Inequalities in treatment among patients with colon and rectal cancer: a multistate survival model using data from England national cancer registry 2012-2016.

BACKGROUND: Individual and tumour factors only explain part of observed inequalities in colorectal cancer survival in England. This study aims to investigate inequalities in treatment in patients with colorectal cancer. METHODS: All patients diagnosed with colorectal cancer in England between 2012 and 2016 were followed up from the date of diagnosis (state 1), to treatment (state 2), death (state 3) or censored at 1 year after the diagnosis. A multistate approach with flexible parametric model was used to investigate the effect of income deprivation on the probability of remaining alive and treated in colorectal cancer. RESULTS: Compared to the least deprived quintile, the most deprived with stage I-IV colorectal cancer had a lower probability of being alive and treated at all the time during follow-up, and a higher probability of being untreated and of dying. The probability differences (most vs. least deprived) of being alive and treated at 6 months ranged between -2.4% (95% CI: -4.3, -1.1) and -7.4% (-9.4, -5.3) for colon; between -2.0% (-3.5, -0.4) and -6.2% (-8.9, -3.5) for rectal cancer. CONCLUSION: Persistent inequalities in treatment were observed in patients with colorectal cancer at every stage, due to delayed access to treatment and premature death.

Incident Cardiovascular Diseases Among Survivors of High-Risk Stage II-III Colorectal Cancer: A Cluster-Wide Cohort Study.

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.

Bayesian variable selection and survival modeling: assessing the Most important comorbidities that impact lung and colorectal cancer survival in Spain.

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 .

Estimating the Marginal Causal Effect and Potential Impact of Waterpipe Smoking on Risk of Multiple Sclerosis Using the Targeted Maximum Likelihood Estimation Method: A Large, Population-Based Incident Case-Control Study.

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.

The role of multimorbidity in short-term mortality of lung cancer patients in Spain: a population-based cohort study.

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.

Comorbidity prevalence among cancer patients: a population-based cohort study of four cancers.

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.

Association between age, deprivation and specific comorbid conditions and the receipt of major surgery in patients with non-small cell lung cancer in England: A population-based study.

INTRODUCTION: We investigated socioeconomic disparities and the role of the main prognostic factors in receiving major surgical treatment in patients with lung cancer in England. METHODS: Our study comprised 31 351 patients diagnosed with non-small cell lung cancer in England in 2012. Data from the national population-based cancer registry were linked to Hospital Episode Statistics and National Lung Cancer Audit data to obtain information on stage, performance status and comorbidities, and to identify patients receiving major surgical treatment. To describe the association between prognostic factors and surgery, we performed two different analyses: one using multivariable logistic regression and one estimating cause-specific hazards for death and surgery. In both analyses, we used multiple imputation to deal with missing data. RESULTS: We showed strong evidence that the comorbidities 'congestive heart failure', 'cerebrovascular disease' and 'chronic obstructive pulmonary disease' reduced the receipt of surgery in early stage patients. We also observed gender differences and substantial age differences in the receipt of surgery. Despite accounting for sex, age at diagnosis, comorbidities, stage at diagnosis, performance status and indication of having had a PET-CT scan, the socioeconomic differences persisted in both analyses: more deprived people had lower odds and lower rates of receiving surgery in early stage lung cancer. DISCUSSION: Comorbidities play an important role in whether patients undergo surgery, but do not completely explain the socioeconomic difference observed in early stage patients. Future work investigating access to and distance from specialist hospitals, as well as patient perceptions and patient choice in receiving surgery, could help disentangle these persistent socioeconomic inequalities.

Secular trends in stillbirth by maternal socioeconomic status in Spain 2007-15: a population-based study of 4 million births.

INTRODUCTION: Stillbirth, one of the urgent concerns of preventable perinatal deaths, has wide-reaching consequences for society. We studied secular stillbirth trends by maternal socioeconomic status (SES) in Spain. METHODS: We developed a population-based observational study, including 4 083 919 births during 2007-15. We estimate stillbirth rates and secular trends by maternal SES. We also evaluated the joint effect of maternal educational attainment and the Human Development Index (HDI) of women's country of origin on the risk of stillbirth. The data and statistical analysis can be accessed for reproducibility in a GitHub repository: https://github.com/migariane/Stillbirth. RESULTS: We found a consistent pattern of socioeconomic inequalities in the risk of delivering a stillborn, mainly characterized by a persistently higher risk, over time, among women with lower SES. Overall, women from countries with low HDIs and low educational attainments had approximately a four times higher risk of stillbirth (RR: 4.44; 95%CI: 3.71-5.32). Furthermore, we found a paradoxical reduction of the stillbirth gap over time between the highest and the lowest SESs, which is mostly due to the significant and increasing trend of stillbirth risk among highly educated women of advanced maternal age. CONCLUSION: Our findings highlight no improvement in stillbirth rates among women of lower SES and an increasing trend among highly educated women of advanced maternal age over recent years. Public health policies developing preventive programmes to reduce stillbirth rates among women with lower SES are needed as well as the necessity of further study to understand the growing trend of age-related stillbirths among highly educated women in Spain.

Data-Adaptive Estimation for Double-Robust Methods in Population-Based Cancer Epidemiology: Risk Differences for Lung Cancer Mortality by Emergency Presentation.

In this paper, we propose a structural framework for population-based cancer epidemiology and evaluate the performance of double-robust estimators for a binary exposure in cancer mortality. We conduct numerical analyses to study the bias and efficiency of these estimators. Furthermore, we compare 2 different model selection strategies based on 1) Akaike's Information Criterion and the Bayesian Information Criterion and 2) machine learning algorithms, and we illustrate double-robust estimators' performance in a real-world setting. In simulations with correctly specified models and near-positivity violations, all but the naive estimators had relatively good performance. However, the augmented inverse-probability-of-treatment weighting estimator showed the largest relative bias. Under dual model misspecification and near-positivity violations, all double-robust estimators were biased. Nevertheless, the targeted maximum likelihood estimator showed the best bias-variance trade-off, more precise estimates, and appropriate 95% confidence interval coverage, supporting the use of the data-adaptive model selection strategies based on machine learning algorithms. We applied these methods to estimate adjusted 1-year mortality risk differences in 183,426 lung cancer patients diagnosed after admittance to an emergency department versus persons with a nonemergency cancer diagnosis in England (2006-2013). The adjusted mortality risk (for patients diagnosed with lung cancer after admittance to an emergency department) was 16% higher in men and 18% higher in women, suggesting the importance of interventions targeting early detection of lung cancer signs and symptoms.

Targeted maximum likelihood estimation for a binary treatment: A tutorial.

When estimating the average effect of a binary treatment (or exposure) on an outcome, methods that incorporate propensity scores, the G-formula, or targeted maximum likelihood estimation (TMLE) are preferred over naïve regression approaches, which are biased under misspecification of a parametric outcome model. In contrast propensity score methods require the correct specification of an exposure model. Double-robust methods only require correct specification of either the outcome or the exposure model. Targeted maximum likelihood estimation is a semiparametric double-robust method that improves the chances of correct model specification by allowing for flexible estimation using (nonparametric) machine-learning methods. It therefore requires weaker assumptions than its competitors. We provide a step-by-step guided implementation of TMLE and illustrate it in a realistic scenario based on cancer epidemiology where assumptions about correct model specification and positivity (ie, when a study participant had 0 probability of receiving the treatment) are nearly violated. This article provides a concise and reproducible educational introduction to TMLE for a binary outcome and exposure. The reader should gain sufficient understanding of TMLE from this introductory tutorial to be able to apply the method in practice. Extensive R-code is provided in easy-to-read boxes throughout the article for replicability. Stata users will find a testing implementation of TMLE and additional material in the Appendix S1 and at the following GitHub repository: https://github.com/migariane/SIM-TMLE-tutorial.

Prevalence and risk factors of gestational diabetes mellitus: findings from a universal screening feasibility program in Lima, Peru.

BACKGROUND: Gestational diabetes mellitus (GDM) is a global public health concern with potential implications for the health of a mother and her offspring. However, data on the prevalence and risk factors of GDM in Latin America are scarce. The study was designed to estimate the prevalence of GDM and identify maternal risk factors among Peruvian women. METHODS: A cross-sectional study was conducted among 1300 pregnant women attending a prenatal clinic in Lima, Peru. GDM was diagnosed using an Oral Glucose Tolerance Test (OGTT) performed between 24 and 28 gestational weeks using the International Association of Diabetes and Pregnancy Study Groups (IADPSG) criteria. Depression status was assessed using the Patient Health Questionnaire-9. Multivariate logistic regression models were used to identify risk factors of GDM. RESULTS: Approximately 16% of pregnant women were diagnosed with GDM. The prevalence of obesity and depression were 24.4 and 10.6%, respectively. After adjusting for confounders, mid-pregnancy obesity was associated with a 1.64-fold increased odds of GDM (OR: 1.64; 95% CI: 1.03-2.61). Participants with a family history of diabetes had a 1.5-fold increased odds of developing GDM (OR: 1.51, 95% CI: 1.10-2.07) as compared to women without this family history. Depression was associated with a 1.54-fold increased odds of GDM (OR: 1.54; 95% CI:1.09-2.17). CONCLUSIONS: GDM is highly prevalent and was associated with maternal obesity, family history of diabetes and antepartum depression among Peruvian women. Intervention programs aimed at early diagnoses and management of GDM need to take maternal obesity, family history of diabetes and antepartum depression into account.

The Spectrum of Subclinical Primary Aldosteronism and Incident Hypertension: A Cohort Study.

BACKGROUND: Primary aldosteronism is recognized as a severe form of renin-independent aldosteronism that results in excessive mineralocorticoid receptor (MR) activation. OBJECTIVE: To investigate whether a spectrum of subclinical renin-independent aldosteronism that increases risk for hypertension exists among normotensive persons. DESIGN: Cohort study. SETTING: National community-based study. PARTICIPANTS: 850 untreated normotensive participants in MESA (Multi-Ethnic Study of Atherosclerosis) with measurements of serum aldosterone and plasma renin activity (PRA). MEASUREMENTS: Longitudinal analyses investigated whether aldosterone concentrations, in the context of physiologic PRA phenotypes (suppressed, ≤0.50 µg/L per hour; indeterminate, 0.51 to 0.99 µg/L per hour; unsuppressed, ≥1.0 µg/L per hour), were associated with incident hypertension (defined as systolic blood pressure ≥140 mm Hg, diastolic blood pressure ≥90 mm Hg, or initiation of antihypertensive medications). Cross-sectional analyses investigated associations between aldosterone and MR activity, assessed via serum potassium and urinary fractional excretion of potassium. RESULTS: A suppressed renin phenotype was associated with a higher rate of incident hypertension than other PRA phenotypes (incidence rates per 1000 person-years of follow-up: suppressed renin phenotype, 85.4 events [95% CI, 73.4 to 99.3 events]; indeterminate renin phenotype, 53.3 events [CI, 42.8 to 66.4 events]; unsuppressed renin phenotype, 54.5 events [CI, 41.8 to 71.0 events]). With renin suppression, higher aldosterone concentrations were independently associated with an increased risk for incident hypertension, whereas no association between aldosterone and hypertension was seen when renin was not suppressed. Higher aldosterone concentrations were associated with lower serum potassium and higher urinary excretion of potassium, but only when renin was suppressed. LIMITATION: Sodium and potassium were measured several years before renin and aldosterone. CONCLUSION: Suppression of renin and higher aldosterone concentrations in the context of this renin suppression are associated with an increased risk for hypertension and possibly also with increased MR activity. These findings suggest a clinically relevant spectrum of subclinical primary aldosteronism (renin-independent aldosteronism) in normotension. PRIMARY FUNDING SOURCE: National Institutes of Health.

"Nonfunctional" Adrenal Tumors and the Risk for Incident Diabetes and Cardiovascular Outcomes: A Cohort Study.

BACKGROUND: Benign adrenal tumors are commonly discovered on abdominal imaging. Most are classified as nonfunctional and are considered to pose no health risk, but some are considered functional because they secrete hormones that increase risk for metabolic and cardiovascular diseases. OBJECTIVE: To evaluate the hypothesis that nonfunctional adrenal tumors (NFATs) increase risk for cardiometabolic outcomes compared with absence of adrenal tumors. DESIGN: Cohort study. SETTING: Integrated hospital system. PARTICIPANTS: Participants with benign NFATs ("exposed"; n = 166) and those with no adrenal tumor ("unexposed"; n = 740), with at least 3 years of follow-up. MEASUREMENTS: Medical records were reviewed from the time of abdominal imaging for development of incident outcomes (hypertension, composite diabetes [prediabetes or type 2 diabetes], hyperlipidemia, cardiovascular events, and chronic kidney disease) (mean, 7.7 years). Primary analyses evaluated independent associations between exposure status and incident outcomes by using adjusted generalized linear models. Secondary analyses evaluated relationships between NFATs and cortisol physiology. RESULTS: Participants with NFATs had significantly higher risk for incident composite diabetes than those without adrenal tumors (30 of 110 [27.3%] vs. 72 of 615 [11.7%] participants; absolute risk, 15.6% [95% CI, 6.9% to 24.3%]; adjusted risk ratio, 1.87 [CI, 1.17 to 2.98]). No significant associations between NFATs and other outcomes were observed. Higher "normal" postdexamethasone cortisol levels (≤50 nmol/L) were associated with larger NFAT size and higher prevalence of type 2 diabetes. LIMITATION: Potential bias in the selection of participants and ascertainment of outcomes. CONCLUSION: Participants with NFATs had a significantly higher risk for diabetes than those without adrenal tumors. These results should prompt a reassessment of whether the classification of benign adrenal tumors as "nonfunctional" adequately reflects the continuum of hormone secretion and metabolic risk they may harbor. PRIMARY FUNDING SOURCE: National Institutes of Health and Doris Duke Charitable Foundation.

Adjusting for overdispersion in piecewise exponential regression models to estimate excess mortality rate in population-based research.

BACKGROUND: In population-based cancer research, piecewise exponential regression models are used to derive adjusted estimates of excess mortality due to cancer using the Poisson generalized linear modelling framework. However, the assumption that the conditional mean and variance of the rate parameter given the set of covariates x i are equal is strong and may fail to account for overdispersion given the variability of the rate parameter (the variance exceeds the mean). Using an empirical example, we aimed to describe simple methods to test and correct for overdispersion. METHODS: We used a regression-based score test for overdispersion under the relative survival framework and proposed different approaches to correct for overdispersion including a quasi-likelihood, robust standard errors estimation, negative binomial regression and flexible piecewise modelling. RESULTS: All piecewise exponential regression models showed the presence of significant inherent overdispersion (p-value <0.001). However, the flexible piecewise exponential model showed the smallest overdispersion parameter (3.2 versus 21.3) for non-flexible piecewise exponential models. CONCLUSION: We showed that there were no major differences between methods. However, using a flexible piecewise regression modelling, with either a quasi-likelihood or robust standard errors, was the best approach as it deals with both, overdispersion due to model misspecification and true or inherent overdispersion.

Deconstructing the smoking-preeclampsia paradox through a counterfactual framework.

Although smoking during pregnancy may lead to many adverse outcomes, numerous studies have reported a paradoxical inverse association between maternal cigarette smoking during pregnancy and preeclampsia. Using a counterfactual framework we aimed to explore the structure of this paradox as being a consequence of selection bias. Using a case-control study nested in the Icelandic Birth Registry (1309 women), we show how this selection bias can be explored and corrected for. Cases were defined as any case of pregnancy induced hypertension or preeclampsia occurring after 20 weeks' gestation and controls as normotensive mothers who gave birth in the same year. First, we used directed acyclic graphs to illustrate the common bias structure. Second, we used classical logistic regression and mediation analytic methods for dichotomous outcomes to explore the structure of the bias. Lastly, we performed both deterministic and probabilistic sensitivity analysis to estimate the amount of bias due to an uncontrolled confounder and corrected for it. The biased effect of smoking was estimated to reduce the odds of preeclampsia by 28 % (OR 0.72, 95 %CI 0.52, 0.99) and after stratification by gestational age at delivery (<37 vs. ≥37 gestation weeks) by 75 % (OR 0.25, 95 %CI 0.10, 0.68). In a mediation analysis, the natural indirect effect showed and OR > 1, revealing the structure of the paradox. The bias-adjusted estimation of the smoking effect on preeclampsia showed an OR of 1.22 (95 %CI 0.41, 6.53). The smoking-preeclampsia paradox appears to be an example of (1) selection bias most likely caused by studying cases prevalent at birth rather than all incident cases from conception in a pregnancy cohort, (2) omitting important confounders associated with both smoking and preeclampsia (preventing the outcome to develop) and (3) controlling for a collider (gestation weeks at delivery). Future studies need to consider these aspects when studying and interpreting the association between smoking and pregnancy outcomes.

Fasting lipid and lipoproteins concentrations in pregnant women with a history of migraine.

BACKGROUND: Migraine is associated with a number of cardiometabolic risk factors including abnormalities in lipid metabolism. However, little is known about these associations among pregnant migraineurs. We conducted the present study to evaluate the extent to which altered lipid profiles are associated with history of migraine among pregnant women. METHODS: A cohort of 1062 Peruvian women were interviewed at 24-28 weeks of gestation. Migraine status was classified based on the International Classification of Headache Disorders-II diagnostic criteria. Serum lipid concentrations were measured enzymatically using standardized assays. Multivariable logistic regression was used to estimate adjusted odds ratios (AORs) and 95% confidence intervals (CIs) as measures of associations of migraine status with varying concentrations of lipids and lipoproteins during pregnancy. RESULTS: Approximately 18.5% of the study participants were identified as migraineurs (196 of 1062). Maternal serum total cholesterol, high-density lipoprotein (HDL), low-density lipoprotein (LDL), triglycerides, and total cholesterol : HDL ratio were all statistically significantly elevated among pregnant migraineurs compared with pregnant non-migraineurs. In multivariate adjusted models, pregnant women with migraine had higher odds of elevated total cholesterol, LDL, and total cholesterol : HDL ratio as compared with pregnant women without migraine. For instance, the AOR and 95% CI for successive quartiles of the total cholesterol associated with history of migraine were Q2 (219-247 mg/dL): 1.05 (0.64-1.70), Q3 (248-281 mg/dL): 1.16 (0.72-1.86), and Q4 (≥282 mg/dL): 1.87 (1.20-2.91) with the lowest quartile (<219 mg/dL) as the referent group (P value for trend = .003). Obese women with elevated total cholesterol (≥282 mg/dL) were more likely to be migraineurs (OR = 3.71; 95% CI 1.58-8.71) as compared with non-obese women with lower total cholesterol (<219 mg/dL). Similar elevated odds of migraine were observed for obese women with elevated LDL cholesterol, elevated triglycerides and high total cholesterol : HDL ratio. CONCLUSION: Pregnant migraineurs had elevated odds of dyslipidemia, particularly hypercholesterolemia, elevated LDL, and total cholesterol : HDL ratio as compared with pregnant non-migraineurs. The observed associations were more pronounced among obese migraineurs. Our findings add to the accumulating evidence of adverse cardiometabolic risk profiles among migraineurs and extend these associations to pregnant women.

Is the fetoplacental ratio a differential marker of fetal growth restriction in small for gestational age infants?

Higher placental weight relative to birthweight has been described as an adaptive mechanism to fetal hypoxia in small for gestational age (SGA) infants. However, placental weight alone may not be a good marker reflecting intrauterine growth restriction. We hypothesized that fetoplacental ratio (FPR)-the ratio between birthweight and placental weight-may serve as a good marker of SGA after adjustment for surrogates of fetal hypoxemia (maternal iron deficiency anemia, smoking and choriodecidual necrosis). We conducted a within-sibling analysis using data from the US National Collaborative Perinatal Project (1959-1966) of 1,803 women who delivered their first two (or more) consecutive infants at term (n = 3,494). We used variance-component fixed-effect linear regression models to explore the effect of observed time-varying factors on placental weight and conditional logistic regression to estimate the effects of the tertiles of FPRs (1st small, 2nd normal and 3rd large) on the odds of SGA infants. We found placental weights to be 15 g [95 % confidence interval (CI) 8, 23] higher and -7 g (95 % CI -13, -2) lower among women that had anemia and choriodecidual necrosis, respectively. After multivariable adjustment, newborns with a small FPR (1st-tertile ≤7) had twofold higher odds of being SGA (OR 2.0, 95 % CI 1.2, 3.5) than their siblings with a large FPR (3nd-tertile ≥9). A small FPR was associated with higher odds of SGA, suggesting that small FPR may serve as an indicator suggestive of adverse intrauterine environment. This observation may help to distinguish pathological from constitutional SGA.

High risk for obstructive sleep apnea and other sleep disorders among overweight and obese pregnant women.

BACKGROUND: Obstructive sleep apnea (OSA), a common and serious disorder in which breathing repeatedly stops during sleep, is associated with excess weight and obesity. Little is known about the co-occurrence of OSA among pregnant women from low and middle-income countries. METHODS: We examined the extent to which maternal pre-pregnancy overweight or obesity status are associated with high risk for OSA, poor sleep quality, and excessive daytime sleepiness in 1032 pregnant women in Lima, Peru. The Berlin questionnaire was used to identify women at high risk for OSA. The Pittsburgh Sleep Quality Index (PSQI) and Epworth Sleepiness Scale (ESS) were used to examine sleep quality and excessive daytime sleepiness, respectively. Multinomial logistic regression procedures were employed to estimate odds ratios (aOR) and 95% confidence intervals (CI) adjusted for putative confounding factors. RESULTS: Compared with lean women (<25 kg/m(2)), overweight women (25-29.9 kg/m(2)) had 3.69-fold higher odds of high risk for OSA (95% CI 1.82-7.50). The corresponding aOR for obese women (≥30 kg/m(2)) was 13.23 (95% CI: 6.25-28.01). Obese women, as compared with their lean counterparts had a 1.61-fold higher odds of poor sleep quality (95% CI: 1.00-2.63). CONCLUSION: Overweight or obese pregnant women have increased odds of sleep disorders, particularly OSA. OSA screening and risk management may be indicated among pregnant women in low and middle income countries, particularly those undergoing rapid epidemiologic transitions characterized by increased prevalence of excessive adult weight gain.

Assessment of tuberculosis surveillance by capture-recapture in the Balearic Islands, Spain, 2005-2007.

The tuberculosis surveillance system in the Balearic Islands was assessed from 2005 to 2007. Applying the capture-recapture method the completeness of this system was evaluated to be 58.4%. When a new electronic recorded data was included in Primary Health Care, up to 66.5% was obtained. This new source of data increased the detected cases of pulmonary tuberculosis from 572 to 681. As a result, the estimated annual incidence rate increases from 18.9 cases/10(5) to 22.6 cases/10(5) [95% CI, 20.9-24.3], similar to figures issued by WHO.