Efficacy of the physiobiological parameter-based grading system for predicting the long-term prognosis after curative surgery for resectable pancreatic cancer

Preoperative Prediction of Long-Term Survival After Surgery in Patients with Resectable Pancreatic Ductal Adenocarcinoma

BACKGROUND

Although some clinical trials have demonstrated the benefits of neoadjuvant therapy for resectable pancreatic ductal adenocarcinoma (PDAC), its optimal candidate has not been clarified. This study aimed to detect predictive prognostic factors for resectable PDAC patients who underwent upfront surgery and identify patient cohorts with long-term survival without neoadjuvant therapy.

PATIENTS AND METHODS

A total of 232 patients with resectable PDAC who underwent upfront surgery between January 2008 and December 2019 were evaluated.

RESULTS

The median overall survival (OS) time and 5-year OS rate of resectable PDAC with upfront surgery was 31.5 months and 33.3%, respectively. Multivariate analyses identified tumor diameter in computed tomography (CT) ≤ 19 mm [hazard ratio (HR) 0.40, p < 0.001], span-1 within the normal range (HR 0.54, p = 0.023), prognostic nutritional index (PNI) ≥ 44.31 (HR 0.51, p < 0.001), and lymphocyte-to-monocyte ratio (LMR) ≥ 3.79 (HR 0.51, p < 0.001) as prognostic factors that influence favorable prognoses after upfront surgery. According to the prognostic prediction model based on these four factors, patients with four favorable prognostic factors had a better prognosis with a 5-year OS rate of 82.4% compared to others (p < 0.001). These patients had a high R0 resection rate and a low frequency of tumor recurrence after upfront surgery.

CONCLUSIONS

We identified patients with long-term survival after upfront surgery by prognostic prediction model consisting of tumor diameter in CT, span-1, PNI, and LMR. Evaluation of anatomical, biological, nutritional, and inflammatory factors may be valuable to introduce an optimal treatment strategy for resectable PDAC.

Prognostic potential of nutritional risk screening and assessment tools in predicting survival of patients with pancreatic neoplasms: a systematic review

BACKGROUNDS & AIMS

The nutritional evaluation of pancreatic cancer (PC) patients lacks a gold standard or scientific consensus, we aimed to summarize and systematically evaluate the prognostic value of nutritional screening and assessment tools used for PC patients.

METHODS

Relevant studies were retrieved from major databases (PubMed, Embase, Web of Science, Cochrane Library) and searched from January 2010 to December 2023. We performed meta-analyses with STATA 14.0 when three or more studies used the same tool.

RESULTS

This analysis included 27 articles involving 6,060 PC patients. According to a meta-analysis of these studies, poor nutritional status evaluated using five nutritional screening tools Prognostic Nutritional Index (PNI), Geriatric Nutritional Risk Index (GNRI), Controlling Nutritional Status Score (CONUT), Nutrition Risk Screening (NRS2002) and Glasgow Prognostic Score (GPS) was associated with all-cause mortality in PC patients. But Modified Glasgow Prognostic Score (mGPS) did not. Of all tools analyzed, CONUT had the maximum HR for mortality (HR = 1.978, 95%CI 1.345-2.907, P = 0.001).

CONCLUSION

All-cause mortality in PC patients was predicted by poor nutritional status. CONUT may be the best nutritional assessment tool for PC patients. The clinical application value of Short Form Mini Nutritional Assessment (MNA-SF), Generated Subjective Global Assessment (SGA) and Patient-generated Subjective Global Assessment (PG-SGA) in PC patients need to be confirmed. In order to improve patients' nutritional status and promote their recovery, nutritional screening tools can be used.

REGISTRATION

This systematic review was registered at the International Prospective Register of Systematic Reviews (PROSPERO) (number CRD42022376715).

Prognostic role of the prognostic nutritional index in patients with pancreatic cancer who underwent curative resection without preoperative neoadjuvant treatment: A systematic review and meta-analysis

Background

The prognostic nutrition index (PNI), which has been evaluated in various kinds of cancers, offered a simple yet effective approach to predict the prognosis. The aim of this meta-analysis is to reveal the correlation between preoperative PNI and the prognosis of patients with pancreatic ductal adenocarcinoma (PDAC) who underwent curative resection.

Methods

We searched the PubMed, Embase, Web of Science and Cochrane Library databases, and extracted the hazard ratio (HR) with 95% confidential interval (CI) from eligible studies. The pooled HR with 95% CI was applied to evaluate the association between PNI and overall survival (OS), recurrence-free survival (RFS).

Results

A total of fourteen studies with 3,385 patients were included for meta-analysis. The results (the pooled HR: 1.664, 95% CI: 1.424–1.994, I² = 42.6%, p value = 0.046) indicated that low preoperative PNI was closely related to poor OS. In addition, the results suggested that PNI was negatively correlated with RFS (the pooled HR: 1.369, 95%CI: 1.080–1.734). The robustness of these pooled results was verified by our subgroup analysis and sensitivity analysis. Moreover, different cutoff values among studies are responsible for the heterogeneity of pooled HR of OS through meta-regression analysis (p value = 0.042). Funnel plots, Begg's test (p value = 0.228) and Egger’s test (p value = 0.702) indicated no significant publication bias in OS.

Conclusion

Preoperative PNI might be a promising marker to predict the prognosis of PDAC patients who underwent curative resection.

A Novel DNA Replication-Related Signature Predicting Recurrence After R0 Resection of Pancreatic Ductal Adenocarcinoma: Prognostic Value and Clinical Implications

The aim of any surgical resection for pancreatic ductal adenocarcinoma (PDAC) is to achieve tumor-free margins (R0). R0 margins give rise to better outcomes than do positive margins (R1). Nevertheless, postoperative morbidity after R0 resection remains high and prognostic gene signature predicting recurrence risk of patients in this subgroup is blank. Our study aimed to develop a DNA replication-related gene signature to stratify the R0-treated PDAC patients with various recurrence risks. We conducted Cox regression analysis and the LASSO algorithm on 273 DNA replication-related genes and eventually constructed a 7-gene signature. The predictive capability and clinical feasibility of this risk model were assessed in both training and external validation sets. Pathway enrichment analysis showed that the signature was closely related to cell cycle, DNA replication, and DNA repair. These findings may shed light on the identification of novel biomarkers and therapeutic targets for PDAC.