Ripretinib in advanced gastrointestinal stromal tumors: an overview of current evidence and drug approval

Safety assessment of ripretinib: a real-world adverse event analysis from the food and drug administration adverse event reporting system

Background

Ripretinib has been approved for the treatment of gastrointestinal stromal tumors (GIST). As a novel therapy, several adverse reactions remain unidentified, necessitating a thorough safety evaluation. This study analyzes real-world data from the US Food and Drug Administration Adverse Event Reporting System (FAERS) to investigate adverse events (AEs) associated with ripretinib.

Methods

Adverse event reports (AERs) related to ripretinib were extracted from FAERS ASCII data spanning from the second quarter of 2020 to the second quarter of 2024. Following standardization, various disproportionality analyses, including the reporting odds ratio (ROR), proportional reporting ratio (PRR), bayesian confidence propagation neural network (BCPNN), and empirical bayes geometric mean (EBGM), were employed to identify potential safety signals linked to ripretinib. The data provided by medical professionals underwent sensitivity analysis to assess the robustness of the results.

Results

A total of 3,105 ripretinib-related AERs were identified, categorized into 22 system organ classes (SOCs) and 84 preferred terms (PTs). Common AEs, such as alopecia, constipation, and muscle spasms, were consistent with the drug label and clinical trial findings. Notably, the risk of skin cancer associated with ripretinib was further elucidated. Additionally, new signals, including liver abscess and prostatomegaly, were detected. Despite their lower frequency, these signals demonstrated significant strength. A substantial proportion of adverse reactions (n = 322, 39.80%) occurred within the first month of treatment, although a smaller fraction emerged after one year. The sensitivity analysis revealed that most PTs related to skin and subcutaneous tissue maintained high signal values, with 8 cases of skin squamous cell carcinoma-related AEs still reported.

Conclusion

The findings of this study align with established drug guidance and uncover new adverse event signals for ripretinib, thereby enhancing clinical monitoring and facilitating risk identification.

Ripretinib for the treatment of advanced, imatinib-resistant gastrointestinal stromal tumors

Discovery of constitutive activation of KIT/PDGFRA tyrosine kinases in gastrointestinal stromal tumors (GISTs) leads to the development of the targeted drug imatinib. However, the inevitable development of imatinib resistance remains a major issue. Ripretinib is a novel targeted drug that inhibits the activities of a broad spectrum of drug-resistant KIT/PDGFRA mutants. It was approved in 2020 and is currently recommended by major international guidelines as the fourth-line and beyond therapy for advanced GISTs. Emerging evidence shows that ripretinib is superior to sunitinib as a second-line treatment for KIT exon 11-mutated GISTs due to its activity against highly heterogeneous frequently occurring secondary mutations. This review summarizes current data on the use of ripretinib to treat advanced imatinib-resistant GISTs. We also propose future research directions to improve the targeted GIST treatment.

Efficacy and Safety of Ripretinib in Advanced Gastrointestinal Stromal Tumors within an Expanded Access Program: A Cohort Study

Ripretinib, a novel tyrosine kinase inhibitor used in advanced gastrointestinal stromal tumors (GIST) resistant to standard therapies, was assessed in the United Kingdom (UK) within an Expanded Access Program (EAP). A retrospective review of patients treated between January 2020 and October 2021 within the ripretinib EAP in our Institution was conducted. Clinician-documented and mRECIST 1.1 assessments were collected. The primary endpoints were progression-free survival (PFS) and time to treatment discontinuation (TTD). Treatment beyond progression (TBP), overall survival (OS), objective response rates and safety data were also analyzed. Survival curves were constructed using the Kaplan-Meier method, and univariate and multivariate Cox regression analyses were performed. All analyses were performed with R software. Overall, forty-five patients were included. After a median follow-up of 24.2 (95% CI 19.7-29.7) months, the median PFS of the group receiving 150 mg ripretinib once daily (OD) was 7.9 (95% CI 5.6-19.3) months. In the cohort of 22 patients with dose escalation upon tumor progression to 150 mg ripretinib twice daily (BD), the median PFS from BD was 5.4 (95% CI 2.8-9.3) months. Overall, median PFS and OS values for patients on ripretinib were 9.7 (95% CI 8.3-18.1) and 14.0 (95% CI 9.9-NA) months, respectively. TTD was similar to PFS. TBP was observed in about one third of all patients. Objective responses to ripretinib OD and BD treatments were observed in 16.7% and 10.0% of the patients, respectively. No new safety signals were identified. In conclusion, patients with advanced GIST receiving ripretinib in the UK within the EAP reported prolonged benefits, in line with the recent phase III clinical trials.

Advanced gastrointestinal stromal tumor: reliable classification of imatinib plasma trough concentration via machine learning

AIM

Patients with advanced gastrointestinal stromal tumors (GISTs) exhibiting an imatinib plasma trough concentration (IM Cmin) under 1100 ng/ml may show a reduced drug response rate, leading to the suggestion of monitoring for IM Cmin. Consequently, the objective of this research was to create a customized IM Cmin classification model for patients with advanced GISTs from China.

METHODS

Initial data and laboratory indicators from patients with advanced GISTs were gathered, and the above information was segmented into a training set, validation set, and testing set in a 6:2:2 ratio. Key variables associated with IM Cmin were identified to construct the classification model using the least absolute shrinkage and selection operator (LASSO) regression and forward stepwise binary logistic regression. Within the training and validation sets, nine ML classification models were constructed via the resampling method and underwent comparison through the Brier scores, the areas under the receiver-operating characteristic curve (AUROC), the decision curve, and the precision-recall (AUPR) curve to determine the most suitable model for this dataset. Two methods of internal validation were used to assess the most suitable model's classification performance: tenfold cross-validation and random split-sample validation (test set), and the value of the test set AUROC was used to evaluate the model's classification performance.

RESULTS

Six key variables (gender, daily IM dose, metastatic site, red blood cell count, platelet count, and percentage of neutrophils) were ultimately selected to construct the classification model. In the validation set, it is found by comparison that the Extreme Gradient Boosting (XGBoost) model has the largest AUROC, the lowest Brier score, the largest area under the decision curve, and the largest AUPR value. Furthermore, as evaluated via internal verification, it also performed well in the test set (AUROC = 0.725).

CONCLUSION

For patients with advanced GISTs who receive IM, initial data and laboratory indicators could be used to accurately estimate whether the IM Cmin is below 1100 ng/ml. The XGBoost model may stand a chance to assist clinicians in directing the administration of IM.

Chinese Pedigree with Hereditary Gastrointestinal Stromal Tumors: A Case Report and Literature Review

Familial gastrointestinal stromal tumor (GIST) is a rare autosomal dominant genetic disorder with only a few affected families reported to date. Here, we report a case of familial GISTs harboring a novel germline mutation within exon 18 of KIT. A 58-year-old male patient presented with gastric subepithelial lesions accompanied by cutaneous hyperpigmentation, which were subsequently diagnosed as multinodular GISTs. Endoscopic surgery was initially conducted to remove the larger lesions, and pathological examinations were then conducted for the diagnosis of GISTs. Family history revealed that some other family members had similar cutaneous pigmentations. Whole-exome sequencing was used to search for potential driver mutations, and Sanger sequencing was used for mutation validation. A novel primary driver mutation of KIT (c.G2485C, p.A829P) was detected in these hereditary GISTs, which has been reported in some targeted chemotherapy-resistant GISTs. Cell models were subsequently established for the rapid screening of candidate drugs and exploring potential mechanisms. This mutation could lead to cell proliferation and imatinib resistance by ligand-independent activation of KIT; however, ripretinib administration was identified as an applicable targeted therapy for this mutation. The mutation activated the JAK/STAT3 and MAPK/ERK pathways, which could be inhibited by ripretinib administration. To the best of our knowledge, this is the first report of the KIT-A829P mutation in familial GISTs, complementing the pathogenesis of familial GISTs and providing valuable information for the precision treatment of this disease.