Clinical trial NCT06323135: Nutrition Assessment in Advanced Cancer Patients
Official title: The Predictive Value of PG-SGA Criteria in Advanced Cancer Patients
Study type: OBSERVATIONAL
Overall status: COMPLETED
Conditions: Advanced Cancer
Nutrition Aspect of Cancer
Prognostic Cancer Model
Lead sponsor: West China Hospital
Sponsor class: OTHER
First posted: 2024-03-21
Enrollment: 2115
Sex: ALL
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Observational model: COHORT
Time perspective: RETROSPECTIVE
Sampling method: NON_PROBABILITY_SAMPLE
Study population: In this study, all of the cancer types were reviewed. The histological information of cancer types was confirmed by the biopsy or resected surgical specimen. The tumor stages were classified based on the guidelines of the American Joint Committee on Cancer Manual (8th edition) (32) at the initial admission. Patients with the following clinical characteristics were excluded, such as those with incomplete nutritional evaluation, incomplete blood indicator test, and loss of follow-up. Furthermore, some cancer types with small sample sizes (\<20 cases) were also excluded from the analysis because of the study's validity concerns. Ultimately, eleven types of cancers (lung cancer, colorectal cancer, esophagus cancer, gastric cancer, head and neck cancer, pancreatic cancer, liver cancer, lymphoma, urinary cancer, breast cancer, and cancer with unknown primary sites) of interest were further investigated.

Brief summary: The goal of this retrospective observational study is to evaluate the prognostic value of nutrition assessment tool in advanced cancers. We aim to evaluate the clinical utility of nutrition assessment tool in predicting the clinical outcomes of cancer patients, which would help the clinicians to make tailored decision for this population.

Detailed description: To date, cancer is the leading cause of disability and death globally. Cancer-related mortality rate differs significantly across the world, reflecting varying patterns of inherent genetic heterogeneity and medical resources available factors. Considerable proportions of patients remained diagnosed with advanced-stage cancers at the initial visit, given the differences between demographic geographical and socioeconomic regions, and inadequate resources of China. For this reason, how to make adequate clinical management and prognostic prediction for advanced-stage cancers are still challenged. Malnutrition is prevalent in cancer patients, accounting for approximately 20% to 80% of the cancer population, which plays a key role in the short-and long-term clinical outcomes. Providing more real-world clinical evidence for supporting the beneficial role of nutritional screening in advanced-stage cancers can help to improve clinical nursing care for advanced-stage patients, especially in developing countries.

The malnutrition status of cancer patients is often accompanied by symptoms of poor nutrient intake, weight loss, progress of systemic inflammatory disorders, and upregulated immune responses. Emerging evidence has determined that the systemic pro-inflammation status was positively associated with elevated malnutritional scores and consistently predicted the worse survival probabilities of cancer patients. Notably, the European Society for Clinical Nutrition and Metabolism (ESPEN) expert consensus regarding the action against cancer-related malnutrition recommended that nutritionists were encouraged to use additional biomarkers to assess the severity of cancer-related systemic inflammation burdens, which might enhance the predictive value of existing malnutritional screening tools in clinical practice. Although the PG-SGA criteria, the nutrition assessment tool, has been widely interpreted and validated to be a simple and easily available tool for the prognosis prediction for varied cancers in recent years, the criteria of the PG-SGA lacked the calculation of systemic inflammatory burdens. Whether the inflammatory indicators could be the surrogate biomarkers for enhancing the prediction ability of PG-SGA for advanced-stage cancer patients remains less studied. Therefore, we aim to fill the mentioned research gaps to conduct this observational study.

Eligibility criteria: Inclusion Criteria:

* Advanced cancers

Exclusion Criteria:

* Aged below 18
* Incomplete blood tests
* Incomplete follow-up data

Primary outcomes:
measure: All-cause mortality
timeFrame: Nov 11, 2019 to 11 Sep, 2023
Secondary outcomes:
measure: length of stay in hospital
timeFrame: Nov 11, 2019 to 11 Sep, 2023
Other outcomes:
Locations:
city: Chengdu
country: China
facility: West China Hospital, Sichuan Universit
state: Sichuan
Study officials:
References: