Explore the vast range of titles available.

Diabetic nephropathy (DN) is a serious complication of diabetes mellitus. A high level of neutrophil-lymphocyte ratio (NLR) is an indicator of abnormal immune system activity which may serve as an effective potential inflammatory marker for identifying the risk of DN. This study aimed to investigate the relationship between neutrophil-lymphocyte ratio (NLR) and the incidence of DN in type 2 diabetes mellitus (T2DM) patients. DN incidence was defined as the time from baseline diabetes diagnosis to first DN occurrence (KDIGO CKD criteria). NLR's effect and interactions were evaluated using covariate-adjusted competing risks regression (death as competing event). The optimal NLR cut-point for DN prediction was determined by ROC analysis. The Fine and Gray subdistribution hazard model assessed NLR's effect on DN incidence, with subdistribution hazard ratios (sHR) validated via bootstrap sampling. The final sample consisted of the records of 220 individuals (median age 64 years (IQR: 55-72)) with T2DM with complete covariates information which were available for incidence analysis with NLR. Among 220 T2DM patients with complete covariates, 133 (60.45%) developed DN at 6 years, 20 (9.10%) were lost to competing events, and 67 remained DN-free. Median NLR was 2.4 (IQR: 1.8-3.3), positively correlating with urinary albumin-to-creatinine ratio and negatively with the estimated glomerular filtration rate (eGFR) ( <0.01). ROC analysis demonstrated diagnostic value for DN (AUC=0.772; 95% CI: 0.708, 0.836; <0.01), with optimal cut-off at 3.02. NLR showed associations with DN in cause-specific (CSH=1.66; 95% CI: 1.13, 2.52) and FGR models (sHR=2.26; 95% CI: 1.72, 2.92). Bootstrap validation yielded consistent results (sHR= 2.36; 95% CI: 1.76, 3.02). Notably, NLR better predicts DN risk in older adults (>65 years) and those with well-controlled HbA1c (≤7.5%). NLR shows promise for predicting DN incidence in Chinese patients, especially those >65 years or with good glycemic control.

Background Diabetic retinopathy (DR) is a major sight-threatening microvascular complication in individuals with diabetes. Systemic inflammation combined with oxidative stress is thought to capture most of the complexities involved in the pathology of diabetic retinopathy. A high level of neutrophil–lymphocyte ratio (NLR) is an indicator of abnormal immune system activity. Current estimates of the association of NLR with diabetes and its complications are almost entirely derived from cross-sectional studies, suggesting that the nature of the reported association may be more diagnostic than prognostic. Therefore, in the present study, we examined the utility of NLR as a biomarker to predict the incidence of DR in the Scottish population. Methods The incidence of DR was defined as the time to the first diagnosis of R1 or above grade in the Scottish retinopathy grading scheme from type 2 diabetes diagnosis. The effect of NLR and its interactions were explored using a competing risks survival model adjusting for other risk factors and accounting for deaths. The Fine and Gray subdistribution hazard model (FGR) was used to predict the effect of NLR on the incidence of DR. Results We analysed data from 23,531 individuals with complete covariate information. At 10 years, 8416 (35.8%) had developed DR and 2989 (12.7%) were lost to competing events (death) without developing DR and 12,126 individuals did not have DR. The median (interquartile range) level of NLR was 2.04 (1.5 to 2.7). The optimal NLR cut-off value to predict retinopathy incidence was 3.04. After accounting for competing risks at 10 years, the cumulative incidence of DR and deaths without DR were 50.7% and 21.9%, respectively. NLR was associated with incident DR in both Cause-specific hazard (CSH = 1.63; 95% CI: 1.28–2.07) and FGR models the subdistribution hazard (sHR = 2.24; 95% CI: 1.70–2.94). Both age and HbA 1c were found to modulate the association between NLR and the risk of DR. Conclusions The current study suggests that NLR has a promising potential to predict DR incidence in the Scottish population, especially in individuals less than 65 years and in those with well-controlled glycaemic status.

In the presence of competing risks, when the baseline risk is unclear, if only the sub-distribution hazard ratio (SHR) is reported in the results, which is related to the cumulative incidence function, the survival disparity of events of interest between groups cannot be clarified. In contrast, the difference in restricted mean time lost (RMTLd), which is the difference in the areas under the cumulative incidence between two groups, can well compensate for the deficiencies of SHR and explain the effects on a time scale, facilitating clinical interpretation and communication. The Surveillance, Epidemiology, and End Results (SEER) database was used to collect information on female patients with locally advanced breast cancer diagnosed between 2010 and 2015. The prognostic factors of breast cancer death were evaluated considering competing risk. Univariable and multivariable analyses were conducted to get SHR and RMTLd. SHR can indicate the direction of prognostic factors, while RMTLd can quantify prognostic effects and provide time-scale interpretation. For instance, in adjuvant radiotherapy, the SHR showed a protective effect, which can be quantified as an average increase of 4.15 months in survival time. In the presence of competing risks, the combined use of absolute measure RMTLd can more intuitively explain the prognostic effect, which is convenient for clinical practice and communication.

Randomized controlled trials (RCTs) are criticized for including patients who are overselected. Health authorities consequently encourage “real-world” postmarketing cohort studies. Our objective was to determine the differences between RCTs and observational studies as regards their populations and efficacy/safety results. A systematic review was conducted to identify RCTs and observational studies including patients with venous thromboembolism receiving direct oral anticoagulants or conventional treatment. Ratios of hazard ratio (RHR) comparing epidemiological studies (prospective and retrospective cohort studies and studies using living databases) with RCTs were computed. Six RCTs (27,121 patients) and twenty observational studies (248,971 patients) were identified and analyzed. Prospective cohort studies seemed to recruit patients who were no less selected than those of RCTs whereas other types of observational studies may reflect the population treated in real life. Among observational studies, prospective cohort studies yielded the most favorable estimates of treatment effect compared with RCTs. These studies were associated with a nonsignificant 33% increase in efficacy estimate (RHR 0.67, [95% CI, 0.39–1.18]) but no effect on safety estimate. Studies using living databases were associated with nonsignificant trends toward a greater effect on efficacy (RHR 0.82, [0.66–1.01]) and a smaller effect on safety (RHR 1.33, [0.96–1.84]). Overall, in this clinical setting, an exaggeration of the treatment efficacy estimate was seen with observational studies compared with RCTs. As the presence of residual confounding cannot be excluded, these results should be interpreted cautiously.

The absolute standardized hazard ratio (ASHR) is a scale-invariant scalar measure of the strength of association of a vector of covariates with the risk of an event. It is derived from proportional hazards regression. The ASHR is useful for making comparisons among different sets of covariates. Extensions of the ASHR concept and practical considerations regarding its computation are discussed. These include a new method to conduct preliminary checks for collinearity among covariates, a partial ASHR to evaluate the association with event risk of some of the covariates conditioning on others, and the ASHR for interactions. To put the ASHR in context, its relationship to measures of explained variation and other measures of separation of risk is discussed. A new measure of the contribution of each covariate to the risk score variance is proposed. This measure, which is derived from the ASHR calculations, is interpretable as variable importance within the context of the multivariable model.

Associations between an exposure and multiple competing events are typically described by cause-specific hazard ratios (csHR) or subdistribution hazard ratios (sHR). However, diagnostic tools to assess differences between them have not been described. Under the proportionality assumption for both, it can be shown mathematically that the sHR and csHR must be equal, so reporting different time-constant sHR and csHR implies non-proportionality for at least one. We propose a simple, intuitive approach using the ratio of sHR/csHR to nonparametrically compare these metrics. In general, for the non-null case, there must be at least one event type for which the sHR and csHR differ, and the proposed diagnostic will be useful to identify these cases. Furthermore, once standard methods are used to estimate the csHR, multiplying it with our nonparametric estimate for the sHR/csHR ratio will yield estimates of sHR which fulfill intrinsic linkages of the subhazards that separate analysis may violate. In addition, for non-null cases, at least one must be time dependent (i.e., non-proportional), and thus our tool serves as an indirect test of the proportionality assumption. We applied this proposed diagnostic tool to data from a cohort of children with congenital kidney disease to describe racial differences in the time to first dialysis or first transplant and extend methods to include adjustment for socioeconomic factors.

There has arisen a considerable body of research addressing the estimation of association between paired failure times in the presence of competing risks. In a 2002 paper, Bandeen-Roche and Liang proposed the conditional cause-specific hazard ratio (CCSHR) as a measure of this association and a parametric method by which to estimate it. The method features an interpretable decomposition of the CCSHR into factors describing the association between a pair’s times to first failure among multiple failure causes and the association in pair members’ propensities to fail due to a common cause. There were indications of sensitivity to model assumptions, however, in the 2002 work. Here we report a detailed study of the method’s sensitivity to its parametric assumptions. We conclude that the method’s performance is most sensitive to mis-specification of temporality in the association between pair members’ first-failure times and of correlation between propensity to fail early or late and the propensity to fail of a specific cause. Implications for methods development are highlighted.

Background: The aim of this study was to clarify any gender differences in the mortality risk of people with DFD since patients with diabetic foot disease (DFD) are at a high risk of mortality and, at the same time, are more likely to be men. Methods: From regional administrative sources, the survival probability was retrospectively evaluated by the Kaplan-Meier method and using the Cox proportional-hazards model comparing people with DFD to those without DFD across the years 2011–2018 in Tuscany, Italy. Gender difference in mortality was evaluated by the ratio of hazard ratios (RHR) of men to women after initial DFD hospitalizations (n = 11,529) or in a cohort with prior history of DFD hospitalizations (n = 11,246). Results: In both cohorts, the survival probability after DFD was lower among women. Compared to those without DFD, after initial DFD hospitalizations, the mortality risk was significantly (18%) higher for men compared to women. This excess risk was particularly high after major amputations but also after ulcers, infections, gangrene, or Charcot, with a lower reduction after revascularization procedures among men. In the cohort that included people with a history of prior DFD hospitalizations, except for the risk of minor amputations being higher for men, there was no gender difference in mortality risk. Conclusions: In people with DFD, the overall survival probability was lower among women. Compared to those without DFD after a first DFD hospitalization, men were at higher risk of mortality. This excess risk disappeared in groups with a history of previous DFD hospitalizations containing a greater percentage of women who were older and probably had a longer duration of diabetes and thus becoming, over time, progressively frailer than men.

Since previous meta-analyses, which were limited only to depression and by a small number of studies available for inclusion at the time of publication, several additional studies have been published assessing the link between ultra-processed food consumption and depression as well as other mental disorders. We aimed to build on previously conducted reviews to synthesise and meta-analyse the contemporary evidence base and clarify the associations between the consumption of ultra-processed food and mental disorders. A total of 17 observational studies were included (n = 385,541); 15 cross-sectional and 2 prospective. Greater ultra-processed food consumption was cross-sectionally associated with increased odds of depressive and anxiety symptoms, both when these outcomes were assessed together (common mental disorder symptoms odds ratio: 1.53, 95%CI 1.43 to 1.63) as well as separately (depressive symptoms odds ratio: 1.44, 95%CI 1.14 to 1.82; and, anxiety symptoms odds ratio: 1.48, 95%CI 1.37 to 1.59). Furthermore, a meta-analysis of prospective studies demonstrated that greater ultra-processed food intake was associated with increased risk of subsequent depression (hazard ratio: 1.22, 95%CI 1.16 to 1.28). While we found evidence for associations between ultra-processed food consumption and adverse mental health, further rigorously designed prospective and experimental studies are needed to better understand causal pathways.

ObjectiveIntestinal inflammation has been suggested to play a role in development of Parkinson’s disease (PD) and multiple system atrophy (MSA). To test the hypothesis that IBD is associated with risk of PD and MSA, we performed a nationwide population-based cohort study.DesignThe cohort consisted of all individuals diagnosed with IBD in Denmark during 1977–2014 (n=76 477) and non-IBD individuals from the general population, who were comparable in terms of gender, age and vital status (n=7 548 259). All cohort members were followed from IBD diagnosis/index date to occurrence of PD and MSA (according to the Danish National Patient Register).ResultsPatients with IBD had a 22% increased risk of PD as compared with non-IBD individuals (HR=1.22; 95% CI 1.09 to 1.35). The increased risk was present independently of age at IBD diagnosis, gender or length of follow-up. The overall incidence of MSA was low in our study, and the regression analysis suggested a tendency towards higher risk of developing MSA in patients with IBD as compared with non-IBD individuals (HR=1.41; 95% CI 0.82 to 2.44). Estimates were similar for women and men. The increased risk of parkinsonism was significantly higher among patients with UC (HR=1.35; 95% CI 1.20 to 1.52) and not significantly different among patients with Crohn’s disease (HR=1.12; 95% CI 0.89 to 1.40).ConclusionsThis nationwide, unselected, cohort study shows a significant association between IBD and later occurrence of PD, which is consistent with recent basic scientific findings of a potential role of GI inflammation in development of parkinsonian disorders.