Body Mass Index and Melanoma Prognosis.
Ontology highlight
ABSTRACT: Introduction
Obesity has been suggested as a risk factor in the progression of malignancies, including melanoma. Most studies defined obesity using body mass index (BMI), although the index is considered an imperfect measure of body composition.Objective
The aim of this article is to examine whether BMI can impact on the prognosis of cutaneous melanoma, regardless of anti-tumor therapy. The relationship between BMI and specific prognostic factors in melanoma patients has been reviewed.Methods
Literature search was conducted on PubMed using the terms "melanoma" and "body mass index" or "obesity". We selected articles, published up to 30 November 2020, examining the prognostic aspects of melanoma. Articles evaluating the risk and incidence of melanoma were excluded as well as studies regarding morbidity and complications following surgical procedures, or those performed in metastatic melanoma patients treated with anti-tumor therapies.Results
Mixed results have emerged from studies assessing the clinical outcomes in melanoma patients in relation to BMI. More consistent data seem to support the relationship between BMI and Breslow thickness.Conclusions
Studies that focus specifically on the link between obesity and melanoma prognosis are limited; further research is needed to deepen our knowledge on this link.
SUBMITTER: Cassano N
PROVIDER: S-EPMC8480463 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Objective: At present, the association of body mass index (BMI) with the prognosis of liver cirrhosis is controversial. Our retrospective study aimed to evaluate the impact of BMI on the outcome of liver cirrhosis. Methods: In the first part, long-term death was evaluated in 436 patients with cirrhosis and without malignancy from our prospectively established single-center database. In the second part, in-hospital death was evaluated in 379 patients with cirrhosis and with acute gastrointestinal bleeding (AGIB) from our retrospective multicenter study. BMI was calculated and categorized as underweight (BMI <18.5 kg/m2), normal weight (18.5 ≤ BMI < 23.0 kg/m2), and overweight/obese (BMI ≥ 23.0 kg/m2). Results: In the first part, Kaplan-Meier curve analyses demonstrated a significantly higher cumulative survival rate in the overweight/obese group than the normal weight group (p = 0.047). Cox regression analyses demonstrated that overweight/obesity was significantly associated with decreased long-term mortality compared with the normal weight group [hazard ratio (HR) = 0.635; 95% CI: 0.405-0.998; p = 0.049] but not an independent predictor after adjusting for age, gender, and Child-Pugh score (HR = 0.758; 95%CI: 0.479-1.199; p = 0.236). In the second part, Kaplan-Meier curve analyses demonstrated no significant difference in the cumulative survival rate between the overweight/obese and the normal weight groups (p = 0.094). Cox regression analyses also demonstrated that overweight/obesity was not significantly associated with in-hospital mortality compared with normal weight group (HR = 0.349; 95%CI: 0.096-1.269; p = 0.110). In both of the two parts, the Kaplan-Meier curve analyses demonstrated no significant difference in the cumulative survival rate between underweight and normal weight groups. Conclusion: Overweight/obesity is modestly associated with long-term survival in patients with cirrhosis but not an independent prognostic predictor. There is little effect of overweight/obesity on the short-term survival of patients with cirrhosis and with AGIB.
| S-EPMC8417598 | biostudies-literature
Project description:A better understanding of the SARS-CoV-2 virus behavior and possible risk factors implicated in poor outcome has become an urgent need. We performed a systematic review in order to investigate a possible association between body weight and prognosis among patients diagnosed with COVID-19. We searched in Cochrane Library, EMBASE, MEDLINE, WHO-Global Literature on Coronavirus Disease, OpenGrey, and Medrxiv. We used the ROBINS-I tool or Cross-Sectional/Prevalence Study Quality tool from AHRQ, to evaluate the methodological quality of included studies. Nine studies (two prospective cohorts, four retrospective cohorts and three cross-sectional) were included and assessed the relationship between obesity and COVID-19 prognosis. Risk of bias of the included studies ranged from moderate to critical. Clinical and methodological heterogeneity among them precluded meta-analyses. Most of the included studies showed some degree of association to: (a) higher BMI and worse clinical presentation and (b) obesity and need of hospitalization. The results were inconsistent about the impact of obesity on mortality. Based on limited methodological quality studies, obesity seems to predict poor clinical evolution in patients with COVID-19. Further studies with appropriate prospective design are needed to reduce the uncertainty on this evidence.
| S-EPMC7456965 | biostudies-literature
Project description:Inactivation of the TP53 (p53) pathway by TP53 mutations is one of key steps in colorectal carcinogenesis. TP53 also plays an important role in cellular energy metabolism. We hypothesized that TP53-altered tumor cells might behave aggressively independent of energy balance, while progression of TP53-intact cells might depend on excess energy balance. Utilizing a database of 1,060 colon and rectal cancer patients in two prospective cohort studies, we evaluated TP53 expression by immunohistochemistry. Among 1,060 colorectal cancers, 457 (43%) tumors were positive for TP53. Cox proportional hazards model was used to compute mortality hazard ratio (HR), adjusting for clinical and tumoral features, including microsatellite instability, the CpG island methylator phenotype, LINE-1 methylation, KRAS, BRAF and PIK3CA. TP53 positivity was not significantly associated with cancer-specific survival in univariate analysis with HR of 1.16 [95% confidence interval (CI)=0.92-1.45], which became significant after stage adjustment (multivariate HR=1.30; 95% CI=1.02-1.65). Notably, we found a possible modifying effect of patient's body mass index (BMI) on tumor TP53. In non-obese patients (BMI<30 kg/m2), TP53 positivity was associated with shorter cancer-specific survival (multivariate HR=1.53; 95% CI=1.17-2.00), while TP53 positivity was not significantly associated with survival among obese patients (BMI≥30 kg/m2). Effect of TP53 positivity on cancer-specific survival significantly differed by BMI (pinteraction=0.0051). The adverse effect of obesity on patient mortality was limited to TP53-negative patients. These molecular pathological epidemiology data may support a dual role of TP53 alterations in cell-cycle deregulation and cell autonomy with respect to energy balance status.
| S-EPMC3288809 | biostudies-literature
Project description:BackgroundHeight and body mass index (BMI) have both been positively associated with melanoma risk, although findings for BMI have been less consistent than height. It remains unclear, however, whether these associations reflect causality or are due to residual confounding by environmental and lifestyle risk factors. We re-evaluated these associations using a two-sample Mendelian randomization (MR) approach.MethodsWe identified single nucleotide polymorphisms (SNPs) for BMI and height from separate genome-wide association study (GWAS) meta-analyses. We obtained melanoma SNPs from the most recent melanoma GWAS meta-analysis comprising 12 874 cases and 23 203 controls. We used the inverse variance-weighted estimator to derive separate causal risk estimates across all SNP instruments for BMI and height.ResultsBased on the combined estimate derived from 730 SNPs for BMI, we found no evidence of an association between genetically predicted BMI and melanoma [odds ratio (OR) per one standard deviation (1 SD) (4.6 kg/m2) increase in BMI 1.00, 95% confidence interval (CI): 0.91-1.11]. In contrast, we observed a positive association between genetically-predicted height (derived from a pooled estimate of 3290 SNPs) and melanoma risk [OR 1.08, 95% CI: 1.02-1.13, per 1 SD (9.27 cm) increase in height]. Sensitivity analyses using two alternative MR methods yielded similar results.ConclusionsThese findings provide no evidence for a causal association between higher BMI and melanoma, but support the notion that height is causally associated with melanoma risk. Mechanisms through which height influences melanoma risk remain unclear, and it remains possible that the effect could be mediated through diverse pathways including growth factors and even socioeconomic status.
| S-EPMC7778056 | biostudies-literature
Project description:The prognostic implications of very low body mass index (BMI) values remain unclear in patients with acute decompensated heart failure (ADHF). This study aimed to investigate the prognostic impact of BMI classification based on the World Health Organization criteria in patients with ADHF. Among 3509 patients with ADHF and available BMI data at discharge in 19 participating hospitals in Japan between October 2014 and March 2016, the study population was divided into five groups; (1) Severely underweight: BMI?<?16 kg/m2, (2) Underweight: BMI???16 kg/m2 and?<?18.5 kg/m2, (3) Normal weight: BMI???18.5 kg/m2 and?<?25 kg/m2, (4) Overweight: BMI???25 kg/m2 and?<?30 kg/m2 (5) Obese: BMI???30 kg/m2. The primary outcome measure was all-cause death. The median follow-up duration was 471 days, with 96.4% follow up at 1-year. The cumulative 1-year incidence of all-cause death was higher in underweight groups, and lower in overweight groups (Severely underweight: 36.3%, Underweight: 23.9%, Normal weight: 14.4%, Overweight: 7.9%, and Obese: 9.0%, P?<?0.001). After adjusting confounders, the excess mortality risk remained significant in the severely underweight group (HR, 2.32; 95%CI, 1.83–2.94; P?<?0.001), and in the underweight group (HR, 1.31; 95%CI, 1.08–1.59; P?=?0.005) relative to the normal weight group, while the lower mortality risk was no longer significant in the overweight group (HR, 0.82; 95%CI, 0.62–1.10; P?=?0.18) and in the obese group (HR, 1.09; 95%CI, 0.65–1.85; P?=?0.74). Very low BMI was associated with a higher risk for one-year mortality after discharge in patients with ADHF.
| S-EPMC7542148 | biostudies-literature
Project description:ImportanceBody mass index (BMI) is used to diagnose obesity in adolescents worldwide, despite evidence that weight does not scale with height squared in adolescents. To account for this, health care providers diagnose obesity using BMI percentiles for each age (BMI z scores), but this does not ensure that BMI is accurate in adolescents.ObjectiveTo compare the accuracy of BMI vs other body fat indices of the form body mass divided by heightn in estimating body fat levels in adolescents.Design, setting, and participantsCross-sectional data from the 1999 to 2006 US National Health and Nutrition Examination Survey were analyzed between September 2015 and December 2016.Main outcomes and measuresDual-energy x-ray absorptiometry and anthropometric data were used to determine changes in body fat levels, body proportions, and the scaling relationships among body mass, height, and percent body fat. To assess the merits of each adiposity index, 3 criteria were used: stability with age, accuracy in estimating percent body fat, and accuracy in classifying adolescents as overweight vs normal weight.ResultsParticipants included 2285 non-Hispanic white participants aged 8 to 29 years. Percent body fat varied with both age and height during adolescence, invalidating the standard weight-to-height regression as the way of finding the optimal body fat index. Because the correct regression model (percent body fat is proportional to mass divided by heightn) suggested that percent body fat scales to height with an exponent closer to 3, we therefore focused on the tri-ponderal mass index (TMI; mass divided by height cubed) as an alternative to BMI z scores. For ages 8 to 17 years, TMI yielded greater stability with age and estimated percent body fat better than BMI (R2?=?0.64 vs 0.38 in boys and R2?=?0.72 vs 0.66 in girls). Moreover, TMI misclassified adolescents as overweight vs normal weight less often than BMI z scores (TMI, 8.4%; 95% CI, 7.3%-9.5% vs BMI, 19.4%; 95% CI, 17.8%-20.0%; P?<?.001) and performed equally as well as updated BMI percentiles derived from the same data set (TMI, 8.4%; 95% CI, 7.3%-9.5% vs BMI, 8.0%; 95% CI, 6.9%-9.1%; P?=?.62).Conclusions and relevanceThe tri-ponderal mass index estimates body fat levels more accurately than BMI in non-Hispanic white adolescents aged 8 to 17 years. Moreover, TMI diagnoses adolescents as overweight more accurately than BMI z scores and equally as well as updated BMI percentiles but is much simpler to use than either because it does not involve complicated percentiles. Taken together, it is worth considering replacing BMI z scores with TMI to estimate body fat levels in adolescents.
| S-EPMC5710345 | biostudies-literature
Project description:Triglyceride glycemic-body mass index (TyG-BMI) is a simple and reliable surrogate for insulin resistance (IR). However, it is still unclear if TyG-BMI has any predictive value in patients having percutaneous coronary intervention (PCI) for ST-segment elevation myocardial infarction (STEMI). The purpose of this study was to examine the TyG-BMI index's prognostic significance and predictive power in patients with STEMI. The study comprised a total of 2648 consecutive STEMI patients who underwent PCI. The primary endpoint was the occurrence of major adverse cardiovascular events (MACE), defined as the combination of all-cause death, nonfatal myocardial infarction, nonfatal stroke, and coronary revascularization. The TyG-BMI index was formulated as ln [fasting triglycerides (mg/dL) × fasting plasma glucose (mg/dL)/2] × BMI. 193 patients in all experienced MACE over a median follow-up of 14.7 months. There was a statistically significant difference between the Kaplan-Meier survival curves for the TyG-BMI index tertiles (log-rank test, p = 0.019) for the cumulative incidence of MACE. The adjusted HRs for the incidence of MACE in the middle and highest quartiles of the TyG-BMI index compared with the lowest quartile were 1.37 (95% CI 0.92, 2.03) and 1.53 (95% CI 1.02, 2.29), respectively, in the fully adjusted Cox regression model. At six months, one year, and three years, the TyG-BMI area under the curve (AUC) for predicting MACE was 0.691, 0.666, and 0.637, respectively. Additionally, adding the TyG-BMI index to the risk prediction model enhanced outcome prediction. In STEMI patients undergoing PCI, TyG-BMI was independently linked to MACE. TyG-BMI could be a simple and solid way to assess MACE risk and prognosis.
| S-EPMC10782013 | biostudies-literature
Project description:Genome wide DNA methylation profiling of MZ twins discordant and concordant for BMI. The Illumina Infinium 450k Human DNA methylation Beadchip was used to obtain DNA methylation profiles across approximately 485,000 CpGs. Samples included 30 MZ twin pairs discordant for BMI and 10 pairs concordant for BMI.
2015-04-20 | GSE43975 | GEO
Project description:Prospective epidemiologic studies that investigated the association between body mass index (BMI) and non-melanoma skin cancer (NMSC) yielded inconsistent findings. A dose-response meta-analysis was conducted to quantitatively summarize the evidence. PubMed and Embase databases were searched for relevant studies. Study-specific relative risk (RR) and 95% confidence interval (CI) for an increase in BMI of 5?kg/m2 was computed with the generalized least squares trend estimation, and these risk estimates were combined with the random-effects model. Nine publications were included in the final analyses, consisting of 18 independent cohorts with 22 risk estimates (971,795 participants and 50,561 NMSC cases). Results of the dose-response analyses showed a nonlinear inverse relationship between BMI and NMSC (RR?=?0.88, 95% CI: 0.85-0.91, I2?=?71.2%, P-nonlinearity <0.001), which persisted when limiting to the studies with adjustment for important potential confounders including sun exposure and sensitivity factors. The risk estimates were very similar for squamous cell carcinoma and basal cell carcinoma. Sex appeared a source of heterogeneity (P-difference?=?0.06), with a weaker, but still significant inverse association in men than in women. This dose-response meta-analysis suggests a nonlinear inverse association between BMI and NMSC.
| S-EPMC5127294 | biostudies-literature
Project description:ObjectivesBody mass index (BMI) is a known indicator of all-cause mortality. However, conventional BMI does not reflect the three-dimensional human body. To overcome this limitation, a new BMI has been proposed that provides a closer approximation of real human body shape. This study investigated the associations between the new BMI and poor outcomes in patients with antineutrophil cytoplasmic antibody-associated vasculitis (AAV).MethodWe retrospectively reviewed the medical records of 242 patients with AAV in a single tertiary medical center. Based on the new BMI, the patients were categorized into four groups: underweight (<18.5 kg/m2.5 ), healthy weight (18.5 to <25.0 kg/m2.5 ), overweight (25.0 to <30.0 kg/m2.5 ), and obese (≥30.0 kg/m2.5 ). The association among the new BMI and death, relapse, end-stage renal disease (ESRD) development, cerebrovascular accident, and cardiovascular disease was analyzed.ResultsThe underweight group, according to the new BMI, had higher hazard ratios (HRs) for all-cause mortality (HR: 3.180, 95% confidence interval [CI]: 1.134-8.922, p = 0.028), relapse (HR: 2.141, 95% CI: 1.019-4.368, p = 0.036), and ESRD development (HR: 2.729, 95% CI: 1.190-6.259, p = 0.018) than the healthy weight group. However, according to the conventional BMI, there were no differences in the risks for all poor outcomes between the underweight and healthy weight groups. Multivariate logistic regression analysis demonstrated that being underweight, according to the new BMI, was an independent risk factor for all-cause mortality (HR: 5.285; 95% CI: 1.468-19.018; p = 0.011).ConclusionBeing underweight, according to the new BMI, is associated with poor outcomes in patients with AAV.
| S-EPMC9102757 | biostudies-literature