Predictors of lymph node metastasis in patients with gastrointestinal stromal tumors (GISTs)

The influence of lymphadenectomy on the prognosis of small intestinal stromal tumors: a study based on the SEER database

BACKGROUND

Small intestinal stromal tumors (SISTs) typically require surgical treatment. However, the impact of lymphadenectomy (LA) on long-term prognosis in patients remains unclear. Therefore, we plan to analyze the effect of LA on the prognosis of patients with SISTs using the Surveillance, Epidemiology, and End Results (SEER) database.

METHODS

Data on SISTs patients between 2000 and 2019 were obtained from the SEER database. Multiple imputation (MI) was employed to handle missing data, while propensity score matching (PSM) was conducted to mitigate selection bias in the comparative assessments between the LA group and the No-LA group. Kaplan-Meier analyses and multivariate Cox proportional hazards models were utilized to evaluate both overall survival (OS) and cancer-specific survival (CSS).

RESULTS

A total of 2412 patients diagnosed with SISTs were included in the study, with 879 undergoing LA and 1533 not undergoing LA. There were no significant differences observed between the two cohorts concerning long-term OS (hazard ratio [HR] 0.97, 95% confidence interval [CI] 0.84-1.13, P  = 0.720) and CSS (HR 1.05, 95% CI 0.86-1.29, P = 0.622). After PSM, 1596 patients (798 in the LA group and 789 in the No-LA group) were matched for comparison. There was also no difference in long-term OS and CSS between the two groups. Subgroup analysis revealed that in the age group > 60 years, the CSS in the No-LA group was superior to that in the LA group. Multivariate Cox regression analysis revealed that age, M stage, marital status, and mitotic rate are significant risk factors influencing OS and CSS.

CONCLUSIONS

Conducting LA in patients with SISTs does not enhance long-term prognosis. For patients aged over 60 years, it may be more advisable to refrain from performing LA.

Automated machine learning for predicting liver metastasis in patients with gastrointestinal stromal tumor: a SEER-based analysis

Gastrointestinal stromal tumors (GISTs) are a rare type of tumor that can develop liver metastasis (LIM), significantly impacting the patient's prognosis. This study aimed to predict LIM in GIST patients by constructing machine learning (ML) algorithms to assist clinicians in the decision-making process for treatment. Retrospective analysis was performed using the Surveillance, Epidemiology, and End Results (SEER) database, and cases from 2010 to 2015 were assigned to the developing sets, while cases from 2016 to 2017 were assigned to the testing set. Missing values were addressed using the multiple imputation technique. Four algorithms were utilized to construct the models, comprising traditional logistic regression (LR) and automated machine learning (AutoML) analysis such as gradient boost machine (GBM), deep neural net (DL), and generalized linear model (GLM). We evaluated the models' performance using LR-based metrics, including the area under the receiver operating characteristic curve (AUC), calibration curve, and decision curve analysis (DCA), as well as AutoML-based metrics, such as feature importance, SHapley Additive exPlanation (SHAP) Plots, and Local Interpretable Model Agnostic Explanation (LIME). A total of 6207 patients were included in this study, with 2683, 1780, and 1744 patients allocated to the training, validation, and test sets, respectively. Among the different models evaluated, the GBM model demonstrated the highest performance in the training, validation, and test cohorts, with respective AUC values of 0.805, 0.780, and 0.795. Furthermore, the GBM model outperformed other AutoML models in terms of accuracy, achieving 0.747, 0.700, and 0.706 in the training, validation, and test cohorts, respectively. Additionally, the study revealed that tumor size and tumor location were the most significant predictors influencing the AutoML model's ability to accurately predict LIM. The AutoML model utilizing the GBM algorithm for GIST patients can effectively predict the risk of LIM and provide clinicians with a reference for developing individualized treatment plans.

Effects of surgical management for gastrointestinal stromal tumor patients with liver metastasis on survival outcomes

Purpose

To investigate the effect of surgical resection on survival in gastrointestinal stromal tumors synchronous liver metastasis (GIST-SLM) and to develop clinically usable predictive models for overall survival (OS) and cancer-specific survival (CSS) in patients.

Methods

We identified patients in the SEER database diagnosed with GISTs from 2010 to 2019. We used propensity score matching (PSM) to balance the bias between the Surgery and No surgery groups. Kaplan-Meier(K-M) analysis was used to detect differences in OS and CSS between the two groups. The nomogram to predict 1, 3, and 5-year OS and CSS were developed and evaluated.

Results

After PSM, 228 patients were included in this study. There were significant differences in 1, 3, and 5-year OS and CSS between the two groups (OS: 93.5% vs. 84.4%, 73.2% vs. 55.3%, 60.9% vs. 36.9%, P=0.014; CSS: 3.5% vs.86.2%,75.3% vs.57.9%, 62.6% vs. 42.9%, P=0.02). We also found that patients who received surgery combined with targeted therapy had better OS and CSS at 1, 3, and 5 years than those who received surgery only (OS: 96.6% vs.90.9%, 74.9% vs. 56.8%, 61.7% vs. 35.5%, P=0.022; CSS: 96.6% vs. 92.1%, 77.4% vs.59.2%,63.8% vs. 42.0%, P=0.023). The area under the curve (AUC) was 0.774, 0.737, and 0.741 for 1, 3, and 5-year OS, respectively, with 0.782 and 0.742 for 1, 3, and 5-year CSS. In the model, C-index was 0.703 for OS and 0.705 for CSS and showed good consistency.

Conclusion

Surgical treatment can improve the OS and CSS of patients with GIST-SLM. In addition, the combination with chemotherapy may be more favorable for the long-term survival of patients. Meanwhile, we constructed the nomograms for predicting OS and CSS at 1, 3, and 5-year, and validated them internally. Our model can contribute to clinical management and treatment strategy optimization.

Lymph node metastases in young patients with gastrointestinal stromal tumor: A nationwide analysis

BACKGROUND

Children, adolescents, and young adults (CAYA) (age ≤39 years) with GIST have high rates of LNM, but their clinical relevance is undefined. This study analyzed the impact of LNM on overall survival (OS) for CAYA with GIST.

METHODS

The National Cancer Database was queried for patients with resected GIST and pathologic nodal staging data from 2004-2019. Factors associated with LNM were identified. Survival was assessed stratified by presence of LNM.

RESULTS

Of 4420 patients with GIST, 238 were CAYA (5.4%). When compared to older adults, CAYA more often had small intestine primaries (51.8% vs. 36.6%, p < 0.0001), T4 tumors (30.7% vs. 24.5%, p = 0.0275) and pN1 disease (11.3% vs. 4.7%, p < 0.0001). Within a multivariable Cox proportional hazards regression model adjusting for age, comorbid disease, mitotic rate, tumor size, and primary site, LNM were associated with increased hazard of death for older adults (hazard ratio [HR]: 1.83; confidence interval [CI]: 1.35-2.42; p < 0.0001), but not CAYA (HR: 3.38; CI: 0.50-14.08; p = 0.13). For CAYA, only high mitotic rate predicted mortality (HR: 4.68; CI: 1.41-18.37: p = 0.02).

CONCLUSIONS

LNM are more commonly identified among CAYA with resected GIST who undergo lymph node evaluations, but do not appear to impact OS as observed in older adults. High mitotic rate remains a predictor of poor outcomes for CAYA with GIST.

Simple Scoring Model Based on Enhanced CT in Preoperative Prediction of Biological Risk of Gastrointestinal Stromal Tumor

Objective: To construct a simple scoring model for predicting the biological risk of gastrointestinal stromal tumors based on enhanced computed tomography (CT) features. Methods: The clinicopathological and imaging data of 149 patients with primary gastrointestinal stromal tumor were retrospectively analyzed in our hospital. According to the risk classification, the patients were divided into low-risk group and high-risk group. The features of enhanced CT were observed and recorded. Univariate and multivariate logistic regression models were used to determine the predictors of high-risk biological behaviors of gastrointestinal stromal tumor, and then a simple scoring model was constructed according to the regression coefficients of each predictor. The receiver operating characteristic curve was used to evaluate the predictive ability of the model. Results: There was no significant difference between the risk classification of gastrointestinal stromal tumor with gender and age (P = .168, .320), while significant difference was found between the tumor size and location (P < .001). Univariate and multivariate logistic regression analyses showed that tumor size, enlarged vessels feeding or draining the mass, peritumoral lymph node enlargement, and venous phase contrast enhancement rate were independent predictors of the biological risk of gastrointestinal stromal tumor (P < .05). The area under the curve value of tumor size, enlarged vessels feeding or draining the mass, peritumoral lymph node enlargement, and venous phase contrast enhancement rate as the high-risk predictor of gastrointestinal stromal tumor were 0.955, 0.729, 0.680, and 0.807, respectively. Receiver operating characteristic curve results showed that the area under the curve of the scoring model constructed based on enhanced CT features was 0.941 (95% confidence interval: 0.891-0.973). When the total score was >1, the sensitivity of the scoring model in diagnosing gastrointestinal stromal tumor was 85.58%, the specificity was 88.89%, the positive predictive value was 88.51%, the negative predictive value was 86.04%, and the accuracy was 86.18%. The results of DeLong test showed that the area under the curve of the scoring model was better than that of the receiver operating characteristic curve of tumor size, enlarged vessels feeding or draining the mass, peritumoral lymph node enlargement, venous phase contrast enhancement rate, and other indicators alone in predicting the high risk of gastrointestinal stromal tumor, and the differences were statistically significant (Z = 26.510, P < .001; Z = 3.992, P < .001; Z = 6.353, P < .001; Z = 4.052, P = .013). Conclusion: The simple scoring model based on enhanced CT features is a simple and practical clinical prediction model, which is helpful to make preoperative individualized treatment plan and improve the prognosis of gastrointestinal stromal tumor patients.

Lymph Node Metastases in Gastrointestinal Stromal Tumors: an Uncommon Event

BACKGROUND

Lymph node (LN) metastases are uncommon among gastrointestinal stromal tumors (GISTs), and their presence has not been utilized in disease prognostication. This study was designed to examine factors associated with GIST nodal metastases and their impact on survival.

PATIENTS AND METHODS

Patients undergoing surgical resection of GIST with nodal evaluation were selected from the National Cancer Database. Logistic regression was utilized to evaluate factors associated with LN metastases. Survival was assessed for patients with and without nodal involvement and Cox regression was used to evaluate the impact of LN metastases while adjusting for other prognostic factors.

RESULTS

Out of 5018 patients, 301 (6.0%) had LN involvement. Nodal metastases occurred most frequently among tumors of the stomach (49.5%), followed by the small bowel (43.2%), colorectum (6.0%), and esophagus (1.3%). On multivariable analysis, male sex (OR 1.34), high mitotic rate (OR 2.10), tumor size (OR 1.02), and a primary tumor located in the small bowel (OR 1.36) were all significantly associated with nodal metastases. LN metastases were significantly associated with decreased overall survival (OS) for tumors arising in the small bowel (log-rank p < 0.01) and the colorectum (log-rank p < 0.01). Within a multivariable model adjusting for established prognostic factors, LN metastases remained independently associated with decreased survival (HR 1.60, p < 0.001).

CONCLUSIONS

For GISTs, LN metastases occur more often in males and were associated with tumor size and mitotic activity. Nodal involvement is associated with decreased survival, independent of other well-established prognostic factors.

Prognostic Factors and Management of Colorectal Gastrointestinal Stromal Tumors

Introduction The gastrointestinal stromal tumor (GIST) is the most common mesenchymal neoplasm of the gastrointestinal tract. Even though it can be found in any location of the digestive tract, the colorectal GIST is rare. With this study, we aim to review the current knowledge regarding the prognosis and management of colorectal GIST.

Methods A literature search was conducted in PubMed, and 717 articles were collected. After analyzing these studies, 60 articles were selected to use in this review.

Results The mitotic index, as well as tumor size and location were identified as good discriminators of prognosis in various studies. Surgery remains the only curative therapy for potentially resectable tumors. However, even after surgical resection, some patients develop disease recurrence and metastasis, especially those with high-risk tumors. Therefore, surgical resection alone might be inadequate for the management of all colorectal GISTs. The discovery of GIST's molecular pathway led to a shift in its therapy, insofar as tyrosine kinase inhibitors became part of the treatment schemes for this tumor, revolutionizing the treatment's outcome and prognosis.

Discussion/Conclusion The controversy concerning colorectal GIST prognosis and treatment can be, in part, attributed to the limited number of studies in the literature. In this review, we gathered the most recent knowledge about the prognosis and management of GIST in this rare location and propose two algorithms for its approach. Lastly, we highlight the importance of an individualized approach in the setting of a multidisciplinary team.

Survival outcome of local vs. radical excision in rectal gastrointestinal stromal tumor: a SEER database analysis

Background

The choice of surgical strategy for patients with rectal gastrointestinal stromal tumor (GIST) remains controversial. This study aims to address whether the surgical procedure [local excision (LE) vs. radical excision (RE)] influences the survival outcomes.

Methods

The information of the patients recruited in this study was obtained from the Surveillance, Epidemiology, and End Results (SEER) database. A survival curve was used to evaluate the differences in cancer-specific survival (CSS).

Results

No significant difference was detected in the CSS between the LE and RE groups. Also, no significant differences were observed in the CSS between the two groups with respect to different T classification, N classification, tumor differentiation, tumor size, regional LN surgery, age, gender, race, chemotherapy, and radiotherapy. The T classification and age were independent prognostic factors in rectal GIST patients.

Conclusions

LE and RE have similar survival time after surgery, and LE could be considered as an effective surgical approach for rectal GIST.

Combined model based on enhanced CT texture features in liver metastasis prediction of high-risk gastrointestinal stromal tumors

PURPOSE

To investigate the use of the combined model based on clinical and enhanced CT texture features for predicting the liver metastasis of high-risk gastrointestinal stromal tumors (GISTs).

METHODS

This retrospective study was conducted including 204 patients with pathologically confirmed high-risk GISTs from the Zhejiang Cancer Hospital from January 2015 to June 2021, and 76 cases of them were diagnosed with simultaneous liver metastasis. We randomly divided the cohort into a training cohort (n = 142) and a validation cohort (n = 62) with a ratio of 7:3. All volumes of interest (VOIs) of the high-risk GISTs were manually segmented on the portal venous phase CT images using the ITK-SNAP software. The least absolute shrinkage and selection operator (Lasso) algorithm was performed to determine the most valuable features from a total of 110 texture features extracted by the A-K software to reflect the texture information of the given VOIs. Texture-based predictive model was built from the selected texture features. Independent clinical risk factors were identified through univariate logistic analysis. Then, the texture-based model incorporated the clinical predictors to develop a combined model by multivariate logistic regression. Receiver operating characteristic curve, calibration curve, and decision curve analysis were utilized to analyze the discrimination capacity and clinical application value of the predictive models.

RESULTS

The nine optimal texture features were remained after the reduction of dimension using Lasso method. Another four clinical parameters (BMI, location, gastrointestinal bleeding, and CA125 level) were included in the clinical-based predictive model. Finally, with the combination of remaining texture and clinical features, a multivariate logistic regression classifier was built to predict the liver metastasis potential of high-risk GISTs. The remarkable classification performance of the combined model for the prediction of liver metastasis in the subjects with high-risk GISTs was obtained with area under curve (AUC) = 0.919, sensitivity = 83.9%, specificity = 89.7%, and accuracy = 84.9% in our validation group.

CONCLUSION

The texture-based radiomic signature derived from the portal venous phase CT images could predict liver metastasis of high-risk GISTs in a non-invasive way. Integrating additional clinical variables into the model further leads to an improvement of liver metastasis risk prediction.

Skeletal muscle metastasis from a gastrointestinal stromal tumor: A case report

RATIONALE

Gastrointestinal stromal tumors (GISTs) are the most common mesenchymal tumors of the gastrointestinal tract. Common sites for metastasis are the liver and peritoneum, whereas skeletal muscle metastases are rare.

PATIENT CONCERNS

A 59-year-old man with skeletal muscle metastasis was diagnosed during a period of adjuvant imatinib therapy following the recurrence of GIST of the small intestine.

DIAGNOSIS

The patient was diagnosed with skeletal muscle metastasis of GIST based on immunohistochemistry and molecular pathology analysis results.

INTERVENTION

Extensive resection of the left thigh tumor was performed. The patient underwent whole-exome sequencing of tissue examination. The results suggest that resistance to imatinib may have been developed, and the patient was therefore administered sunitinib instead.

OUTCOMES

Complete remission was observed following sunitinib therapy.

LESSONS

In cases of skeletal muscle metastasis diagnosed during a period of adjuvant imatinib therapy following the recurrence of a GIST of the small intestine, whole exome sequencing may be used to discover more gene variations.

A novel nomogram for predicting liver metastasis in patients with gastrointestinal stromal tumor: a SEER-based study

Background

Liver metastasis (LIM) of gastrointestinal stromal tumor (GIST) is associated with poor prognosis. The present study aimed at developing and validating nomogram to predict LIM in patients with GIST, thus helping clinical diagnosis and treatment.

Methods

The data of GIST patients derived from Surveillance, Epidemiology, and End Results (SEER) database from 2010 to 2016, which were then screened by univariate and multivariate logistic regression for the construction of LIM nomogram. The model discrimination of LIM nomogram was evaluated by concordance index (C-index) and calibration plots, while the predictive accuracy and clinical values were measured by decision curve analysis (DCA) and clinical impact plot. Furthermore, we validated predictive nomogram in the internal testing set.

Results

A total of 3797 patients were enrolled and divided randomly into training and validating groups in a 3-to-1 ratio. After logistic regression, the significant variables were sex, tumor location, tumor size, N stage and mitotic rate. The calibration curves showed the perfect agreement between nomogram predictions and actual observations, while the DCA and clinical impact plot showed the clinical utility of LIM nomogram. C-index of the nomogram was 0.812. What’s more, receiver operating characteristic curves (ROC) also showed good discrimination and calibration in the training set (AUC = 0.794, 95% CI 0.778–0.808) and the testing set (AUC = 0.775, 95% CI 0.748–0.802).

Conclusion

The nomogram for patients with GIST can effectively predict the individualized risk of liver metastasis and provide insightful information to clinicians to optimize therapeutic regimens.

Gastrointestinal stromal tumors (GIST): a proposal of a "CT-based predictive model of Miettinen index" in predicting the risk of malignancy

PURPOSE

To identify the predictors of malignancy on CT for the evaluation of gastrointestinal stromal tumors (GIST) by correlating CT findings with the mitotic index in order to propose a "CT-based predictive model of Miettinen index."

METHODS

One radiologist and one resident in radiology with 14- and 4-year experience in oncological field reviewed the CT findings of 42 patients by consensus, with respect to lesion site, size, contour, tumor growth pattern, enhancing pattern, degree of enhancement of tumor, percentage of tumor necrosis, mesenteric fat infiltration, ulceration, calcification, regional lymphadenopathy, direct invasion to adjacent organs, and distant metastasis. All parameters were correlated with the mitotic index evaluated at histopathological analysis following surgery. Normality of variables was evaluated using Shapiro-Wilk test. Pearson's correlation test was used to assess the interaction between variables. The diagnostic accuracy percentage of tumor necrosis was measured by receiver operating characteristic (ROC) analysis for detecting whether the number of mitosis per 50 high-power fields was > 5.

RESULTS

A significant statistical correlation was found between percentage of tumor necrosis and the mitotic index (p < 0.005), dimension, and location of the tumor.

CONCLUSION

CT could be an accurate technique in the prediction of malignancy of GIST in a CT risk assessment system, based on the location of the tumor, its size, and the percentage of tumor necrosis.

Long-term survival among patients with gastrointestinal stromal tumors diagnosed after another malignancy: a SEER population-based study

Background

To explore overall survival (OS) and GISTs-specific survival (GSS) among cancer survivors developing a second primary gastrointestinal stromal tumors (GISTs).

Methods

We conducted a cohort study, where patients with GISTs after another malignancy (AM-GISTs, n = 851) and those with only GISTs (GISTs-1, n = 7660) were identified from the Surveillance, Epidemiology, and End Results registries (1988–2016). Clinicopathologic characteristics and survival were compared between the two groups.

Results

The most commonly diagnosed first primary malignancy was prostate cancer (27.7%), followed by breast cancer (16.2%). OS among AM-GISTs was significantly inferior to that of GISTs-1; 10-year OS was 40.3% vs. 50.0%, (p < 0.001). A contrary finding was observed for GSS (10-year GSS 68.9% vs. 61.8%, p = 0.002). In the AM-GISTs group, a total of 338 patients died, of which 26.0% died of their initial cancer and 40.8% died of GISTs. Independent of demographics and clinicopathological characteristics, mortality from GISTs among AM-GISTs patients was decreased compared with their GISTs-1 counterparts (HR, 0.71; 95% CI, 0.59–0.84; p < 0.001), whereas OS was inferior among AM-GISTs (HR, 1.11; 95% CI, 0.99–1.25; p = 0.085).

Conclusions

AM-GISTs patients have decreased risk of dying from GISTs compared with GIST-1. Although another malignancy history does not seemingly affect OS for GISTs patients, clinical treatment of such patients should be cautious.

Establishment and Verification of Synchronous Metastatic Nomogram for Gastrointestinal Stromal Tumors (GISTs): A Population-Based Analysis

Aim

Assess the risk of synchronous metastasis and establish a nomogram in patients with GISTs.

Methods

Surveillance, Epidemiology and End Results database (2004-2014) was accessed. With the logistic regression model as the basis, a nomogram was constructed.

Results

7,256 target patients were contained in our study. The nomogram discrimination for mGIST prediction revealed that tumor size contributed most to synchronous metastasis, followed by lymph nodes, extension, pathologic grade, tumor location, and mitotic count. C-index values of predictions were 0.821 (95% CI, 0.805-0.836) and 0.815 (95% CI, 0.800-0.831), and Brier score were 0.109 and 0.112 in training and validation group, respectively. The value of area under the ROCs were 0.813 (p < 0.001) in the primary cohort and 0.819 (p < 0.001) in the validation cohort. Through the calibration curves (as seen in the figures), nomogram prediction proved to have excellent agreement with actual metastatic diseases.

Conclusion

A new nomogram was created that can evaluate synchronous metastatic diseases in patients with GISTs.

Lymphadenectomy is associated with poor survival in patients with gastrointestinal stromal tumors

Background

Current clinical practice suggests lymphadenectomy for gastrointestinal stromal tumor (GIST) patients with enlarged lymph nodes, but little is known about the influence of lymphadenectomy on long-term survival.

Methods

This population-based study consisted of 3,819 non-metastatic GIST patients diagnosed between January 1^st, 2001, to December 31^st, 2015, from the Surveillance, Epidemiology, and End Results (SEER) database. Kaplan-Meier methods and Cox proportion regression models were used to compare differences in overall survival (OS) and cancer-specific survival (CSS) between the lymphadenectomy group and non-lymphadenectomy group.

Results

Among the 3,819 GIST patients, 1,202 received lymphadenectomy and 2,617 did not receive lymphadenectomy. Lymphadenectomy was associated with poor OS (adjusted HR =1.25, 95% CI: 1.06-1.47) and CSS (adjusted HR =1.32, 95% CI: 1.07-1.64) in GIST patients. This was especially evident in GIST patients with a tumor size less than 2 cm (OS, HR =1.91, 95% CI: 0.79-4.60 and CSS, HR =6.37, 95% CI: 1.85-21.90), who were more than 40 years old (OS, HR =1.28, 95% CI: 1.08-1.51 and CSS, HR =1.36, 95% CI: 1.09-1.70), and with a stomach tumor (OS, HR =1.39, 95% CI: 1.12-1.72 and CSS, HR =1.77, 95% CI: 1.33-2.35).

Conclusions

In conclusion, contrary to what was previously presumed, lymphadenectomy was associated with an increased and not a decreased risk of mortality in GIST patients.