Insulin resistance in patients with cancer: a systematic review and meta-analysis.

BACKGROUND: Insulin resistance is a critical cause of metabolic dysfunctions. Metabolic dysfunction is common in patients with cancer and is associated with higher cancer recurrence rates and reduced overall survival. Yet, insulin resistance is rarely considered in the clinic and thus it is uncertain how frequently this condition occurs in patients with cancer. METHODS: To address this knowledge gap, we performed a systematic review and a meta-analysis guided by the Preferred Items for Systematic Review and Meta-Analyses (PRISMA) statement. We included studies assessing insulin resistance in patients with various cancer diagnoses, using the gold-standard hyperinsulinemic-euglycemic clamp method. Studies eligible for inclusion were as follows: (1) included cancer patients older than 18 years of age; (2) included an age-matched control group consisting of individuals without cancer or other types of neoplasms; (3) measured insulin sensitivity using the hyperinsulinemic-euglycemic clamp method. We searched the databases MEDLINE, Embase, and Cochrane Central Register of Controlled Trials for articles published from database inception through March 2023 with no language restriction, supplemented by backward and forward citation searching. Bias was assessed using funnel plot. FINDINGS: Fifteen studies satisfied the criteria. The mean insulin-stimulated rate of glucose disposal (Rd) was 7.5 mg/kg/min in control subjects (n = 154), and 4.7 mg/kg/min in patients with a cancer diagnosis (n = 187). Thus, the Rd mean difference was -2.61 mg/kg/min [95% confidence interval, -3.04; -2.19], p<.01). Heterogeneity among the included studies was insignificant (p=.24). INTERPRETATION: These findings suggest that patients with a cancer diagnosis are markedly insulin resistant. As metabolic dysfunction in patients with cancer associates with increased recurrence and reduced overall survival, future studies should address if ameliorating insulin resistance in this population can improve these outcomes thereby improving patient care.Key pointsMetabolic dysfunction increases cancer recurrence rates and reduces survival for patients with cancer.Insulin resistance is a critical cause of metabolic dysfunctions.To date, no comprehensive compilation of research investigating insulin resistance in cancer patients has been produced.In this meta-analysis, we found that patients with various cancers were markedly insulin-resistant.

Association of ferritin and transferrin saturation with all-cause mortality, and the effect of concurrent inflammation: a danish cohort study.

The association between ferritin and transferrin saturation (TS), respectively, and all-cause mortality is unclear. Furthermore, the influence of concurrent inflammation has not been sufficiently elucidated. We investigated these associations and the effect of concurrently elevated C-reactive protein (CRP), and accordingly report the levels associated with lowest all-cause mortality for females and males with and without inflammation.Blood test results from 161,921 individuals were included. Statistical analyses were performed in sex-stratified subpopulations, with ferritin or TS level as continuous exposure variables, and were adjusted for age, co-morbidity and inflammation status using CRP. An interaction was used to investigate whether the effect of ferritin or TS on all-cause mortality was modified by inflammation status (CRP ≥ 10 mg/L or CRP < 10 mg/L). Low and high ferritin and TS levels were respectively associated with increased all-cause mortality in females and in males. These associations persisted with concurrent CRP ≥ 10 mg/L. The ferritin level associated with lowest mortality was 60 µg/L for females and 125 µg/L for males with CRP < 10 mg/L. It was 52 µg/L for females and 118 µg/L for males with CRP ≥ 10 mg/L. The TS level associated with lowest mortality was 33.9% for females and 32.3% for males with CRP < 10 mg/L. It was 28.7% for females and 30.6% for males with CRP ≥ 10 mg/L.Our findings can nuance clinical interpretation and further aid in defining recommended ranges for ferritin and TS.

Decreased plasma lipid levels in a statin-free Danish primary health care cohort between 2001 and 2018.

BACKGROUND: Lipid levels in blood have decreased considerably during the past decades in the general population partly due to use of statins. This study aims to investigate the trends in lipid levels between 2001 and 2018 in a statin-free population from primary health care, overall and by sex and age. METHODS: In a cohort of 634,119 patients from general practice with no diagnoses or medical treatments that affected lipid levels of total cholesterol (TC; n = 1,574,339) between 2001 and 2018 were identified. Similarly, measurements of low-density lipoprotein cholesterol (LDL-C; n = 1,302,440), high-density lipoprotein cholesterol (HDL-C; n = 1,417,857) and triglycerides (TG; n = 1,329,477) were identified. RESULTS: Mean TC decreased from 5.64 mmol/L (95% CI: 5.63-5.65) in 2001 to 5.17 mmol/L (95% CI: 5.16-5.17) in 2018 while LDL-C decreased from 3.67 mmol/L (95% CI: 3.66-3.68) to 3.04 mmol/L (95% CI: 3.03-3.04). Women aged 70-74 years experienced the largest decreases in TC levels corresponding to a decrease of 0.7 mmol/L. The decrease in LDL-C levels was most pronounced in men ≥85 years with a decrease of 0.9 mmol/L. For both genders, TC and LDL-C levels increased with advancing age until around age 50. After menopause the women had higher TC and LDL-C levels than the men. The median (geometric mean) TG level decreased by 0.4 mmol/L from 2001 to 2008, after which it increased slightly by 0.1 mmol/L until 2018. During life the TG levels of the men were markedly higher than the women's until around age 65-70. HDL-C levels showed no trend during the study period. CONCLUSIONS: The levels of TC and LDL-C decreased considerably in a statin-free population from primary health care from 2001 to 2018. These decreases were most pronounced in the elderly population and this trend is not decelerating. For TG, levels have started to increase, after an initial decrease.

A note on pseudo-observations and left-truncation.

Pseudo-observations have been introduced as a way to perform regression analysis of a mean value parameter related to a right-censored time-to-event outcome, such as the survival probability or the restricted mean survival time. Since the introduction of the approach there have been several extensions from the original setting. However, the proper definition and performance of pseudo-observations under left-truncation has not yet been addressed. Here, we look at two types of pseudo-observations under right-censoring and left-truncation. We explored their performance in a simulation study and applied them to data on diabetes patients with left-truncation.

Brain Natriuretic Peptide in Plasma as Predictor of All-Cause Mortality in a Large Danish Primary Health Care Population Suspected of Heart Failure.

BACKGROUND: Measurement of B-type natriuretic peptide (BNP) in plasma may have its greatest potential in primary care, as general practitioners need to rapidly identify patients who warrant further medical review. The aim of the present study was to examine the prognostic information of BNP measurement on all-cause mortality in a large Danish primary care cohort. METHODS: This study covered a cohort of Danish primary care patients (n = 61665) with a median follow-up period of 4.36 years (interquartile range, 2.29-6.62 years). BNP was measured in plasma using the ADVIA Centaur/CentaurXP platform. The association of BNP with mortality was assessed with a hazard ratio for all-cause mortality from a multivariable Cox proportional hazards model. RESULTS: Kaplan-Meier curves showed decreasing survival probability with increasing BNP (P < 0.001). Each doubling of BNP increased mortality by 32.3% (95% CI, 30.8-33.8) when adjusted for sex and age, and by 25.3% (95% CI, 23.8-26.8) when further adjusted for Charlson comorbidity index, hemoglobin, estimated glomerular filtration rate, glycohemoglobin, and thyroid-stimulating hormone. Also, in a subcohort (n = 10824) without biochemical signs of severe kidney failure, anemia, polycythemia, hypothyroidism or hyperthyroidism, or dysregulated diabetes, each doubling of BNP increased mortality by 28.6% (95% CI, 22.8-34.7). CONCLUSIONS: Our results show that even in a primary care population, BNP measurements contain prognostic information regarding all-cause mortality.

Dynamic prediction of cumulative incidence functions by direct binomial regression.

In recent years there have been a series of advances in the field of dynamic prediction. Among those is the development of methods for dynamic prediction of the cumulative incidence function in a competing risk setting. These models enable the predictions to be updated as time progresses and more information becomes available, for example when a patient comes back for a follow-up visit after completing a year of treatment, the risk of death, and adverse events may have changed since treatment initiation. One approach to model the cumulative incidence function in competing risks is by direct binomial regression, where right censoring of the event times is handled by inverse probability of censoring weights. We extend the approach by combining it with landmarking to enable dynamic prediction of the cumulative incidence function. The proposed models are very flexible, as they allow the covariates to have complex time-varying effects, and we illustrate how to investigate possible time-varying structures using Wald tests. The models are fitted using generalized estimating equations. The method is applied to bone marrow transplant data and the performance is investigated in a simulation study.