Publications

2022
Redondo-Sánchez D, Sánchez M-J, Fernández-Navarro P, Rachet B, Luque-Fernandez MA. Association of socioeconomic deprivation with life expectancy and all-cause mortality in Spain, 2011–2013 [Internet]. Scientific Reports 2022;12(1):15554. Publisher's VersionAbstract
Life tables summarise a population's mortality experience during a time period. Sex- and age-specific life tables are needed to compute various cancer survival measures. However, mortality rates vary according to socioeconomic status. We present sex- and age-specific life tables based on socioeconomic status at the census tract level in Spain during 2011–2013 that will allow estimating cancer relative survival estimates and life expectancy measures by socioeconomic status. Population and mortality data were obtained from the Spanish Statistical Office. Socioeconomic level was measured using the Spanish Deprivation Index by census tract. We produced sex- and age-specific life expectancies at birth by quintiles of deprivation, and life tables by census tract and province. Life expectancy at birth was higher among women than among men. Women and men in the most deprived census tracts in Spain lived 3.2 and 3.8 years less than their counterparts in the least deprived areas. A higher life expectancy in the northern regions of Spain was discovered. Life expectancy was higher in provincial capitals than in rural areas. We found a significant life expectancy gap and geographical variation by sex and socioeconomic status in Spain. The gap was more pronounced among men than among women. Understanding the association between life expectancy and socioeconomic status could help in developing appropriate public health programs. Furthermore, the life tables we produced are needed to estimate cancer specific survival measures by socioeconomic status. Therefore, they are important for cancer control in Spain.
Bogdanet D, Luque-Fernandez MA, Toth-Castillo M, Desoye G, O’Shea PM, Dunne FP, Halperin JA, Group DALICI. The role of early pregnancy maternal pGCD59 levels in predicting neonatal hypoglycaemia- sub-analysis of the DALI study [Internet]. The Journal of Clinical Endocrinology & Metabolism 2022; Publisher's VersionAbstract
The aim of this study was to assess the association between early pregnancy maternal levels of plasma glycated CD59 (pGCD59) and neonatal hypoglycaemia (NH).This is an observational study of pregnant women with a pre-pregnancy body mass index (BMI) ≥ 29 kg/m2 screened for eligibility to participate in the Vitamin D and Lifestyle Intervention for Gestational Diabetes (DALI) trial. This analysis included 399 pregnancies. Levels of pGCD59, were measured in fasting maternal samples taken at the time of a 75 g, 2-hour oral glucose tolerance test (OGTT) performed in early pregnancy (\<20 weeks). NH, the study outcome, was defined as a heel-prick capillary glucose level of less than 2.6 mmol/L within 48 h of delivery.We identified 30 infants with NH. Maternal levels of pGCD59 in early pregnancy, were positively associated with the prevalence of NH (ANOVA one-way, p-value \<0.001). The odds of NH were higher in infants from mothers in the Tertile 3 of pGCD59 levels as compared to those from mothers in Tertile 1 (OR: 2.41, 95\% CI: 1.03–5.63). However, this was attenuated when adjusted for maternal BMI (OR: 2.28 (95\% CI: 0.96–5.43). The cross-validated area under the curve (AUC) was 0.64 (95\% CI: 0.54–0.74), and adjusted for maternal BMI, age, and ethnicity, the AUC was 0.70 (95\% CI: 0.56–0.78).Although pGCD59 levels in early pregnancy in women with BMI ≥29 kg/m2 are associated with NH, our results indicate that this biomarker by itself is only a fair predictor of NH.
Bogdanet D, Toth Castillo M, Doheny H, Dervan L, Luque-Fernandez MA, Halperin J, O'Shea PM, Dunne FP. The utility of first trimester plasma glycated CD59 (pGCD59) in predicting gestational diabetes mellitus: a prospective study of non-diabetic pregnant women in Ireland [Internet]. Diabetes Research and Clinical Practice 2022;:110023. Publisher's VersionAbstract
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 2h 75g 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<0.001) for predicting GDM, and b) 0.71 (95%CI:0.62-0.79, p<0.001 for GDM diagnosed with a fasting plasma glucose (FPG) ≥5.1 mmol/L. Sensitivity analysis of BMI subgroups showed that pGCD59 generated the highest AUC in the 35 kg/m2 ≤ BMI <40 kg/m2 (AUC:0.85, 95%CI:0.70-0.98) and BMI ≥40 kg/m2 (AUC:0.88, 95%CI:0.63-0.99) categories. Conclusions Early in pregnancy, pGCD59 may be a good predictor of GDM in women with a high BMI and a fair predictor of GDM diagnosed by an elevated FPG independent of BMI.
Bogdanet D, Toth Castillo M, Doheny H, Dervan L, Luque-Fernandez M-A, Halperin JA, O’Shea PM, Dunne FP. The Diagnostic Accuracy of Second Trimester Plasma Glycated CD59 (pGCD59) to Identify Women with Gestational Diabetes Mellitus Based on the 75 g OGTT Using the WHO Criteria: A Prospective Study of Non-Diabetic Pregnant Women in Ireland [Internet]. Journal of Clinical Medicine 2022;11(13) Publisher's VersionAbstract
: 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.
Zepeda-Tello R, Schomaker M, Maringe C, Smith MJ, Belot A, Rachet B, Schnitzer ME, Luque-Fernandez MA. The Delta-Method and Influence Function in Medical Statistics: a Reproducible Tutorial [Internet]. 2022; Publisher's VersionAbstract
:Approximate statistical inference via determination of the asymptotic distribution of a statistic is routinely used for inference in applied medical statistics (e.g. to estimate the standard error of the marginal or conditional risk ratio). One method for variance estimation is the classical Delta-method but there is a knowledge gap as this method is not routinely included in training for applied medical statistics and its uses are not widely understood. Given that a smooth function of an asymptotically normal estimator is also asymptotically normally distributed, the Delta-method allows approximating the large-sample variance of a function of an estimator with known large-sample properties. In a more general setting, it is a technique for approximating the variance of a functional (i.e., an estimand) that takes a function as an input and applies another function to it (e.g. the expectation function). Specifically, we may approximate the variance of the function using the functional Delta-method based on the influence function (IF). The IF explores how a functional ϕ(θ) changes in response to small perturbations in the sample distribution of the estimator and allows computing the empirical standard error of the distribution of the functional. The ongoing development of new methods and techniques may pose a challenge for applied statisticians who are interested in mastering the application of these methods. In this tutorial, we review the use of the classical and functional Delta-method and their links to the IF from a practical perspective. We illustrate the methods using a cancer epidemiology example and we provide reproducible and commented code in R and Python using symbolic programming. The code can be accessed at this https URL https://github.com/migariane/DeltaMethodInfluenceFunction
Luque-Fernandez MA, Tobias A. The Management of the COVID-19 Pandemic Evidences the Need to Transform Spain’s Public Health Education [Internet]. International Journal of Public Health 2022;67 Publisher's Version
Andrews C, Toth-Castillo M, Aktas H, Luque-Fernandez MA, Wong SK, Sen S, Halperin J. Plasma-glycated CD59 as an early biomarker for gestational diabetes mellitus: prospective cohort study protocol [Internet]. BMJ Open 2022;12(4) Publisher's VersionAbstract
Introduction The 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 analysis We will obtain discarded plasma samples from pregnant women at two time points: first prenatal visit (usually <14 weeks gestation) and gestational weeks 24–28. A study-specific medical record abstraction tool will be used to obtain relevant maternal and neonatal clinical data from the EPIC clinical database. The prevalence of GDM will be determined using standard of care glucose load test results. We will determine the sensitivity and specificity of pGCD59 to predict the diagnosis of GDM and gestational impaired glucose tolerance, as well as the associations between levels of pGCD59 and the prevalence of maternal and neonatal outcomes.Ethics and dissemination This 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.
Rubio FJ, Alvares D, Redondo-Sanchez D, Marcos-Gragera R, Sánchez M-J, Luque-Fernandez MA. Bayesian variable selection and survival modeling: assessing the Most important comorbidities that impact lung and colorectal cancer survival in Spain [Internet]. BMC Medical Research Methodology 2022;22(1):95. Publisher's VersionAbstract
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.
Lee SF, Vellayappan BA, Wong LC, Chiang CL, Chan SK, Wan EY-F, Wong IC-K, Lambert PC, Rachet B, Ng AK, Luque-Fernandez MA. Cardiovascular diseases among diffuse large B-cell lymphoma long-term survivors in Asia: a multistate model study [Internet]. ESMO Open 2022;7(1):100363. Publisher's VersionAbstract
Background We modeled the clinical course of a cohort of diffuse large B-cell lymphoma (DLBCL) patients with no prior cardiovascular diseases (CVDs) using a multistate modeling framework. Patients and methods Data on 2600 patients with DLBCL diagnosed between 2000 and 2018 and had received chemotherapy with or without radiotherapy were obtained from a population-wide electronic health database of Hong Kong. We used the Markov illness-death model to quantify the impact of doxorubicin and various risk factors (therapeutic exposure, demographic, comorbidities, cardiovascular risk factors, and lifestyle factors which included smoking) on the clinical course of DLBCL (transitions into incident CVD, lymphoma death, and other causes of death). Results A total of 613 (23.6%) and 230 (8.8%) of 2600 subjects died of lymphoma and developed incident CVD, respectively. Median follow-up was 7.0 years (interquartile range 3.8-10.8 years). Older ages [hazard ratio (HR) for >75 versus ≤60 years 1.88; 95% confidence interval (CI) 1.25-2.82 and HR for 61-75 versus ≤60 years 1.60; 95% CI 1.12-2.30], hypertension (HR 4.92; 95% CI 2.61-9.26), diabetes (HR 1.43; 95% CI 1.09-1.87), and baseline use of aspirin (HR 5.30; 95% CI 3.93-7.16) were associated with an increased risk of incident CVD. In a subgroup of anticipated higher-risk patients (aged 61-75 years, smoked, had diabetes, and received doxorubicin), we found that they remained on average 7.9 (95% CI 7.2-8.8) years in the DLBCL state and 0.1 (95% CI 0.0-0.4) years in the CVD state, if they could be followed up for 10 years. The brief time in the CVD state is consistent with the high chance of death in patients who developed CVD. Other causes of death have overtaken DLBCL-related death after about 5 years. Conclusions In this Asian population-based cohort, we found that incident CVDs can occur soon after DLBCL treatment and continued to occur throughout survivorship. Clinicians are advised to balance the risks and benefits of treatment choices to minimize the risk of CVD.
2021
Smith MJ, Njagi EN, Belot A, Leyrat C, Bonaventure A, Majano SB, Rachet B, Luque-Fernandez MA. Association between multimorbidity and socioeconomic deprivation on short-term mortality among patients with diffuse large B-cell or follicular lymphoma in England: a nationwide cohort study [Internet]. BMJ Open 2021;11(11) Publisher's VersionAbstract
Objectives We 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.Setting The 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.Results Overall, 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, p<0.001) than least deprived patients without comorbidity; among DLBCL, there was approximately twice the hazard (HR: 1.9, CI 1.70 to 2.07, p<0.001).Conclusions Multimorbidity, 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.Data may be obtained from a third party and are not publicly available. The data that support the findings of this study are available via application to the Public Health England Office for Data Release, but restrictions apply to the availability of these data. No additional data available.
Smith MJ, Belot A, Quartagno M, Fernandez MAL, Bonaventure A, Gachau S, Majano SB, Rachet B, Njagi EN. Excess Mortality by Multimorbidity, Socioeconomic, and Healthcare Factors, amongst Patients Diagnosed with Diffuse Large B-Cell or Follicular Lymphoma in England [Internet]. Cancers 2021;13(22) Publisher's VersionAbstract
(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.
Smith MJ, Mansournia MA, Maringe C, Zivich PN, Cole SR, Leyrat C, Belot A, Rachet B, Luque-Fernandez MA. Introduction to computational causal inference using reproducible Stata, R, and Python code: A tutorial [Internet]. Statistics in Medicine 2021;n/a(n/a) Publisher's VersionAbstract

Abstract 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

Link to the GitHub Repo Including the CODE (Python, R and Stata)

Lee SF, Redondo Sánchez D, Sánchez M{\'ıa-J, Gelaye B, Chiang CL, Wong IOL, Cheung DST, Luque-Fernandez MA. Trends in gender of authors of original research in oncology among major medical journals: a retrospective bibliometric study [Internet]. BMJ Open 2021;11(10) Publisher's VersionAbstract
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.Data are available in a public, open access repository.
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Niksic M, Redondo-Sanchez D, Chang Y-L, RODRIGUEZ-BARRANCO MIGUEL, Exposito-Hernandez J, Marcos-Gragera R, Oliva-Poch E, Bosch-Barrera J, Sanchez M-J, Luque-Fernandez MA. The role of multimorbidity in short-term mortality of lung cancer patients in Spain: a population-based cohort study. BMC Cancer 2021;21(1):1048.Abstract
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. 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. 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. 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.
Lee SF, Evens AM, Ng AK, Luque-Fernandez M-A. Socioeconomic inequalities in treatment and relative survival among patients with diffuse large B-cell lymphoma: a Hong Kong population-based study [Internet]. Scientific Reports 2021;11(1):17950. Publisher's VersionAbstract
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.
Smith MJ, Luque-Fernandez MA, Belot A, Quartagno M, Bonaventure A, Majano SB, Rachet B, Njagi EN. Investigating the inequalities in route to diagnosis amongst patients with diffuse large B-cell or follicular lymphoma in England [Internet]. British Journal of Cancer 2021; Publisher's VersionAbstract
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.
Redondo-Sánchez D, Marcos-Gragera R, Carulla M, Lopez de Munain A, Sabater Gregori C, Jimenez Chillarón R, Guevara M, Nuñez O, Fernández-Navarro P, Sánchez M-J, Luque-Fernandez MA. Lung, Breast and Colorectal Cancer Incidence by Socioeconomic Status in Spain: A Population-Based Multilevel Study [Internet]. Cancers 2021;13(11) Publisher's VersionAbstract
Socioeconomic inequalities in cancer incidence are not well documented in southern Europe. We aim to study the association between socioeconomic status (SES) and colorectal, lung, and breast cancer incidence in Spain. We conducted a multilevel study using data from Spanish population-based cancer registries, including incident cases diagnosed for the period 2010–2013 in nine Spanish provinces. We used Poisson mixed-effects models, including the census tract as a random intercept, to derive cancer incidence rate ratios by SES, adjusted for age and calendar year. Male adults with the lowest SES, compared to those with the highest SES, showed weak evidence of being at increased risk of lung cancer (risk ratio (RR): 1.18, 95% CI: 0.94–1.46) but showed moderate evidence of being at reduced risk of colorectal cancer (RR: 0.84, 95% CI: 0.74–0.97). Female adults with the lowest SES, compared to those with the highest SES, showed strong evidence of lower breast cancer incidence with 24% decreased risk (RR: 0.76, 95% CI: 0.68–0.85). Among females, we did not find evidence of an association between SES and lung or colorectal cancer. The associations found between SES and cancer incidence in Spain are consistent with those obtained in other European countries.
Lee SF, Nikšić M, Rachet B, Sanchez M-J, Luque-Fernandez MA. Socioeconomic Inequalities and Ethnicity Are Associated with a Positive COVID-19 Test among Cancer Patients in the UK Biobank Cohort [Internet]. Cancers 2021;13(7) Publisher's VersionAbstract
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.
Bouvier A-M, Jooste V, Sanchez-Perez MJ, Bento MJ, Rodrigues JR, Marcos-Gragera R, Carmona-Garcia MC, Luque-Fernandez MA, Minicozzi P, Bouvier V, Innos K, Sant M, Eycken LV, Henau K, Grozeva T, Valerianova Z, Innos K, Mägi M, Bouvier V, Launoy G, Robaszkiewicz M, Bouvier AM, Jooste V, Babaev V, Katalinic A, Ólafsdóttir EJ, Tryggvadóttir L, Amati C, Baili P, Bonfarnuzzo S, Margutti C, Meneghini E, Minicozzi P, Moretti G, Sant M, Cirilli C, Carrozzi G, Spata E, Tumino R, Rossi PG, Vicentini M, Stracci F, Bianconi F, Contiero P, Tagliabue G, Kycler W, Oko M, Macek P, Smok-Kalwat J, Bielska-Lasota M, Kycler W, Oko M, Bento MJ, Rodrigues J, Mayer-da-Silva A, Miranda A, Primic-Žakelj M, Jarm K, Almar E, Mateos A, Bidaurrazaga J, De La Cruz M, Alberich C, Torrella-Ramos A, García JMD, Marcos-Navarro AI, Carmona-Garcia C, Marcos-Gragera R, Luque-Fernandez MA, Sánchez-Pérez MJ, Ardanaz E, Guevara M, Bouchardy C, Fournier E. Differences in the management and survival of metastatic colorectal cancer in Europe. A population-based study [Internet]. Digestive and Liver Disease 2021; Publisher's VersionAbstract
Background The management regarding metastatic colorectal cancer throughout Europe is not well known. Aims To draw a European comparison of the management and prognosis of metastatic colorectal cancers. Methods 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. Results 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 (P<0.001) 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 patients <70 or ≥80 years at diagnosis. Conclusion 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.
Abdollahpour I, Nedjat S, Almasi-Hashiani A, Nazemipour M, Mansournia MA, Luque-Fernandez MA. Estimating the Marginal Causal Effect and Potential Impact of Waterpipe Smoking on Multiple Sclerosis Using Targeted Maximum Likelihood Estimation Method: a Large Population-Based Incident Case-Control Study [Internet]. American Journal of Epidemiology 2021; Publisher's VersionAbstract
There are few if any reports regarding the role of lifetime waterpipe smoking in multiple sclerosis (MS) etiology. The authors investigated the association between waterpipe and MS, adjusted for confounders. This was a population-based incident case-control study conducted in Tehran, Iran. Cases (n=547) were 15–50-year-old patients identified from the Iranian Multiple Sclerosis Society between 2013 and 2015. Population-based controls (n=1057) were 15–50-year old recruited by random digit telephone dialing. A double robust estimator method known as targeted maximum likelihood estimator (TMLE) was used to estimate the marginal risk ratio and odds ratio between waterpipe and MS. The both estimated RR and OR was 1.70 (95% CI: 1.34, 2.17). The population attributable fraction was 21.4% (95% CI: 4.0%, 38.8%). Subject to the limitations of case-control studies in interpreting associations causally, this study suggests that waterpipe use, or its strongly related but undetermined factors, increases the risk of MS. Further epidemiological studies including nested case-control studies are needed to confirm these results.

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