Clinical Trial Details
— Status: Completed
Administrative data
NCT number |
NCT05620537 |
Other study ID # |
2022JinlingHospital-cohort2 |
Secondary ID |
|
Status |
Completed |
Phase |
|
First received |
|
Last updated |
|
Start date |
November 10, 2022 |
Est. completion date |
November 25, 2022 |
Study information
Verified date |
February 2023 |
Source |
Jinling Hospital, China |
Contact |
n/a |
Is FDA regulated |
No |
Health authority |
|
Study type |
Observational
|
Clinical Trial Summary
This multicenter retrospectively observational cohort study was conducted on participants
with histologically confirmed gastric and colorectal cancer who underwent radical surgery in
11 medical centers in China from August 1, 2015, to June 31, 2018. Baseline clinicopathologic
data and nutritional status assessments including Nutrition Risk Screening 2002 (NRS 2002)
score and Patient-generated Subjective Global Assessment (PG-SGA) rating were collected.
Variables will be screened using the least absolute shrinkage and selection operator (LASSO)
regression model and Cox regression analysis. Internal and external validations will be
performed via the receiver operating curve (ROC), the area under the curve (AUC), the
concordance index (C-index), calibration plots, decision curve analysis (DCA), and Five folds
cross-validation by 200 times.
Description:
1. Study design and patients This study is a multicenter retrospectively observational
cohort study, which collected and followed up the patients with gastric cancer and
colorectal cancer in 11 Chinese hospitals from August 1, 2015, to June 31, 2018. The
eight sites of these were recruited as a training cohort, and the other three sites were
recruited as an external validation cohort (Supplement Table 1). The inclusion criteria
for both cohorts were complied with: 1) 18-80 years old; 2) postoperative pathological
diagnosis of gastric or colorectal adenocarcinoma; 3) underwent radical surgery; 4) TNM
stage ranged from stage I to stage III. The exclusion criteria included: 1) NRS 2002 or
PG-SGA data was missing; 2) pathological diagnosis of gastric stump cancer, cancer in
situ, or pin-point cancer; 3) in-hospital death or death within 30 days after surgery;
4) preoperative neoadjuvant therapy; 5) preoperative endoscopic surgery; 6) the previous
history of other malignant tumors; 7) pregnancy. This study was approved by the Ethics
Committee of each hospital.
2. Data collection The following clinical data were collected in this study: demographic
characteristics (age, sex, height, weight, and BMI), age-adjusted Charlson Comorbidity
Index (aCCI), NRS 2002 score, PG-SGA rating, pathological characteristics (tumor stage,
type, differentiation, tumor size, and tumor vol-ume), surgical characteristics
(operation type and intraoperative blood loss), hematological indicators
[carcinoembryonic antigen (CEA), cancer antigen19-9 (CA19-9), albumin, pre-albumin,
blood glucose, triglycerides (TG), alanine aminotransferase (ALT), aspartate
aminotransferase (AST), total bilirubin, blood urea nitrogen (BUN), serum creatinine,
hemoglobin, and white blood cell], and other clinical characteristics (postoperative
complication and postoperative infection). These candidate variables were derived from
previous studies and clinical experience. We obtained tumor staging from electronic
medical records and pathological reports using the American Joint Committee on Cancer
(AJCC) 8th edition. Tumor volume was derived from tumor length, width, and height using
the following formulas: V = 1/2 × a × b2 or V = π/6 × a × b × c.
3. Nutritional status assessments All the centers routinely perform nutritional status
assessments on admission by the NRS 2002 and PG-SGA. We collected the NRS 2002 score and
PG-SGA rating from the electronic medical record system.
3.1 NRS 2002 NRS 2002 was used to estimate nutritional risk, accounting for inadequate
nutritional status (low, moderate, or severe) and illness severity (low, moderate, or
severe), with a 70-year age adjustment. The NRS 2002 score ranges from 0 to 7. For the
NRS 2002, we employed three categories: no nutritional risk (<3), nutritional risk
(3-4), and severe nutritional risk (≥5).
3.2 PG-SGA The PG-SGA, a nutritional status assessment tool based on the SGA, was
developed exclusively for cancer patients. This includes self-evaluation by patients as
well as evaluation by medical professionals. The seven components that make up the core
content are weight, food intake, symptoms, functional ability, illness and its
relationship to nutritional needs, metabolic demand (stress), and physical examination.
The first four components were assessed by patients, while the final three were assessed
by medical professionals. Physical examination was used to determine muscular
exhaustion, subcutaneous fat thickness, and edema. Decreased mass and tone in temporal
regions, deltoids, and quads indicated muscular exhaustion. The triceps and midaxillary
lines at the level of the lower ribs were studied for subcutaneous fat depletion. Edema
was checked on the ankles. Patients were categorized as well-nourished (A), moderately
malnourished (B), or severely malnourished (C) based on the foregoing assessments.
4. Study Outcome The primary outcome of this study was OS, defined as the time from the
date of surgery to the end of follow-up or death. Follow-up information was mainly
collected through the follow-up database of gastric and colorectal cancer of each center
combined with telephone, outpatient, or inpatient follow-ups.
5. Statistical methods Measurement data will be expressed as means and standard deviations
(SD), while enumeration data will be expressed as frequencies and respective
percentages. Hematological indicators will be converted to categorical variables while
analyzed. Variables will be initially screened using the least absolute shrinkage and
selection operator (LASSO) regression. The variables with minimum λ will be further
screened using univariate and multivariate Cox regression analysis to identify
independent predictors. Then we will build a prediction model by multivariate Cox
regression model and plot the nomogram. For user convenience, we will also create a
dynamic nomogram webpage. Discrimination of the model will be assessed using the
receiver operating curve (ROC), the area under the curve (AUC), and the concordance
index (C-index). Calibration plots will be used to assess the calibration of the model.
Decision curve analysis (DCA) will be used to evaluate the clinical utility of the
model. The same assessments will be performed with an external validation cohort.
Internal validation of the model will be performed using Five folds cross-validation by
200 times. The cut-off values of the nomogram score which categorize patients into three
categories (low-risk, middle-risk, and high-risk) will be calculated by X-tile 3.6.1
version (https://medicine.yale.edu/lab/rimm/research/software/). Kaplan-Meier analysis
will be used to do survival analyses. R 4.2.0 version (http://www.r-project.org) will be
used for statistical analyses of this study. A two-tailed p <0.05 will be considered
statistically significant.