Additive value of inflammatory markers in predicting outcomes in resectable gastrointestinal stromal tumor patients

Gastrointestinal stromal tumors (GISTs) represent a unique subset of the most common mesenchymal neoplasms arising mainly in the stomach or small intestine. While complete surgical resection remains the mainstay of curative treatment, the risk of postoperative recurrence remains significant—particularly in tumors with aggressive histological or molecular features. In this context, Zhao et al. (1) offer a novel contribution by proposing a nomogram-based prognostic model that includes preoperative inflammatory markers to estimate recurrence-free survival (RFS) in GIST patients.

The retrospective study analyzed 124 patients who underwent GIST resection between 2014 and 2017 at a single center in China. It focused on evaluating the prognostic value of four systemic inflammatory indices: the systemic immune-inflammation index (SII), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and monocyte-to-lymphocyte ratio (MLR) (1-4). These parameters reflect the interaction between the immune system and cancer progression (5-7). The main finding of the study is that elevated preoperative PLR and MLR levels were independently associated with shorter RFS (1). Specifically, patients with PLR ≥181.33 and MLR ≥0.43 had significantly worse outcomes over the 5-year follow-up. Interestingly, while elevated NLR and SII were also associated with shorter RFS in univariate analysis, they did not retain independent prognostic significance in the multivariate model. Additionally, patients who received postoperative targeted therapy showed a statistically significant reduction in recurrence risk. Based on these results, the authors constructed a nomogram integrating PLR, MLR, and targeted therapy to predict the probability of 5-year RFS.

One of the most valuable aspects of this study lies in its practical approach. By focusing on simple, low-cost blood-derived indices, the authors have developed a model that could potentially be used across various healthcare systems (8). In a field where many prognostic tools rely on advanced genetic or molecular testing, this model stands out for its accessibility.

Furthermore, the use of a nomogram, a graphical statistical tool that translates complex statistical models into individualized risk estimates, increases clinical utility. Nomograms are increasingly used in oncology for personalized decision-making, and the inclusion of inflammatory markers as independent predictors offers an innovative approach (9-11).

From a clinical standpoint, the ability to predict recurrence after surgery is crucial to improving long-term outcomes in GIST patients (12,13). Although several risk stratification schemes exist (e.g., the NIH-Fletcher classification), they do not account for host immune response or systemic inflammation.

By incorporating PLR and MLR, this study introduces additional dimensions to risk assessment. For example, a patient with an otherwise moderate-risk tumor could be reclassified as higher risk based on an elevated MLR or PLR, prompting more intensive follow-up or consideration for adjuvant therapy. On the other hand, patients with low inflammatory scores might avoid unnecessary interventions.

The inclusion of targeted therapy (e.g., imatinib) as a protective factor further reflects current clinical practice and highlights the importance of combining surgical and medical treatment methods (14,15).

Despite its advantages, the study has several limitations, many of which are acknowledged by the authors. First and foremost, the retrospective single-center design introduces inherent risks of bias and limits generalizability. External validation in a multi-center or prospective cohort would be necessary before the nomogram could be widely adopted.

Second, while inflammatory markers are biologically reliable prognostic tools, they can be influenced by numerous factors unrelated to cancer—including infections, autoimmune diseases, and medications (5,16-18). Although the study excluded patients with known comorbidities, subclinical conditions or variations in lab testing could still affect the results.

Another limitation is the relatively small sample size (n=124), which, while acceptable for exploratory analysis, may limit statistical power and the statistical stability of the model. Certain variables—such as mitotic rate, tumor rupture, or genetic mutations—were not included in the final analysis or nomogram, despite being well-established predictors of recurrence in GIST.

Additionally, the lack of time-dependent analysis limits our understanding of how changes in these markers over time could influence prognosis. Future studies might benefit from serial monitoring of inflammatory indices during the postoperative period or after initiation of targeted therapy (19-21).

This study may point a new direction to several potential research pathways. First, the proposed nomogram should undergo external validation in independent larger cohorts across different ethnic and geographic populations. That could confirm its utility in clinical practice.

Second, integrating inflammatory markers with existing risk classification systems could yield models with improved predictive accuracy. For example, a composite model that includes tumor size, mitotic index, location, and PLR/MLR might be more useful than any single method. It is necessary to underline that inflammatory markers may be incorporated into existing prognostic systems in primary GIST, which include well-established features (as mitotic index not included in nomogram proposed by Zhao et al.) (1), as well as primary tumor mutational status, which is still not taken into account when assessing the prognosis of GIST after surgery (22).

Third, the role of inflammation in GIST biology deserves further exploration. Although the association between immune response and tumor progression is well documented in many other cancers (23,24), the specific mechanisms linking platelet and monocyte activity to GIST recurrence remain to be clarified. This could have implications not only for prognosis but also for the development of adjunctive therapies targeting the inflammatory microenvironment. Our research team also found NLR as a prognostic and predictive marker and as a marker for treatment monitoring in patients with advanced GIST treated with imatinib (25).

Zhao et al. (1) have made a valuable contribution by demonstrating that simple, routinely collected inflammatory markers—specifically PLR and MLR—can serve as independent predictors of recurrence in GIST patients undergoing surgery. The nomogram developed in this study offers a practical tool for personalizing follow-up and guiding clinical decisions, particularly when used in combination with existing methods. However, if it could be used in routine practice, it should be incorporated into existing risk assessment systems, which may be especially important for intermediate risk groups that comprise heterogeneous patients in terms of prognosis (13).

While further validation is still needed, this work reinforces the growing recognition that cancer prognosis is shaped not only by tumor characteristics but also by the host immune and inflammatory response. This study serves as a reminder of the power of simple biomarkers and the continued relevance of integrative, multidisciplinary thinking in oncology.

Acknowledgments

None.

Footnote

Provenance and Peer Review: This article was commissioned by the editorial office, Gastrointestinal Stromal Tumor. The article has undergone external peer review.

Peer Review File: Available at https://gist.amegroups.com/article/view/10.21037/gist-2025-7/prf

Funding: None.

Conflicts of Interest: Both authors have completed the ICMJE uniform disclosure form (available at https://gist.amegroups.com/article/view/10.21037/gist-2025-7/coif). P.R. has received honoraria for lectures, consulting fees and Advisory Boards from Bristol-Myers Squibb, MSD, Novartis, Pierre Fabre, Philogen, Genesis, Medison Pharma outside of the scope of the manuscript. He received support for attending meetings and/or travel from Pierre Fabre. His institution received research funding from Novarits, Pfizer, Roche, Bristol-Myers Squibb. The other author has no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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