Nutritional status assessed by Patient-Generated Subjective Global Assessment is associated with toxicity to chemoradiotherapy in women with cervical cancer: a prospective study

Association between body composition phenotypes and treatment toxicity in women with cervical cancer undergoing chemoradiotherapy

OBJECTIVE

To identify whether there is an association between body composition phenotypes and toxicity to chemoradiotherapy in women with cervical cancer.

METHODS

This is a prospective cohort study that included 330 adult patients with cervical cancer treated with chemoradiotherapy. Computed tomography images were used to assess skeletal muscle index (SMI) and radiodensity (SMD), total adipose tissue index, and visceral adipose tissue index. Chemoradiotherapy toxicity was assessed weekly, and toxicity-induced modification of treatment (TIMT) was considered as any severe adverse event resulting in treatment interruption, delay, or dose reduction.

RESULTS

Approximately 45% of the patients presented at least one unfavorable body composition parameter (lower SMI, lower SMD, higher total adipose tissue index, or higher visceral adipose tissue index), 23% had two conditions, and 3% had three conditions. The incidence of toxicity ≥ grade 3 and TIMT was 55% and 30%, respectively. For adverse events ≥ grade 3, lower SMI was the determining factor for worse outcomes when evaluated alone or combined with lower SMD and normal adiposity. All body composition phenotypes were associated with TIMT, increasing the risk when both conditions were present.

CONCLUSIONS

Lower SMI was an independent factor for the higher number of adverse events, as it remained a risk factor when analyzed in isolation or in association with adipose tissue. Women with excess adipose tissue associated with lower muscle mass had a risk approximately 4 times higher of delaying or interrupting chemoradiotherapy. Furthermore, for the sum of unfavorable conditions, there was a progressive increase in the risk of TIMT.

Pretreatment Computed Tomography-Defined Sarcopenia, Treatment-Associated Muscle Loss, and Survival in Patients With Cervical Cancer: A Systematic Review and Meta-Analysis

CONTEXT

Sarcopenia has been identified as a potential predictor of poor prognosis in various types of cancer. However, the impact of pretreatment sarcopenia and the reduction of skeletal muscle mass during treatment on survival outcomes of patients with cervical cancer is still not well understood.

OBJECTIVE

This meta-analysis was conducted to investigate the impact of pretreatment sarcopenia and treatment-associated muscle loss on survival outcomes in patients with cervical cancer.

DATA SOURCES

The PubMed, EMBASE, Web of Science, and Cochrane Library databases were searched for studies exploring the relationship between muscle loss and the prognosis of cervical cancer until January 1, 2023.

DATA EXTRACTION

The hazard ratios (HRs) and 95% CIs for overall survival (OS) and progression-free survival (PFS) were extracted.

DATA ANALYSIS

The data were analyzed using R software. The studies' quality was assessed using the Quality in Prognostic Studies tool. Twelve observational studies involving 1498 patients with cervical cancer were included in the analysis, with a prevalence of sarcopenia ranging from 24.8% to 57.5%. Sarcopenia was an independent predictor of poor OS (HR, 1.68; 95% CI, 1.28-2.21; P < .01) and PFS (HR, 1.53; 95% CI, 1.19-1.98; P < .01) in patients with cervical cancer. Additionally, the decrease in skeletal muscle during treatment was also significantly related to the OS (HR, 4.46; 95% CI, 2.87-6.94; P < .01) and PFS (HR, 2.89; 95% CI. 1.83-4.55; P < .01).

CONCLUSIONS

The prevalence of pretreatment sarcopenia was high among patients with cervical cancer. Pretreatment sarcopenia and skeletal muscle loss during treatment both negatively affected prognosis in cervical cancer.

Phase angle is a predictor for postoperative complications in colorectal cancer

Aim

The aim of this study was to develop a validated nomogram to predict the risk of postoperative complications in colorectal cancer (CRC) patients by analyzing the factors that contribute to these complications.

Methods

We retrospectively collected clinical information on patients who underwent CRC surgery at a single clinical center from January 2021 to December 2021. Univariate and multivariate logistic regression analysis to identify independent risk factors for postoperative complications and to develop a predictive model. A receiver operating characteristic (ROC) curve was used to calculate the area under the curve (AUC) to assess the predicted probability. Calibration curve was drawn to compare the predicted probability of the nomogram with the actual probability, and decision curve analysis (DCA) was employed to evaluate the clinical utility of the nomogram.

Results

A total of 190 CRC patients were included in this study. We retrospectively collected baseline information, clinical information, surgical information, and nutrition-related indicators for all patients. Through multivariate logistic regression analysis, preoperative albumin (p = 0.041, OR = 0.906, 95% CI = 0.824-0.996), surgical time (p = 0.009, OR = 1.006, 95% CI = 1.001-1.010), waistline (p = 0.049, OR = 1.011, 95% CI = 1.002-1.020) and phase angle (PA) (p = 0.022, OR = 0.615, 95% CI = 0.405-0.933) were identified as independent risk factors for postoperative complications in CRC, and a nomogram prediction model was established using the above four variables. The AUC of 0.706 for the ROC plot and the high agreement between predicted and actual probabilities in the calibration curves suggested that the prediction model has good predictive power. The DCA also confirmed the good clinical performance of the nomogram.

Conclusion

This study developed a nomogram to predict the risk of postoperative complications in CRC patients, providing surgeons with a reliable reference to personalized patient management in the perioperative period and preoperative nutritional interventions.

Nutritional Assessment Tools for Patients with Cancer: A Narrative Review

Cancer patients are at high risk of malnutrition, which can lead to adverse health outcomes such as prolonged hospitalization, increased complications, and increased mortality. Accurate and timely nutritional assessment plays a critical role in effectively managing malnutrition in these patients. However, while many tools exist to assess malnutrition, there is no universally accepted standard. Although different tools have their own strengths and limitations, there is a lack of narrative reviews on nutritional assessment tools for cancer patients. To address this knowledge gap, we conducted a non-systematic literature search using PubMed, Embase, Web of Science, and the Cochrane Library from their inception until May 2023. A total of 90 studies met our selection criteria and were included in our narrative review. We evaluated the applications, strengths, and limitations of 4 commonly used nutritional assessment tools for cancer patients: the Subjective Global Assessment (SGA), Patient-Generated Subjective Global Assessment (PG-SGA), Mini Nutritional Assessment (MNA), and Global Leadership Initiative on Malnutrition (GLIM). Our findings revealed that malnutrition was associated with adverse health outcomes. Each of these 4 tools has its applications, strengths, and limitations. Our findings provide medical staff with a foundation for choosing the optimal tool to rapidly and accurately assess malnutrition in cancer patients. It is essential for medical staff to be familiar with these common tools to ensure effective nutritional management of cancer patients.

Malnutrition, sarcopenia, and cancer cachexia in gynecologic cancer

Patients with gynecologic cancers are at risk for malnutrition, cancer cachexia, and sarcopenia. Accumulating data supports that malnourished patients with gynecologic cancer have worse overall survival, increased healthcare utilization and costs, and a higher incidence of postoperative complications and treatment toxicity than those who are not malnourished. Malnutrition is defined as insufficient energy intake, leading to altered body composition and subsequent impaired physical and cognitive function, and can result in sarcopenia and cachexia, defined as the loss of lean body mass and loss of body weight respectively. The etiology of cancer-related malnutrition is complex, resulting from a systemic pro-inflammatory state of malignancy with upregulation of muscle degradation pathways and metabolic derangements, including lipolysis and proteolysis, that may not respond to nutritional repletion alone. Numerous validated scoring systems and radiographic measures have been described to define and quantify the severity of malnutrition and muscle loss in both clinical and research settings. "Prehabilitation" and optimization of nutrition and functional status early in therapy may combat the development or worsening of malnutrition and associated syndromes and ultimately improve oncologic outcomes, but limited data exist in the context of gynecologic cancer. Multi-modality nutrition and physical activity interventions have been proposed to combat the biophysical losses related to malnutrition. Several trials are underway in gynecologic oncology patients to address these aims, but significant gaps in knowledge persist. Pharmacologic interventions and potential immune targets for combating cachexia related to malignancy are discussed in this review and may provide opportunities to target disease and cachexia. This article reviews currently available data regarding the implications, diagnostics, physiology, and intervention strategies for gynecologic oncology patients with malnutrition and its associated conditions.

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.