PROGNOSTIC EVALUATION OF THE NUTRITIONAL PROGNOSTIC INDEX IN PATIENTS WITH NON-METASTATIC RECTAL CANCER
Bibliographic record
Abstract
Rectal cancer (RC) is one of the leading causes of cancer mortality worldwide. Recent studies indicate that systemic inflammation and nutritional status are associated with the prognosis of cancer patients. The prognostic nutritional index (PNI) has been increasingly studied as a predictor of survival outcome. However, despite these advances, there are few studies evaluating the prognostic capacity of this index in patients with RC. To analyze the impact of PNI on the survival of patients with non-metastatic RC undergoing oncological treatment. This is a retrospective, cross-sectional and analytical study. It included patients diagnosed with stage I, II and III rectal carcinoma who had been treated surgically, with or without neoadjuvant and adjuvant chemotherapy, and who were attended to at the Clinical Oncology outpatient clinic of the Hospital das Clínicas of the University of Campinas between January 2000 and December 2016. Patients were categorized into low and high PNI, according to the median of the sample. PNI was calculated using the formula: PNI = (10xserum albumin [g/dl]) + 0.005xlymphocytes/μL). Clinical variables, body composition and systemic inflammatory indices were also analyzed. Body composition was analyzed using computed tomography, and skeletal muscle compartments and subcutaneous and visceral adipose tissue were assessed using SliceOmatic software (Tomovision, Canada). Statistical analyses were carried out using Stata software version 12.0 (Stata Corp LP®). This research was approved by the UNICAMP Research Ethics Committee (CAAE: 22438319.9.0000.5404). The sample consisted of 298 patients, 118 of whom had low PNI. The group with low PNI had a lower muscle mass index (p = 0.025) and subcutaneous adipose tissue index (p = 0.044), and higher subcutaneous (p =0.049) and visceral (p = 0.012) adipose tissue radiodensity. Median disease-free survival was 24.5 months for patients with low PNI (HR 1.85; CI 1.30-2.62; p = 0.001). Patients with low PNI had a lower median disease-free survival (mDS) of 24.5 months compared to 107.4 months for the high PNI group [HR 1.85; IC 1.30-2.62; p = 0.001]. Median overall survival (mOS) was 75.3 months for the low NPI group and 140.4 months for the high NPI group (HR 1.67; CI 1.13-2.48; p = 0.011). The PNI performed at diagnosis is a prognostic tool for assessing the clinical outcome of patients with non-metastatic RC. Nutritional status and systemic inflammation are associated with survival in cancer patients. The PNI is a marker that combines both conditions and has been shown to be an important prognostic tool for desease-free survival (DFS) and overall survival (OS) in RC. The PNI is a simple, practical tool that uses low-cost clinical evaluation parameters and can therefore be easily implemented in clinical practice.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".