Obesity and high neutrophil-to-lymphocyte ratio are prognostic factors in non-metastatic breast cancer patients

Relationships between human serum albumin levels and septic shock, in-hospital, and out-of-hospital mortality in elderly patients with pneumonia in different BMI ranges

OBJECTIVE

This retrospective cohort identified the association of human serum albumin (HSA) with adverse outcomes (septic shock, in-hospital and out-of-hospital mortality) in elderly hospitalized patients who have community-acquired pneumonia (CAP) and specific body mass index (BMI).

MATERIALS AND METHODS

This research included hospitalized CAP individuals (≥ 60 years) and was conducted at a teaching hospital in western China. All the patients were categorized into three populations based on two BMI cutoff values (18.5 kg/m2 and 24 kg/m2). The data was acquired from medical records, local government mortality databases, and telephone interviews. Binomial logistic regression analysis was used to explore the associations between low HSA and septic shock and in-hospital mortality, and Cox regression analysis was used to explore the association between low HSA and out-of-hospital mortality.

RESULTS

A total of 627 patients were included in the analysis of in-hospital death and septic shock, and 431 patients were included in the analysis of out-of-hospital death. The study showed that 120 elderly patients with CAP (19.14%) died in the hospital, while 141 patients (32.71%) died out of the hospital, and 93 patients (14.83%) developed septic shock. No differences in in-hospital and out-of-hospital mortality were observed for BMI values < 18.5 kg/m2 or BMI ≥ 24 kg/m2, regardless of whether HSA was ≥ 40 g/l or < 40 g/l. When 18.5 kg/m2 ≤ BMI < 24 kg/m2, patients with HSA < 40 g/l had both higher in-hospital and out-of-hospital mortality compared with those with HSA ≥ 40 g/l (in-hospital death: 26.13% vs. 11.46%, p < 0.001; out-of-hospital death: 46.15% vs. 19.17%, p < 0.001). No significant differences were observed in the incidence of septic shock between patients with HSA < 40 g/l and those with HSA ≥ 40 g/l either in the overall population or when the BMI values were divided according to the cutoff values of 18.5 kg/m2 and 24 kg/m2. After further logistic regression analysis and adjustment for potential confounders, the results showed that when 18.5 kg/m2 ≤ BMI < 24 kg/m2, elderly CAP patients with HSA < 40 g/l had a higher risk of in-hospital and out-of-hospital mortality compared with those with HSA ≥ 40 g/l (in-hospital death: HR = 1.964, 95%CI = 1.08-3.573; out-of-hospital death: HR = 2.841, 95%CI = 1.745-4.627).

CONCLUSIONS

HSA levels can predict the risk of in-hospital and out-of-hospital mortality in elderly patients with CAP and normal BMI values. However, HSA cannot predict the risk of septic shock in elderly patients hospitalized with CAP, irrespective of their BMI classification.

Postdiagnosis body fatness, weight change and breast cancer prognosis: Global Cancer Update Program (CUP global) systematic literature review and meta-analysis

Previous evidence on postdiagnosis body fatness and mortality after breast cancer was graded as limited-suggestive. To evaluate the evidence on body mass index (BMI), waist circumference, waist-hip-ratio and weight change in relation to breast cancer prognosis, an updated systematic review was conducted. PubMed and Embase were searched for relevant studies published up to 31 October, 2021. Random-effects meta-analyses were conducted to estimate summary relative risks (RRs). The evidence was judged by an independent Expert Panel using pre-defined grading criteria. One randomized controlled trial and 225 observational studies were reviewed (220 publications). There was strong evidence (likelihood of causality: probable) that higher postdiagnosis BMI was associated with increased all-cause mortality (64 studies, 32 507 deaths), breast cancer-specific mortality (39 studies, 14 106 deaths) and second primary breast cancer (11 studies, 5248 events). The respective summary RRs and 95% confidence intervals per 5 kg/m2 BMI were 1.07 (1.05-1.10), 1.10 (1.06-1.14) and 1.14 (1.04-1.26), with high between-study heterogeneity (I2  = 56%, 60%, 66%), but generally consistent positive associations. Positive associations were also observed for waist circumference, waist-hip-ratio and all-cause and breast cancer-specific mortality. There was limited-suggestive evidence that postdiagnosis BMI was associated with higher risk of recurrence, nonbreast cancer deaths and cardiovascular deaths. The evidence for postdiagnosis (unexplained) weight or BMI change and all outcomes was graded as limited-no conclusion. The RCT showed potential beneficial effect of intentional weight loss on disease-free-survival, but more intervention trials and well-designed observational studies in diverse populations are needed to elucidate the impact of body composition and their changes on breast cancer outcomes.

Prognostic Potential of Immune Inflammatory Biomarkers in Breast Cancer Patients Treated with Neoadjuvant Chemotherapy

Simple Summary

Systemic inflammation is associated with an increased aggressiveness of breast cancer and can contribute to a decreased activity of neoadjuvant treatments. Biomarkers of systemic inflammation are easily obtained from routine blood counts and are highly cost-effective, having great potential to steer cancer prognosis in clinical practice. In our study, we tested the hypothesis that high values of these biomarkers might have an effect on the clinical outcomes in a population of patients treated with neoadjuvant chemotherapy for breast cancer. The results of our study, together with data from the literature, hint at a possible role of inflammatory markers in the diagnostic and therapeutic algorithm of breast cancer, where specific pre-operative blood cell ratios could be used in combination with biological and clinical factors to tailor adjuvant therapy.

Abstract

Immune inflammatory biomarkers are easily obtained and inexpensive blood-based parameters that recently showed prognostic and predictive value in many solid tumors. In this study, we aimed to investigate the role of these biomarkers in predicting distant relapse in breast cancer patients treated with neoadjuvant chemotherapy (NACT). All breast cancer patients who referred to our Breast Unit and underwent NACT were retrospectively reviewed. The pre-treatment neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR), and pan-immune-inflammation value (PIV) were calculated from complete blood counts. The primary outcome was 5-year distant-metastasis-free survival (DMFS). In receiver operating characteristic analyses, the optimal cutoff values for the NLR, PLR, MLR, and PIV were determined at 2.25, 152.46, 0.25, and 438.68, respectively. High levels of the MLR, but not the NLR, PLR, or PIV, were associated with improved 5-year DMSF in the study population using both univariate (HR 0.52, p = 0.03) and multivariate analyses (HR, 0.44; p = 0.02). Our study showed that the MLR was a significant independent parameter affecting DMFS in breast cancer patients undergoing NACT. Prospective studies are required to confirm this finding and to define reliable cutoff values, thus leading the way for the clinical application of this biomarker.

Breast cancer microenvironment and obesity: challenges for therapy

Women with obesity who develop breast cancer have a worsened prognosis with diminished survival rates and increased rates of metastasis. Obesity is also associated with decreased breast cancer response to endocrine and chemotherapeutic treatments. Studies utilizing multiple in vivo models of obesity as well as human breast tumors have enhanced our understanding of how obesity alters the breast tumor microenvironment. Changes in the complement and function of adipocytes, adipose-derived stromal cells, immune cells, and endothelial cells and remodeling of the extracellular matrix all contribute to the rapid growth of breast tumors in the context of obesity. Interactions of these cells enhance secretion of cytokines and adipokines as well as local levels of estrogen within the breast tumor microenvironment that promote resistance to multiple therapies. In this review, we will discuss our current understanding of the impact of obesity on the breast tumor microenvironment, how obesity-induced changes in cellular interactions promote resistance to breast cancer treatments, and areas for development of treatment interventions for breast cancer patients with obesity.

The influence of body mass index on the tolerability and effectiveness of full-weight-based paclitaxel chemotherapy in women with early-stage breast cancer

PURPOSE

To investigate the influence of body mass index (BMI) on the tolerability and effectiveness of full-weight-based paclitaxel chemotherapy in early breast cancer patients.

METHODS

Early-stage breast cancer patients who received (neo)adjuvant weekly paclitaxel 80 mg/m² chemotherapy were included in this retrospective study. Patients were divided into three groups based on their BMI: lean, overweight, and obese. Logistic regression was used to assess for association between BMI with administered relative dose intensity (RDI) < 85%. The occurrence of treatment modifications and the pathological response on neoadjuvant chemotherapy were compared between BMI categories.

RESULTS

Four hundred (400) patients were included in this study; 200 (50%) lean, 125 (31%) overweight, and 75 (19%) obese patients. The adjusted odds ratio to receive RDI < 85% for BMI was 1.02 (p value, .263). Treatment modifications occurred in 115 (58%), 82 (66%), and 52 (69%) patients in the respective BMI categories (p value = .132). Peripheral neuropathy was observed in 79 (40%), 58 (46%), and 41 (55%) patients in the lean, overweight, and obese group (p value = .069), whereas hematologic toxicity was observed in 31 (16%), 10 (8%), and 4 (5%) patients (p value = .025). Pathological complete response was observed in 22 (17%), 11 (14%), and 6 (13%) patients in the respective BMI categories (p value = .799).

CONCLUSION

BMI did not significantly influence the tolerability and effectiveness of full-weight-based paclitaxel chemotherapy. Therefore, the results of this study align with current guideline recommendations of using full-weight-based paclitaxel chemotherapy in obese patients.

Neutrophils Actively Contribute to Obesity-Associated Inflammation and Pathological Complications

Obesity is characterized by an increase in body weight associated with an exaggerated enlargement of the adipose tissue. Obesity has serious negative effects because it is associated with multiple pathological complications such as type 2 diabetes mellitus, cardiovascular diseases, cancer, and COVID-19. Nowadays, 39% of the world population is obese or overweight, making obesity the 21st century epidemic. Obesity is also characterized by a mild, chronic, systemic inflammation. Accumulation of fat in adipose tissue causes stress and malfunction of adipocytes, which then initiate inflammation. Next, adipose tissue is infiltrated by cells of the innate immune system. Recently, it has become evident that neutrophils, the most abundant leukocytes in blood, are the first immune cells infiltrating the adipose tissue. Neutrophils then get activated and release inflammatory factors that recruit macrophages and other immune cells. These immune cells, in turn, perpetuate the inflammation state by producing cytokines and chemokines that can reach other parts of the body, creating a systemic inflammatory condition. In this review, we described the recent findings on the role of neutrophils during obesity and the initiation of inflammation. In addition, we discuss the involvement of neutrophils in the generation of obesity-related complications using diabetes as a prime example.

Pan-Immune-Inflammation Value: A New Prognostic Index in Operative Breast Cancer

Background

To build a predictive scoring model based on simple immune and inflammatory parameters to predict postoperative survival in patients with breast cancer.

Methods

We used a brand-new immuno-inflammatory index-pan-immune-inflammation value (PIV)-to retrospectively evaluate the relationship between PIV and overall survival (OS), and based on the results of Cox regression analysis, we established a simple scoring prediction model based on several independent prognostic parameters. The predictive accuracy of the model was evaluated and independently validated.

Results

A total of 1,312 patients were included for analysis. PIV was calculated as follows: neutrophil count (10⁹/L) × platelet count (10⁹/L) × monocyte count (10⁹/L)/lymphocyte count (10⁹/L). According to the best cutoff value of PIV, we divided the patients into two different subgroups, high PIV (PIV > 310.2) and low PIV (PIV ≤ 310.2), associated with significantly different survival outcomes (3-year OS, 80.26% vs. 86.29%, respectively; 5-year OS, 62.5% vs. 71.55%, respectively). Six independent prognostic factors were identified and used to build the scoring system, which performed well with a concordance index (C-index) of 0.759 (95% CI: 0.715-0.802); the calibration plot showed good calibration.

Conclusions

We have established and verified a simple scoring system for predicting prognosis, which can predict the survival of patients with operable breast cancer. This system can help clinicians implement targeted and individualized treatment strategies.