approach to assess the overall short-term mortality risk 6 months after cancer diagnosis by levels of comorbidity after adjusting for age, sex, smoking status, province of residence, surgery, cancer stage, histology, and body mass index. Results: We found high prevalence of comorbidity in lung cancer patients, especially among the elderly, men, those diagnosed with advanced-stage tumours, smokers, and obese patients. The most frequent comorbidities were chronic obstructive pulmonary disease (36.6%), diabetes (20.7%) and heart failure (16.8%). The strongest pairwise correlation was the combination of heart failure with renal disease (r = 0.20, p < 0.01), and heart failure with diabetes (r = 0.16, p < 0.01). Patients with either one or two or more comorbidities had 40% higher overall mortality risk than those without comorbidities (aHR for comorbidity: 1.4, 95%CI: 1.1–1.7; aHR for multimorbidity: 1.4, 95%CI: 1.1–1.8), when relevant confounding factors were considered. Conclusions: The presence of comorbid diseases, rather than the number of comorbidities, was associated with increasing the risk of short-term lung cancer mortality in Spain. Comorbidity was a consistent and independent predictor of mortality among lung cancer patients, six months after diagnosis. The most common comorbid conditions were age-, obesity- and tobacco-related diseases. Our findings highlight the need to develop targeted preventive interventions and more personalised clinical guidelines to address the needs of lung cancer patients with one or more comorbidities in Spain., Instituto de Salud Carlos III CP17/00206-EU-FEDER EU-FEDER-FIS PI-18/01593, Consortium for Biomedical Research in Epidemiology and Public Health (CIBER en Epidemiologia y Salud Publica), Cancer Epidemiological Surveillance Subprogram (VICA) from the Instituto de Salud Carlos III, Madrid, Spain, Andalusian Department of Health PI-0152/2017

Introduction Diagnostic delay is associated with lower chances of cancer survival. Underlying comorbidities are known to affect the timely diagnosis of cancer. Diffuse large B-cell (DLBCL) and follicular lymphomas (FL) are primarily diagnosed amongst older patients, who are more likely to have comorbidities. Characteristics of clinical commissioning groups (CCG) are also known to impact diagnostic delay. We assess the association between comorbidities and diagnostic delay amongst patients with DLBCL or FL in England during 2005–2013. Methods Multivariable generalised linear mixed-effect models were used to assess the main association. Empirical Bayes estimates of the random effects were used to explore between-cluster variation. The latent normal joint modelling multiple imputation approach was used to account for partially observed variables. Results We included 30,078 and 15,551 patients diagnosed with DLBCL or FL, respectively. Amongst patients from the same CCG, having multimorbidity was strongly associated with the emergency route to diagnosis (DLBCL: odds ratio 1.56, CI 1.40–1.73; FL: odds ratio 1.80, CI 1.45–2.23). Amongst DLBCL patients, the diagnostic delay was possibly correlated with CCGs that had higher population densities. Conclusions Underlying comorbidity is associated with diagnostic delay amongst patients with DLBCL or FL. Results suggest a possible correlation between CCGs with higher population densities and diagnostic delay of aggressive lymphomas.

Background: Socioeconomic inequalities in survival from non-Hodgkin lymphoma persist. Comorbidities are more prevalent amongst those in more deprived areas and are associated with diagnostic delay (emergency diagnostic route), which is also associated with poorer survival probability. We aimed to describe the effect of comorbidity on the probability of death mediated by diagnostic route (emergency vs. elective route) amongst patients with diffuse large B-cell (DLBCL) or follicular lymphoma (FL). Methods: We linked the English population-based cancer registry and hospital admission records (2005–2013) of patients aged 45–99 years. We decomposed the effect of comorbidity on survival into an indirect effect acting through diagnostic route and a direct effect not mediated by diagnostic route. Furthermore, we estimated the proportion of the comorbidity effect on survival mediated by diagnostic route. Results: For both DLBCL (n = 27,379) and FL (n = 14,043), those with any comorbidity, or living in more deprived areas, were more likely to experience diagnostic delay and poorer survival. The indirect effect of comorbidity on mortality through diagnostic route was highest at 12 months since diagnosis (DLBCL: Odds Ratio 1.10 [95% CI 1.07–1.13], FL: OR 1.09 [95% CI 1.04–1.14]). Within the first 12 months since diagnosis, emergency diagnostic route accounted for 24% (95% CI 17.5–29.5) and 16% (95% CI 6.0–25.6) of the comorbidity effect on mortality, for DLBCL and FL, respectively. Conclusion: Efforts to reduce diagnostic delay (emergency diagnosis) amongst patients with comorbidity would reduce inequalities in DLBCL and FL survival by 24% and 16%, respectively. Further public health programs and interventions are needed to reduce diagnostic delay amongst lymphoma patients with comorbidities., Cancer Research UK C7923/A18525

Background: The incidence and survival of colorectal cancer (CRC) are increasing. There is an increasing number of long-term survivors, many of whom are elderly and have comorbidities. We conducted a population-based study in Hong Kong to assess the long-term cardiovascular disease (CVD) incidence associated with adjuvant fluoropyrimidine-based chemotherapy among CRC survivors. Patients and Methods: Using the population-based electronic medical database of Hong Kong, we identified adults who were diagnosed with high-risk stage II–III CRC and treated with radical surgery followed by adjuvant fluoropyrimidine-based chemotherapy between 2010 and 2019. We evaluated the cause-specific cumulative incidence of CVD (including ischemic heart disease, heart failure, cardiomyopathy, and stroke) using the flexible parametric competing risk modeling framework. The control group without a history of CVD was selected from among a noncancer random sample from primary care clinics in the same geographic area. Results: We analyzed 1,037 treated patients with CRC and 5,078 noncancer controls. The adjusted cause-specific hazard ratio (HR) for CVD in the cancer cohort compared with the control group was 2.11 (95% CI, 1.39–3.20). The 1-, 5-, and 10-year cause-specific cumulative incidences were 2.0%, 4.5%, and 5.4% in the cancer cohort versus 1.2%, 3.0%, and 3.8% in the control group, respectively. Age at cancer diagnosis (HR per 5-year increase, 1.16; 95% CI, 1.08–1.24), male sex (HR, 1.40; 95% CI, 1.06–1.86), comorbidity (HR, 1.88; 95% CI, 1.36–2.61 for 1 comorbidity vs none, and HR, 6.61; 95% CI, 4.55–9.60 for ≥2 comorbidities vs none), diabetes (HR, 1.38; 95% CI, 1.04–1.84), hypertension (HR, 3.27; 95% CI, 2.39–4.50), and dyslipidemia/hyperlipidemia (HR, 2.53; 95% CI, 1.68–3.81) were associated with incident CVD. Conclusions: Exposure to adjuvant fluoropyrimidine-based chemotherapy was associated with an increased risk of CVD among survivors of high-risk stage II–III CRC. Cardiovascular risk monitoring of this group throughout cancer survivorship is advisable.

AIMS: To evaluate the ability of first trimester plasma glycated CD59 (pGCD59) to predict gestational diabetes mellitus (GDM) at 24-28 weeks of gestation. METHODS: Prospectively, in 378 pregnant women, GDM was diagnosed using the one step 2 h 75 g oral glucose tolerance test adjudicated by the World Health Organisation (WHO) 2013 criteria. The ability of pGCD59 to predict GDM was assessed using receiver operating characteristic (ROC) curves adjusted for maternal age, body mass index (BMI), maternal ethnicity, parity, previous GDM, family history of diabetes mellitus and week of gestation at time of pGCD59 sampling. RESULTS: pGCD59 generated an adjusted area under the curve (AUC) of (a) 0.63 (95 %CI:0.56-0.70, p

Receiver operating characteristic (ROC) analysis is used for comparing predictive models in both model selection and model evaluation. ROC analysis is often applied in clinical medicine and social science to assess the tradeoff between model sensitivity and specificity. After fitting a binary logistic or probit regression model with a set of independent variables, the predictive performance of this set of variables can be assessed by the area under the curve (AUC) from an ROC curve. An important aspect of predictive modeling (regardless of model type) is the ability of a model to generalize to new cases. Evaluating the predictive performance (AUC) of a set of independent variables using all cases from the original analysis sample often results in an overly optimistic estimate of predictive performance. One can use K-fold cross-validation to generate a more realistic estimate of predictive performance in situations with a small number of observations. AUC is estimated iteratively for k samples (the “test” samples) that are independent of the sample used to predict the dependent variable (the “training” sample). cvauroc implements k-fold cross-validation for the AUC for a binary outcome after fitting a logit or probit regression model, averaging the AUCs corresponding to each fold, and bootstrapping the cross-validated AUC to obtain statistical inference and 95% confidence intervals. Furthermore, cvauroc optionally provides the cross-validated fitted probabilities for the dependent variable or outcome, contained in a new variable named _fit; the sensitivity and specificity for each of the levels of the predicted outcome, contained in two new variables named _sen and _spe; and the plot of the mean cross-validated AUC and k-fold ROC curves.

We investigated the temporal pattern of death in cancer patients using a large sample size and robust statistical methods to account for chronobiological periodicity.We did not detect a circadian pattern of cancer death. The present study evaluated the temporal pattern of death among cancer patients using trigonometric functions and with time modeled in a circular scale.To conclude, we found no evidence of a chronobiological circadian pattern in death among cancer patients by using robust statistical methods and data from a large population in a hospital setting. Increased understanding of the temporal pattern of deaths may yield important insights toward understanding external factors associated with cancer death.

The influence of socioeconomic status (SES) on access to standard chemotherapy and/or monoclonal antibody therapy, and associated secular trends, relative survival, and excess mortality, among diffuse large B-cell lymphoma (DLBCL) patients is not clear. We conducted a Hong Kong population-based cohort study and identified adult patients with histologically diagnosed DLBCL between 2000 and 2018. We examined the association of SES levels with the odds and the secular trends of receipt of chemotherapy and/or rituximab. Additionally, we estimated the long-term relative survival by SES utilizing Hong Kong life tables. Among 4,017 patients with DLBCL, 2,363 (58.8%) patients received both chemotherapy and rituximab and 740 (18.4%) patients received chemotherapy alone, while 1,612 (40.1%) and 914 (22.8%) patients received no rituximab or chemotherapy, respectively. On multivariable analysis, low SES was associated with lesser use of chemotherapy (odd ratio [OR], 0.44; 95% CI 0.34–0.57) and rituximab (OR, 0.41; 95% CI, 0.32–0.52). The socioeconomic disparity for either treatment showed no secular trend of change. Additionally, patients with low SES showed increased excess mortality, with a hazard ratio of 2.34 (95% CI, 1.67–3.28). Improving survival outcomes for patients with DLBCL requires provision of best available medical care and securing access to treatment regardless of patients’ SES.

Background Socioeconomic inequalities of survival in patients with non–Hodgkin lymphoma (NHL) persists, which may be explained by patients’ comorbidities. We aimed to assess the association between co/multimorbidity and survival in patients diagnosed with Diffuse Large B-cell (DLBCL) or Follicular lymphoma (FL) in England accounting for other socio-demographic characteristics. Methods Population-based cancer registry data was linked to Hospital Episode Statistics. We used a flexible multilevel excess hazard model to estimate 5–year net survival and excess mortality by patient’s multimorbidity and comorbidity status adjusted for sociodemographic, economic, healthcare factors, and accounting for the patient’s area of residence. Results Overall, 15,516 and 29,898 patients were diagnosed with FL and DLBCL in England between 2005–2013, respectively. Respectively, those with comorbidities and multimorbidities had 1.3 (95% Confidence Interval -CI-: 1.20–1.40) and 1.5 (95% CI 1.27–1.87) times higher excess mortality compared to those without comorbidities. Patients in most deprived areas showed 26% (95% CI 1.20–1.32) excess mortality risk compared to those in least deprived areas. Conclusion Co/multimorbidities are consistently associated with poorer survival among patients diagnosed with DLBCL or FL. Comorbidities and multimorbidity need to be considered when planning public health interventions targeting haematological malignancies in England.

There are few if any reports regarding the role of lifetime waterpipe smoking in the etiology of multiple sclerosis (MS). In a population-based incident case-control study conducted in Tehran, Iran, we investigated the association between waterpipe smoking and MS, adjusted for confounders. Cases (n = 547) were patients aged 15–50 years identified from the Iranian Multiple Sclerosis Society between 2013 and 2015. Population-based controls (n = 1,057) were persons aged 15–50 years recruited through random digit telephone dialing. A doubly robust estimation method, the targeted maximum likelihood estimator (TMLE), was used to estimate the marginal risk ratio and odds ratio for the association between waterpipe smoking and MS. The estimated risk ratio and odds ratio were both 1.70 (95% confidence interval: 1.34, 2.17). The population attributable fraction was 21.4% (95% confidence interval: 4.0, 38.8). Subject to the limitations of case-control studies in interpreting associations causally, these results suggest that waterpipe use, or strongly related but undetermined factors, increases the risk of MS. Further epidemiologic studies, including nested case-control studies, are needed to confirm these findings.

Classical epidemiology has focused on the control of confounding, but it is only recently that epidemiologists have started to focus on the bias produced by colliders. A collider for a certain pair of variables (e.g. an outcome Y and an exposure A) is a third variable (C) that is caused by both. In a directed acyclic graph (DAG), a collider is the variable in the middle of an inverted fork (i.e. the variable C in A → C ← Y). Controlling for, or conditioning an analysis on a collider (i.e. through stratification or regression) can introduce a spurious association between its causes. This potentially explains many paradoxical findings in the medical literature, where established risk factors for a particular outcome appear protective. We use an example from non-communicable disease epidemiology to contextualize and explain the effect of conditioning on a collider. We generate a dataset with 1000 observations, and run Monte-Carlo simulations to estimate the effect of 24-h dietary sodium intake on systolic blood pressure, controlling for age, which acts as a confounder, and 24-h urinary protein excretion, which acts as a collider. We illustrate how adding a collider to a regression model introduces bias. Thus, to prevent paradoxical associations, epidemiologists estimating causal effects should be wary of conditioning on colliders. We provide R code in easy-to-read boxes throughout the manuscript, and a GitHub repository [https://github.com/migariane/ColliderApp] for the reader to reproduce our example. We also provide an educational web application allowing real-time interaction to visualize the paradoxical effect of conditioning on a collider [http://watzilei.com/shiny/collider/].

Comorbidity is considered to be a prognostic factor in cancer outcomes. The presence of comorbidity can be influential at different points on the cancer pathway, from the time leading up to the diagnosis of cancer to treatment options and ultimate prognosis once cancer has been diagnosed. Cancer patients of lower social or socioeconomic position are more likely to be living with comorbidity than more affluent patients. This chapter aims to examine the role played by comorbidities in the social gradient in cancer survival that is often observed in Europe. It describes relationships between comorbidity and other factors associated with cancer survival, and discusses the findings of epidemiological studies within Europe that investigate comorbidity and social or socioeconomic inequalities in cancer outcomes.

We explored the role of socioeconomic inequalities in COVID-19 incidence among cancer patients during the first wave of the pandemic. We conducted a case-control study within the UK Biobank cohort linked to the COVID-19 tests results available from 16 March 2020 until 23 August 2020. The main exposure variable was socioeconomic status, assessed using the Townsend Deprivation Index. Among 18,917 participants with an incident malignancy in the UK Biobank cohort, 89 tested positive for COVID-19. The overall COVID-19 incidence was 4.7 cases per 1000 incident cancer patients (95%CI 3.8–5.8). Compared with the least deprived cancer patients, those living in the most deprived areas had an almost three times higher risk of testing positive (RR 2.6, 95%CI 1.1–5.8). Other independent risk factors were ethnic minority background, obesity, unemployment, smoking, and being diagnosed with a haematological cancer for less than five years. A consistent pattern of socioeconomic inequalities in COVID-19 among incident cancer patients in the UK highlights the need to prioritise the cancer patients living in the most deprived areas in vaccination planning. This socio-demographic profiling of vulnerable cancer patients at increased risk of infection can inform prevention strategies and policy improvements for the coming pandemic waves., Spanish National Health Institute Carlos III Miguel Servet-I - CP17/00206-EU-FEDER, EU-FEDER-FIS PI-18/01593

In Europe, lung cancer was the third most commonly diagnosed cancer in 2018 for both sexes combined and the leading cause of cancer death. It is also the most frequent cancer and the leading cause of cancer death worldwide. Despite new biological insights and the considerable diagnostic and therapeutic efforts made recently, lung cancer remains a deadly disease with one of the world’s lowest survival probability of all cancers. Similar to what occurs in incidence and mortality, Europe shows important differences in lung cancer survival among a variety of social groups. These differences have been examined less extensively than those in other cancer sites. We have reviewed 47 studies on the relationship between the social environment and lung cancer survival in European countries. Social disparities in lung cancer survival appear remarkably general, with the more deprived patients showing consistently lower survival after a lung cancer diagnosis. However, the effect sizes are generally smaller and not as consistent as those seen in cancers of a better prognosis. It seems that the social gradient in lung cancer survival in Europe is in part mediated by stage of disease at diagnosis and access to optimal treatment and specialised care, but further research on other potential contributing factors should be addressed. The influence of the social environment on the risk of dying from cancer is a global phenomenon, but the explanations for the social differences and the mechanisms underlying the social gradient in lung cancer survival in Europe are not very well known. In light of the results, priority should be given to further research on all possible social contributors to the differences in survival and improving early cancer diagnosis and better access to treatment and healthcare centres.

IntroductionThe significant maternal and neonatal outcomes of gestational diabetes mellitus (GDM) make it a major public health concern. Mothers with GDM are at greater risk of pregnancy complications and their offspring are at higher risk of diabetes and obesity. Currently, GDM is diagnosed with glucose load methods which are time-consuming and inconvenient to administer more than once during pregnancy; for this reason, there is a recognised need for a more accurate and simpler test for GDM. Previous studies indicate that plasma-glycated CD59 (pGCD59) is a novel biomarker for GDM. We present here the protocol of a prospective cohort study designed to (1) determine the accuracy of pGCD59 as an early, first trimester predictor of GDM and gestational impaired glucose tolerance and (2) assess the associations between pGCD59 levels and adverse maternal and neonatal outcomes.Methods and analysisWe will obtain discarded plasma samples from pregnant women at two time points: first prenatal visit (usually Ethics and disseminationThis study has been approved by the Mass General Brigham Institutional Review Board (protocol 2011P002254). The results of this study will be presented at international meetings and disseminated in peer-reviewed journals.

Several epidemiologic studies have shown an association between Gestational Weight Gain (GWG) and offspring complications. The GWG is directly linked to maternal dietary intake and women&rsquo, s nutritional status during pregnancy. The aim of this study was (1) to assess, in a sample of Spanish pregnant women, the association between maternal dietary patterns and GWG and (2) to assess maternal dietary patterns and nutrient adequate intake according to GWG. A retrospective study was conducted in a sample of 503 adult pregnant women in five hospitals in Eastern Andalusia (Spain). Data on demographic characteristics, anthropometric values, and dietary intake were collected from clinical records by trained midwives. Usual food intake was gathered through a validated Food Frequency Questionnaire (FFQ), and dietary patterns were obtained by principal component analysis. Nutrient adequacy was defined according to European dietary intake recommendations for pregnant women. Regression models adjusted by confounding factors were constructed to study the association between maternal dietary pattern and GWG, and maternal dietary patterns and nutritional adequacy. A negative association was found between GWG and the Mediterranean dietary pattern (crude &beta, = &minus, 0.06, 95% CI: &minus, 0.11, &minus, 0.04). Independent of maternal dietary pattern, nutrient adequacy of dietary fiber, vitamin B9, D, E, and iodine was related to a Mediterranean dietary pattern (p &lt, 0.05). A Mediterranean dietary pattern is related to lower GWG and better nutrient adequacy. The promotion of healthy dietary behavior consistent with the general advice promoted by the Mediterranean Diet (based on legumes, vegetables, nuts, olive oil, and whole cereals) will offer healthful, sustainable, and practical strategies to control GWG and ensure adequate nutrient intake during pregnancy.

Belot A, Ndiaye A, Luque-Fernandez MA, et al. ClinEpidemiol. 2019;11:53–65. Page 57, Number of life years lost (NLYL) section, leftcolumn, the sentence “where the quantity 1–FP(t) can bereplaced by SP(t), ie, the classical survival function usingthe population mortality rates λP” placed immediately afterequation 14 indicates that the quantity 1–FP(t) could bereplaced by SP(t). This is wrong as the one-to-one relationshipbetween hazard and risk applies only in all-causemortality setting but not in competing risks settings (suchas the cause-specific or relative survival setting). Indeed, FP(t) depends on both hazards (cancer and other causes)through the overall survival S(t). The authors therefore request the reader to ignore thissentence and apologize for this error. Read the original article &nbsp

La incidencia y la mortalidad brindan información sobre la carga de la morbilidad del cáncer y los añoos potenciales de vida perdidos debido al cáncer. Se ha desarrollado el Índice de Privación (IP) como una medida estandarizada para medir la privación socioeconómica en España a nivel de sección censal. Además, se puede combinar la información del IP con variables ecológicas poblacionales y los datos de los Estudios Europeos de Alta Resolución en Cáncer. El objetivo de este estudio es caracterizar las desigualdades socioeconómicas en la incidencia, el exceso de mortalidad, la mortalidad prematura y la supervivencia neta para tres de los cánceres más incidentes (pulmón, colon-recto y mama) en España usando el IP. Este estudio nacional multinivel de base poblacional evaluará el impacto de las desigualdades socioeconómicas. Se usarán el análisis espacial, la modelización multinivel, la supervivencia neta y la evaluación del impacto económico. Los resultados serán útiles para el apoyo a la toma de decisiones y la planificación y la gestión de intervenciones en salud pública destinadas a reducir el impacto de las desigualdades socioeconómicas en el diagnóstico y el pronóstico de los pacientes de cáncer en España., Incidence and mortality provide information on the burden of cancer morbidity and the potential years of life lost due to cancer. The Spanish Deprivation Index (SDI) has been developed as a standardized measure to study socioeconomic deprivation in Spain at the census tract level. In addition, SDI information can becombined with ecological variables at the population level and data from the High-Resolution European Studies in Cancer. The aim of this study is to characterize socioeconomic inequalities in incidence, excess mortality, premature mortality and net survival for three of the most incident cancers (lung, colon-rectum and breast) in Spain using the SDI. This national population-based study will assess the impact of socioeconomic inequalities using a multilevel modelling approach. Spatial analysis, multilevel mode-ling, net survival and economic impact assessment will be used. The results will be useful for supportingdecision-making, planning, and management of public health interventions aimed at reducing the impact of socioeconomic inequalities in the diagnosis and prognosis of cancer patients in Spain.

Background/aims To identify objective glaucoma-related structural features based on peripapillary (p) and macular (m) spectral domain optical coherence tomography (SD-OCT) parameters and assess their discriminative ability between healthy and glaucoma patients. Methods Two hundred and sixty eyes (91 controls and 169 glaucoma) were included in this prospective study. After a complete examination, all participants underwent the posterior pole and the peripapillary retinal nerve fibre layer (pRNFL) protocols of the Spectralis SD-OCT. Principal component analysis (PCA), a data reduction method, was applied to identify and characterise the main information provided by the ganglion cell complex (GCC). The discriminative ability between healthy and glaucomatous eyes of the first principal components (PCs) was compared with that of conventional SD-OCT parameters (pRNFL, macular RNFL (mRNFL), macular ganglion cell layer (mGCL)and macular inner plexiform layer (mIPL)) using 10-fold cross-validated areas under the curve (AUC). Results The first PC explained 58% of the total information contained in the GCC and the pRNFL parameters and was the result of a general combination of almost all variables studied (diffuse distribution). Other PCs were driven mainly by pRNFL and mRNFL measurements. PCs and pRNFL had similar AUC (0.95 vs 0.96, p=0.88), and outperformed the other structural measurements: mRNFL (0.91, p=0.002), mGCL (0.92, p=0.02) and mIPL (0.92, p=0.0001). Conclusions PCA identified a diffuse representation of the papillary and macular SD-OCT parameters as the most important PC to summarise structural data in healthy and glaucomatous eyes. PCs and pRNFL parameters showed the greatest discriminative ability between healthy and glaucoma cases.

Background The presence of comorbidity affects the care of cancer patients, many of whom are living with multiple comorbidities. The prevalence of cancer comorbidity, beyond summary metrics, is not well known. This study aims to estimate the prevalence of comorbid conditions among cancer patients in England, and describe the association between cancer comorbidity and socio-economic position, using population-based electronic health records. Methods We linked England cancer registry records of patients diagnosed with cancer of the colon, rectum, lung or Hodgkin lymphoma between 2009 and 2013, with hospital admissions records. A comorbidity was any one of fourteen specific conditions, diagnosed during hospital admission up to 6 years prior to cancer diagnosis. We calculated the crude and age-sex adjusted prevalence of each condition, the frequency of multiple comorbidity combinations, and used logistic regression and multinomial logistic regression to estimate the adjusted odds of having each condition and the probability of having each condition as a single or one of multiple comorbidities, respectively, by cancer type. Results Comorbidity was most prevalent in patients with lung cancer and least prevalent in Hodgkin lymphoma patients. Up to two-thirds of patients within each of the four cancer patient cohorts we studied had at least one comorbidity, and around half of the comorbid patients had multiple comorbidities. Our study highlighted common comorbid conditions among the cancer patient cohorts. In all four cohorts, the odds of having a comorbidity and the probability of multiple comorbidity were consistently highest in the most deprived cancer patients. Conclusions Cancer healthcare guidelines may need to consider prominent comorbid conditions, particularly to benefit the prognosis of the most deprived patients who carry the greater burden of comorbidity. Insight into patterns of cancer comorbidity may inform further research into the influence of specific comorbidities on socio-economic inequalities in receipt of cancer treatment and in short-term mortality.

Background: The influence of socioeconomic status (SES) on access to standard chemotherapy and/or monoclonal antibody therapy, and associated secular trends, relative survival, and excess mortality, among diffuse large B-cell lymphoma (DLBCL) patients is not clear. Methods: We developed a population-based study based on a territory-wide electronic database of Hong Kong. We identified adult patients with DLBCL who were histologically diagnosed between 2000 and 2018. We evaluated the odds and the secular trends of receipt of chemotherapy and/or rituximab by levels of SES. In addition, we estimated DLBCL long term relative survival by SES utilizing Hong Kong life tables. Findings: Among 4,017 patients with DLBCL, 2,363 (58·8%) patients received both chemotherapy and rituximab and 740 (18·4%) patients received chemotherapy alone, while 1,612 (40·1%) and 914 (22·8%) patients received no rituximab or chemotherapy, respectively. On multivariable analysis, low SES was associated with lesser use of any chemotherapy (OR, 0·44; 95% CI 0·34-0·57; p

Context Gestational diabetes mellitus (GDM) diagnosed in early pregnancy is a health care challenge because it increases the risk of adverse outcomes. Plasma-glycated CD59 (pGCD59) is an emerging biomarker for diabetes and GDM. The aim of this study was to assess the performance of pGCD59 as a biomarker of early GDM and its association with delivering a large for gestational age (LGA) infant. Objectives To assess the performance of pGCD59 to identify women with GDM in early pregnancy (GDM Methods Blood levels of pGCD59 were measured in samples from 693 obese women (body mass index > 29) undergoing a 75-g, 2-hour oral glucose tolerance test (OGTT) at Results Mean pGCD59 levels were significantly higher (P Conclusion Our results indicate that pGCD59 is a simple and accurate biomarker for detection of GDM in early pregnancy and risk assessment of LGA.

Evidence regarding the dose-related impact of doxorubicin on subsequent cardiovascular diseases (CVDs) in Asian patients with diffuse large B-cell lymphoma (DLBCL) without preexisting CVDs is lacking. From a territory-wide electronic database in Hong Kong, we identified adults who were diagnosed with DLBCL and treated with chemotherapy between 2000 and 2018. We evaluated the patients for incident CVDs (including ischemic heart disease, heart failure, and cardiomyopathy). We evaluated the cause-specific cumulative incidence (csCI) of CVD with levels of doxorubicin exposure by using flexible parametric competing risk analysis and adjusting for demographics, comorbidities, therapeutic exposure, cardiovascular risk factors, and lifestyle factors. Controls were age- and sexmatched to DLBCL patients. We analyzed 2600 patients and 13 000 controls. The adjusted cause-specific hazard ratio (HR) for CVD in patients treated with .500 mg doxorubicin compared with non-doxorubicin regimens was 2.65 (95% confidence interval [CI], 1.23-5.74; P 5 .013). The 5-, 10-, and 15-year csCIs were 8.2%, 11.3%, and 12.8% in patients vs 3.1%, 4.4%, and 5.2% in controls, respectively. Hypertension (HR, 6.20; 95% CI, 0.79-48.44; P 5 .082) and use of aspirin/angiotensin-converting enzyme inhibitor/beta-blocker at baseline (HR, 2.13-4.63; P , .001 to .002) might confer a higher risk of subsequent CVDs. In this Hong Kong population-based study, doxorubicin exposure (absolute dose .500 mg), together with hypertension or baseline use of medication for cardiovascular risk factors, was found to be associated with an increase in csCIs of CVDs. Tailoring therapeutic strategies to underlying CVD risk factors and risk-adapted monitoring and follow-up of susceptible DLBCL patients are advisable., United States Department of Health & Human Services National Institutes of Health (NIH) - USA, Harvard Catalyst, Harvard Clinical and Translational Science Center (National Center for Advancing Translational Sciences) UL1TR002541, HarvardUniversity andits affiliated academic health care centers, Spanish National Health Institute Carlos III Miguel Servet-I Investigator grant/award CP17/00206, United States Department of Health & Human Services National Institutes of Health (NIH) - USA NIH National Cancer Institute (NCI) R01 CA196854