Clinical malnutrition predictive model among gynecologic cancer patients prior to elective operation: A cross-sectional study.

Background: Malnutrition is common among cancer patients regardless of stage of cancer. Given the strong association between malnutrition with prolonged hospitalization, delayed recovery and even higher post-operative complications among gynaecologic cancer (GC) patients, it is important to understand its predictive factors. The current study aimed to determine malnutrition predictors among GC patients before elective operation.

Method: A cross-sectional study was conducted among surgical GC patients who were admitted for elective surgery. Data on socio-demographic characteristics, clinical status (diagnosis, the staging of cancer, comorbidities and family history on cancer), anthropometric measures [ Body Mass Index (BMI), weight changes, the percentage of weight loss past one month, muscle mass, fat mass, fat-free mass and mid-upper arm circumference (MUAC)], biochemical profiles [C-reactive protein, albumin and C-reactive protein (CRP) to albumin ratio (CAR)], handgrip strength, total daily energy and protein intake, and malnutrition status [scored Patient Generated-Subjective Global Assessment (PG-SGA)] were assessed during admission.

Results: Study recruited 124 participants and 57.2% (n = 71) were malnourished. Mean for age, weight changes past one month, handgrip strength, total daily energy and protein intake, PG-SGA score and CAR of participants were 49.9 ± 12.5 years, -4.9 ± 7.2%, 15.6 ± 6.2 kg, 25±7 kcal/kg/day, 1.0 ± 0.3 g/kg/day, 6.5 ± 5.4 and 0.7 ± 1.9, respectively. Multiple linear regression test revealed that the percentage of weight loss past one month, haemoglobin, CRP and handgrip strength were the significant predictors of malnutrition.

Conclusion: Malnutrition is common among GC patient even before elective operation. The early malnutrition screening following with proper nutritional intervention is crucial to optimize nutritional status among GC patients before elective operation.