Dataset Information

Cholesterol-modified prognostic nutritional index (CPNI) as an effective tool for assessing the nutrition status and predicting survival in patients with breast cancer.

ABSTRACT:

Background

Malnutrition is associated with poor overall survival (OS) in breast cancer patients; however, the most predictive nutritional indicators for the prognosis of patients with breast cancer are not well-established. This study aimed to compare the predictive effects of common nutritional indicators on OS and to refine existing nutritional indicators, thereby identifying a more effective nutritional evaluation indicator for predicting the prognosis in breast cancer patients.

Methods

This prospective study analyzed data from 776 breast cancer patients enrolled in the "Investigation on Nutritional Status and its Clinical Outcome of Common Cancers" (INSCOC) project, which was conducted in 40 hospitals in China. We used the time-dependent receiver operating characteristic curve (ROC), Kaplan-Meier survival curve, and Cox regression analysis to evaluate the predictive effects of several nutritional assessments. These assessments included the patient-generated subjective nutrition assessment (PGSGA), the global leadership initiative on malnutrition (GLIM), the controlling nutritional status (CONUT), the nutritional risk index (NRI), and the prognostic nutritional index (PNI). Utilizing machine learning, these nutritional indicators were screened through single-factor analysis, and relatively important variables were selected to modify the PNI. The modified PNI, termed the cholesterol-modified prognostic nutritional index (CPNI), was evaluated for its predictive effect on the prognosis of patients.

Results

Among the nutritional assessments (including PGSGA, GLIM, CONUT, NRI, and PNI), PNI showed the highest predictive ability for patient prognosis (time-dependent ROC = 0.58). CPNI, which evolved from PNI, emerged as the superior nutritional index for OS in breast cancer patients, with the time-dependent ROC of 0.65. It also acted as an independent risk factor for mortality (p < 0.05). Moreover, the risk of malnutrition and mortality was observed to increase gradually among both premenopausal and postmenopausal age women, as well as among women categorized as non-overweight, overweight, and obese.

Conclusions

The CPNI proves to be an effective nutritional assessment tool for predicting the prognosis of patients with breast cancer.

SUBMITTER: Shi J

PROVIDER: S-EPMC10740286 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature

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Publications

Cholesterol-modified prognostic nutritional index (CPNI) as an effective tool for assessing the nutrition status and predicting survival in patients with breast cancer.

Shi Jinyu J Liu Tong T Ge Yizhong Y Liu Chenan C Zhang Qi Q Xie Hailun H Ruan Guotian G Lin Shiqi S Zheng Xin X Chen Yue Y Zhang Heyang H Song Mengmeng M Zhang Xiaowei X Hu Chunlei C Li Xiangrui X Yang Ming M Liu Xiaoyue X Deng Li L Shi Hanping H

BMC medicine 20231221 1

<h4>Background</h4>Malnutrition is associated with poor overall survival (OS) in breast cancer patients; however, the most predictive nutritional indicators for the prognosis of patients with breast cancer are not well-established. This study aimed to compare the predictive effects of common nutritional indicators on OS and to refine existing nutritional indicators, thereby identifying a more effective nutritional evaluation indicator for predicting the prognosis in breast cancer patients.<h4>Me ...[more]

PMID: 38129842

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Project description:BackgroundMalnutrition and sarcopenia are frequently observed in patients undergoing maintenance hemodialysis (MHD). To elucidate whether malnutrition is associated with sarcopenia in those cases, the relationship of nutritional status with sarcopenia was investigated.MethodsNutritional status was assessed using a nutritional risk index (NRI) developed for patients undergoing MHD. This retrospective cross-sectional study included 315 MHD patients (199 males, 116 females), who were divided into low-risk (score 0-7) and medium-/high-risk (score 8-13) groups. Sarcopenia and severe sarcopenia, along with low muscle mass, low muscle strength, and low physical performance were defined using the Asian Working Group for Sarcopenia 2019 criteria.ResultsThe median NRI score was 5.0, while the prevalence of medium-/high-risk cases among the patients was 31.1%. Additionally, the rates of those with low muscle mass, low muscle strength, and low physical performance were 55.9, 60.6, and 31.4%, respectively, while those of sarcopenia and severe sarcopenia were 44.1 and 20.0%, respectively. Multivariable logistic regression analyses revealed a significant (P < 0.001) association of NRI score with sarcopenia [odds ratio (OR) 1.255, 95% confidence interval (CI) 1.143-1.377] and severe sarcopenia (OR 1.257, 95% CI 1.122-1.407), as well as low muscle mass (OR 1.260, 95% CI 1.157-1.374), low muscle strength (OR 1.310, 95% CI 1.178-1.457), and low physical performance (OR 1.216, 95% CI 1.104-1.339). Furthermore, medium-/high-risk status showed a significant (P < 0.05) association with sarcopenia (OR 2.960, 95% CI 1.623-5.401) and severe sarcopenia (OR 2.241, 95% CI 1.151-4.362), as well as low muscle mass (OR 2.141, 95% CI 1.219-3.760), low muscle strength (OR 7.665, 95% CI 3.438-17.091), and low physical performance (OR 2.570, 95% CI 1.401-4.716).ConclusionsThese results suggest that malnutrition contributes to sarcopenia/severe sarcopenia in MHD patients by reducing muscle mass and strength, and physical performance.

Project description:ObjectivesThis study aimed to evaluate the predictive abilities of the 5-item modified Frailty Index (5-mFI), Prognostic Nutrition Index (PNI), and their combination in older adult patients undergoing oral cancer resection and free flap reconstruction.DesignRetrospective cohort study.SettingSecondary care involving multiple centres treating older adult patients for oral cancer.ParticipantsThis study included a total of 1197 patients aged ≥60 years who underwent oral cancer resection with free flap reconstruction between January 2014 and December 2022. The study included patients aged ≥60 years with malignant tumours who underwent selective radical surgery, such as mandibulectomy, maxillectomy, glossectomy or laryngectomy, followed by free flap reconstruction under general anaesthesia. Exclusion criteria included the presence of any inflammatory disease affecting blood test results, incomplete clinical records or missing data for any of the five items in the 5-mFI. Patients were categorised into four groups based on PNI and 5-mFI values: (1) 'Control' (neither frail nor malnourished), (2) 'Frailty' (frail only), (3) 'Malnutrition' (malnourished only) and (4) 'Frailty+Malnutrition' (both frail and malnourished).Primary and secondary outcome measuresThe primary outcome was the rate of complications within 30 days after surgery. Secondary outcomes included unplanned reoperation rates, length of postoperative hospital stay and the predictive performance of PNI, 5-mFI and their combination.ResultsThe overall complication rate within 30 days post-surgery was 34.6%. The Frailty+Malnutrition group exhibited the highest risk of complications, longer postoperative hospital stays and increased rates of unplanned reoperation compared with the Control, Frailty and Malnutrition groups. The combined PNI and 5-mFI model significantly improved the predictive value for postoperative complications compared with either PNI or 5-mFI alone.ConclusionsOlder adult patients undergoing oral cancer resection with free flap reconstruction face considerable risk from frailty and malnutrition. Although both 5-mFI and PNI independently demonstrated good predictive abilities for postoperative complications, the combined model provided the best prediction. These findings could help optimise preoperative management in this high-risk population.

Dataset Information

Cholesterol-modified prognostic nutritional index (CPNI) as an effective tool for assessing the nutrition status and predicting survival in patients with breast cancer.

Background

Methods

Results

Conclusions

Publications

Cholesterol-modified prognostic nutritional index (CPNI) as an effective tool for assessing the nutrition status and predicting survival in patients with breast cancer.

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