Handgrip Strength, Overhydration and Nutritional Status as a Predictors of Gastrointestinal Toxicity in Cervical Cancer Patients. A Prospective Study

Sarcopenia in gynaecological cancers

Gynaecological cancers (GCs) comprise a group of cancers that originate in the female reproductive organs. Each GC is unique, with different signs and symptoms, risk factors and therapeutic strategies. Worldwide, the majority of GCs are still associated with high mortality rates, especially ovarian, due to difficulty in early detection. Despite numerous studies on the underlying pathophysiology, research in the field of GCs poses unique scientific and technological challenges. These challenges require a concerted multi- and inter-disciplinary effort by the clinical, scientific and research communities to accelerate the advancement of prognostic, diagnostic, and therapeutic approaches. Sarcopenia is a multifactorial disease which leads to the systemic loss of skeletal muscle mass and function. It can be caused by malignancies, as well as due to malnutrition, physical inactivity, ageing and neuromuscular, inflammatory, and/or endocrine diseases. Anorexia and systemic inflammation can shift the metabolic balance of patients with cancer cachexia towards catabolism of skeletal muscle, and hence sarcopenia. Therefore, sarcopenia is considered as an indicator of poor general health status, as well as the possible indicator of advanced cancer. There is a growing body of evidence showing the prognostic significance of sarcopenia in various cancers, including GCs. This review will outline the clinical importance of sarcopenia in patients with GCs.

Prognostic value of overhydration and bioelectrical impedance vector on short- and long-term outcomes in hospitalized patients with cancer

BACKGROUND & AIMS

Water, an essential component of body composition, appears to be a significant predictor of adverse outcomes in clinical populations, despite being frequently underexplored. Bioelectrical impedance analysis (BIA) and vector analysis (BIVA) are easy and cost-effective bedside tools for estimating body composition, particularly water content. Therefore, our study aimed to assess the impact of hydration and fluid status using both BIA and BIVA on outcomes in hospitalized patients with cancer.

METHODS

A prospective cohort study involving hospitalized individuals with cancer was conducted. Total body water (TBW) was estimated using BIA. Extracellular-water/TBW (ECW/TBW) and ECW/intracellular-water (ECW/ICW) ratios were calculated. BIVA ellipses vectors were constructed to enhance our analysis of hydration status. Participants were followed during their hospital stay and up to six months after discharge to assess outcomes, including in-hospital mortality, 6-month non-elective rehospitalization, and 6-month mortality.

RESULTS

TBW, ECW/TBW, ECW/ICW ratios, and BIVA plots were not associated with non-elective rehospitalization during the follow-up period. However, TBW and an elevated ECW/ICW ratio were independent predictors of in-hospital mortality [hazard ratio (HR): 1.07 (1.01; 1.13) p = 0.020; HR: 4.23 (1.69; 10.58) p = 0.002]. Elevated ratios ECW/TBW and ECW/ICW were independent predictors of 6-month mortality [HR: 1.87 (1.10; 3.21) p = 0.022; HR: 2.49 (1.37; 4.51) p = 0.003]. BIVA vectors for in-hospital and 6-month mortality shifted significantly to the right, leading to cachexia and overhydration quadrants (p < 0.05).

CONCLUSION

Abnormalities related to overhydration were important predictors of short- and long-term mortality in hospitalized patients with cancer.

Clinical influence of neoadjuvant chemoradiotherapy on immunonutritional status in locally advanced rectal cancer

PURPOSE

Cancer patients receiving various anti-cancer treatments commonly experience malnutrition, and many studies have reported that nutritional status is associated with survival and prognosis. Although standard neoadjuvant chemoradiotherapy (CRT) is commonly used in patients with locally advanced rectal cancer owing to its tumor-downsizing and downstaging effects, there is a lack of research on the impact of patients' nutritional status on the efficacy of neoadjuvant CRT.

METHODS

We investigated the immunonutritional markers before and after long-course neoadjuvant CRT in 131 patients diagnosed with locally advanced rectal cancer from March 2013 to March 2022.

RESULTS

We divided the patients into two groups: a low prognostic nutritional index (PNI) with a cutoff value of 50.92, and a high PNI. In both groups, significant decreases in lymphocyte count and PNI and an increase in neutrophil-to-lymphocyte ratio (NLR) were observed before and after CRT (P<0.001). Furthermore, a higher proportion of patients experienced adverse effects in the low PNI group than in the high PNI group (76.6% in low PNI vs. 54.8% in high PNI, P=0.013). The most commonly reported CRT-induced adverse effect was lower gastrointestinal tract toxicity.

CONCLUSION

By measuring the PNI and NLR without additional tests prior to starting neoadjuvant CRT in patients with locally advanced rectal cancer, it is possible to predict the risk of acute adverse effects caused by CRT. Additionally, providing external nutritional support to reduce the immunonutritional changes that occur during CRT can decrease side effects and potentially increase treatment compliance.

Machine learning for genetic prediction of chemotherapy toxicity in cervical cancer

BACKGROUND

Locally advanced cervical cancer (LACC) is frequently treated with neoadjuvant chemotherapy (NACT), which includes paclitaxel and platinum. However, the development of severe chemotherapy toxicity is a barrier to successful NACT. Phosphatidylinositol 3-kinase (PI3K)/serine/threonine kinase (AKT) pathway is related to the occurrence of chemotherapeutic toxicity. In this research work, we employ a random forest (RF) machine learning model to forecast NACT toxicity (neurological, gastrointestinal, and hematological reactions).

MATERIALS AND METHODS

Twenty-four single nucleotide polymorphisms (SNPs) in the PI3K/AKT pathway from 259 LACC patients were used to construct a dataset. Following the data preprocessing, the RF model was trained. The Mean Decrease in Impurity approach was adopted to evaluate the relevance of 70 selected genotypes' importance by comparing chemotherapy toxicity grades 1-2 vs. 3.

RESULTS

In the Mean Decrease in Impurity analysis, neurological toxicity was much more likely to occur in LACC patients with homozygous AA in Akt2 rs7259541 than in those with AG or GG genotypes. The CT genotype of PTEN rs532678 and the CT genotype of Akt1 rs2494739 increased the risk of neurological toxicity. The top three loci were rs4558508, rs17431184, and rs1130233, which were attributed to an elevated risk of gastrointestinal toxicity. LACC patients who had heterozygous AG in Akt2 rs7259541 exhibited an obviously greater risk of hematological toxicity than those who had AA or GG genotypes. And the CT genotype for Akt1 rs2494739 and the CC genotype in PTEN rs926091 showed a tendency to increase the risk of suffering from hematological toxicity.

CONCLUSION

Akt2 rs7259541 and rs4558508, Akt1 rs2494739 and rs1130233, PTEN rs532678, rs17431184, and rs926091 polymorphisms are associated with different toxic effects during the chemotherapy treatment of LACC.

Development and validation of a radiomics-based nomogram for the prediction of postoperative malnutrition in stage IB1-IIA2 cervical carcinoma

Objective

In individuals with stage IB1-IIA2 cervical cancer (CC) who received postoperative radiotherapy ± chemotherapy (PORT/CRT), the interaction between sarcopenia and malnutrition remains elusive, let alone employing a nomogram model based on radiomic features of psoas extracted at the level of the third lumbar vertebra (L3). This study was set to develop a radiomics-based nomogram model to predict malnutrition as per the Patient-Generated Subjective Global Assessment (PG-SGA) for individuals with CC.

Methods

In total, 120 individuals with CC underwent computed tomography (CT) scans before PORT/CRT. The radiomic features of psoas at L3 were obtained from non-enhanced CT images. Identification of the optimal features and construction of the rad-score formula were conducted utilizing the least absolute shrinkage and selection operator (LASSO) logistic regression to predict malnutrition in the training dataset (radiomic model). Identification of the major clinical factors in the clinical model was performed by means of binary logistic regression analysis. The radiomics-based nomogram was further developed by integrating radiomic signatures and clinical risk factors (combined model). The receiver operating characteristic (ROC) curves and decision curves analysis (DCA) were employed for the evaluation and comparison of the three models in terms of their predictive performance.

Results

Twelve radiomic features in total were chosen, and the rad-score was determined with the help of the non-zero coefficient from LASSO regression. Multivariate analysis revealed that besides rad-score, age and Eastern Cooperative Oncology Group performance status could independently predict malnutrition. As per the data of this analysis, a nomogram prediction model was constructed. The area under the ROC curves (AUC) values of the radiomic and clinical models were 0.778 and 0.847 for the training and 0.776 and 0.776 for the validation sets, respectively. An increase in the AUC was observed up to 0.972 and 0.805 in the training and validation sets, respectively, in the combined model. DCA also confirmed the clinical benefit of the combined model.

Conclusion

This radiomics-based nomogram model depicted potential for use as a marker for predicting malnutrition in stage IB1-IIA2 CC patients who underwent PORT/CRT and required further investigation with a large sample size.

Phase Angle and Nutritional Status: The Impact on Survival and Health-Related Quality of Life in Locally Advanced Uterine Cervical Cancer

The phase angle, an indicator of muscle mass status and membrane cell integrity, has been associated with low survival, poorer clinical outcomes, and worse quality of life among cancer patients, but information on women with uterine cervical cancer (UCCa) is scarce. In this prospective study, we used a bioelectrical impedance analyzer to obtain the PA of 65 women with UCCa. We compared the health-related quality of life and inflammatory and nutritional indicators between low PA and normal PA. The mean age was 52 ± 13. The low PA and normal PA groups differed in terms of the C-reactive protein (15.8 ± 19.6 versus 6.82 ± 5.02, p = 0.022), glucose (125.39 ± 88.19 versus 88.78 ± 23.08, p = 0.021), albumin (3.9 ± 0.39 versus 4.37 ± 0.30, p = 0.000), EORTC QLQ-C30 loss of appetite symptom scale score (33.33 (0.0-100.00) versus 0.0 (0.0-0.0), p = 0.005), and EORTC QLQ-CX24 menopausal symptoms scale score (0.0 (0.0-33.33) versus 0.0 (0.0-100.0), p = 0.03). The main finding of the present study is the interaction between PA and obesity as critical cofactors in the UCCa adeno and adenosquamous histologic variants, to a greater extent than cervical squamous cell carcinoma.

Prognostic values of the prognostic nutritional index, geriatric nutritional risk index, and systemic inflammatory indexes in patients with stage IIB-III cervical cancer receiving radiotherapy

Background

Growing evidence suggests that nutritional status and inflammation are associated with survival in various cancers. This study aimed to evaluate the prognostic value of the prognostic nutritional index (PNI), geriatric nutritional risk index (GNRI), and systemic inflammatory indexes (neutrophil/lymphocyte ratio [NLR], monocyte/lymphocyte ratio [MLR], and platelet/lymphocyte ratio [PLR]) in patients with stage IIB-III cervical cancer receiving radiotherapy.

Results

The ideal cutoff values for the PNI, GNRI, NLR, MLR, and PLR were 48.3, 97.04, 2.8, 0.41, and 186.67, respectively. Low PNI and GNRI scores were associated with poor OS and PFS. High NLR, MLR, and PLR also predicted inferior 5-year OS and PFS rates in patients with stage IIB-III cervical cancer. Multivariate Cox regression analysis identified tumor size, histological type, stage, number of metastatic lymph nodes, PNI, GNRI, NLR, PLR, and MLR as significant prognostic factors for OS and PFS.

Conclusions

The current findings suggest that the PNI, GNRI, NLR, PLR, and MLR are essential parameters for predicting prognosis in patients with stage IIB-III cervical cancer receiving radiotherapy.