A Nomogram Predicting Progression Free Survival in Patients with Gastrointestinal Stromal Tumor Receiving Sunitinib: Incorporating Pre-Treatment and Post-Treatment Parameters

Screening high-risk individuals for primary gastric carcinoma: evaluating overall survival probability score in the presence and absence of lymphatic metastasis post-gastrectomy

OBJECTIVE

The aim of this study was to develop and validate prognostic models for predicting overall survival in individuals with gastric carcinoma, specifically focusing on both negative and positive lymphatic metastasis.

METHODS

A total of 1650 patients who underwent radical gastric surgery at Shanxi Cancer Hospital between May 2002 and December 2020 were included in the analysis. Multiple Cox Proportional Hazards analysis was performed to identify key variables associated with overall survival in both negative and positive lymphatic metastasis cases. Internal validation was conducted using bootstrapping to assess the prediction accuracy of the models. Calibration curves were used to demonstrate the accuracy and consistency of the predictions. The discriminative abilities of the prognostic models were evaluated and compared with the 8th edition of AJCC-TNM staging using Harrell's Concordance index, decision curve analysis, and time-dependent receiver operating characteristic curves.

RESULTS

The nomogram for node-negative lymphatic metastasis included variables such as age, pT stage, and maximum tumor diameter. The C-index for this model in internal validation was 0.719, indicating better performance compared to the AJCC 8th edition TNM staging. The nomogram for node-positive lymphatic metastasis included variables such as gender, age, maximum tumor diameter, neural invasion, Lauren classification, and expression of Her-2, CK7, and CD56. The C-index for this model was 0.674, also outperforming the AJCC 8th edition TNM staging. Calibration curves, time-dependent receiver operating characteristic curves, and decision curve analysis for both nomograms demonstrated excellent prediction ability. Furthermore, significant differences in prognosis between low- and high-risk groups supported the models' strong risk stratification performance.

CONCLUSION

This study provides valuable risk stratification models for lymphatic metastasis in gastric carcinoma, encompassing both node-positive and negative cases. These models can help identify low-risk individuals who may not require further intervention, while high-risk individuals can benefit from targeted therapies aimed at addressing lymphatic metastasis.

Predicting the progression-free survival of gastrointestinal stromal tumors after imatinib therapy through multi-sequence magnetic resonance imaging

PURPOSE

Identify radiomics features associated with progression-free survival (PFS) and develop a predictive model for accurate PFS prediction in liver metastatic gastrointestinal stromal tumor patients (GIST).

METHODS

This multi-center retrospective study involved a comprehensive review of clinical and imaging data pertaining to 211 patients with gastrointestinal stromal tumors (GIST) from Center A and B. A total of 147 patients with hepatic metastatic GIST were included, with 102 cases as the training set and 45 cases as the external validation set. Radiomics features were extracted from non-enhanced MR images, specifically T2WI, DWI, and ADC, and relevant features were selected through LASSO-Cox regression. A radiomics nomogram model was then constructed using multivariable Cox regression analysis to effectively predict PFS. The models performance were evaluated with the concordance index (C-index).

RESULTS

The median age of the patients was 53 years, with 82 males and 65 females. A total of 21 radiomics features were selected to generate the radiomics signature. Radiomics signature slightly outperformed the clinical model but without significant difference (P > 0.05). Integrated radiomics signature with clinical features to build a nomogram, which exhibited high predictive performance in both training (C-index 0.757, 95% CI 0.692-0.822) and validation cohorts (C-index 0.718, 95% CI 0.618-0.818). Nomogram significantly outperformed the clinical model (P = 0.002 for training cohort, P < 0.001 for validation cohort). Stable long-term predictions shown by time-dependent ROC analysis (AUC 0.765-0.919 in training, 0.766-0.893 in validation). Multivariable Cox regression confirmed radiomics signature as an independent prognostic factor for preoperative survival prediction in hepatic metastatic GIST patients (HR = 3.973).

CONCLUSION

Radiomics signature is valuable for predicting PFS in metastatic GIST patients. Integrating imaging features and clinical factors into a comprehensive nomogram improves accuracy and effectiveness of survival prognosis, guiding personalized treatment strategies.

A Potential Association of Zinc Deficiency and Tyrosine Kinase Inhibitor-Induced Hand-Foot Skin Reaction

Hand-foot skin reaction (HFSR) is a common skin-related adverse event induced by multikinase inhibitors targeting both platelet-derived growth factor receptor and vascular endothelial growth factor receptor, possibly due to inadequate repair following frictional trauma. Zinc is a trace element and essential nutrient in humans that plays critical roles in the development and differentiation of skin cells. Zinc transporters (Zrt- and Irt-like proteins and Zn transporters) and metallothioneins are involved in zinc efflux, uptake, and homeostasis and have been reported to be involved in skin differentiation. The underlying mechanism of HFSR remains unclear, and the association between HFSR and zinc has not been previously studied. However, some case reports and case series provide potential evidence to suggest that zinc deficiency may be involved in HFSR development and zinc supplementation may relieve HFSR symptoms. However, no large-scale clinical studies have been conducted to examine this role. Therefore, this review summarizes the evidence supporting a possible link between HFSR development and zinc and proposes potential mechanisms underlying this association based on current evidence.

Comprehensive assessment of pretreatment sarcopenia impacts on patients with EGFR-mutated NSCLC treated with afatinib

BACKGROUND

This study aimed to comprehensively evaluate the efficacy and toxicity of afatinib in patients with sarcopenia, an important prognostic factor for treatment efficacy and toxicity in patients with cancer.

METHODS

The clinical features of patients with advanced NSCLC treated with frontline afatinib between 2014 and 2018 at a medical center in Taiwan were retrospectively reviewed. Sarcopenia was evaluated based on the total cross-sectional area of skeletal muscles assessed by computed tomography (CT) imaging at the L3 level. Baseline characteristics, response rates, survival rates, and adverse events (AEs) were compared between sarcopenic and nonsarcopenic patients.

RESULTS

A total of 176 patients evaluated for sarcopenia by CT and treated with afatinib were enrolled in the current study. Sarcopenia was significantly associated with good performance status, low body mass index (BMI), low body surface area (BSA), and low total mass area (TMA). Sarcopenia did not influence the response rate (69.2% vs. 72.0%, p = 0.299), progression-free survival (median 15.9 vs. 14.9 months, p = 0.791), or overall survival (median 26.5 vs. 27.2 months, p = 0.441). However, BSA ≤ 1.7 and the 40 mg afatinib dose were associated with dose reduction. TMA was the only independent factor for afatinib discontinuation due to AEs.

CONCLUSION

Sarcopenia was not associated with treatment efficacy or toxicity among patients with NSCLC harboring common mutations treated with afatinib, indicating sarcopenic patients should not be excluded from afatinib treatment. Other factors, such as BSA and TMA, were associated with dose reduction and afatinib discontinuation, respectively, which may require additional evaluations in future studies.

Prognostic nomograms for gastric carcinoma after D2 + total gastrectomy to assist decision-making for postoperative treatment: based on Lasso regression

OBJECTIVE

This study aimed to establish novel nomograms that could be used to predict the prognosis of gastric carcinoma patients who underwent D2 + total gastrectomy on overall survival (OS) and progression-free survival (PFS).

METHODS

Lasso regression was employed to construct the nomograms. The internal validation process included bootstrapping, which was used to test the accuracy of the predictions. The calibration curve was then used to demonstrate the accuracy and consistency of the predictions. In addition, the Harrell's Concordance index (C-index) and time-dependent receiver operating characteristic (t-ROC) curves were used to evaluate the discriminative abilities of the new nomograms and to compare its performance with the 8th edition of AJCC-TNM staging. Furthermore, decision curve analysis (DCA) was performed to assess the clinical application of our model. Finally, the prognostic risk stratification of gastric cancer was conducted with X-tile software, and the nomograms were converted into a risk-stratifying prognosis model.

RESULTS

LASSO regression analysis identified pT stage, the number of positive lymph nodes, vascular invasion, neural invasion, the maximum diameter of tumor, the Clavien-Dindo classification for complication, and Ki67 as independent risk factors for OS and pT stage, the number of positive lymph nodes, neural invasion, and the maximum diameter of tumor for PFS. The C-index of OS nomogram was 0.719 (95% CI: 0.690-0.748), which was superior to the 8th edition of AJCC-TNM staging (0.704, 95%CI: 0.623-0.783). The C-index of PFS nomogram was 0.694 (95% CI: 0.654-0.713), which was also better than that of the 8th edition of AJCC-TNM staging (0.685, 95% CI: 0.635-0.751). The calibration curves, t-ROC curves, and DCA of the two nomogram models showed that the prediction ability of the two nomogram models was outstanding. The statistical difference in the prognosis between the low- and high-risk groups further suggested that our model had an excellent risk stratification performance.

CONCLUSION

We reported the first risk stratification and nomogram for gastric carcinoma patients with total gastrectomy in Chinese population. Our model could potentially be used to guide treatment selections for the low- and high-risk patients to avoid delayed treatment or unnecessary overtreatment.

A New Online Dynamic Nomogram: Construction and Validation of a Predictive Model for Distant Metastasis Risk and Prognosis in Patients with Gastrointestinal Stromal Tumors

BACKGROUND

Gastrointestinal stromal tumor (GIST) is the most common sarcoma of the digestive tract, among which patients with distant metastases tend to have a poor prognosis. This study aimed to develop a model for predicting distant metastasis in GIST patients and to develop two models for monitoring overall survival (OS) and cancer-specific survival (CSS) in GIST patients with metastasis. This would allow us to develop an optimal, individualized treatment strategy.

METHODS

We reviewed demographic and clinicopathological characteristics data from 2010 to 2017 of patients diagnosed with GIST in the Surveillance, Epidemiology, and End Results (SEER) database. The data of the external validation group was reviewed from the Forth Hospital of Hebei Medical University. Univariate and multivariate logistic regression analyses were used to confirm the independent risk factors for distant metastasis in the GIST patients, and univariate and multivariate Cox regression analyses were performed to identify the independent prognostic factors for OS and CSS in the GIST patients with distant metastasis. Subsequently, three web-based novel nomograms were developed, which were evaluated by the receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA).

RESULTS

Of the 3639 patients who met the inclusion criteria, 418 (11.4%) had distant metastases. The risk factors for distant metastasis in GIST patients included sex, primary site, grade, N stage, tumor size, and mitotic count. For OS, the independent prognosis factors for GIST patients with metastasis included age, race, marital, primary site, chemotherapy, mitotic count, and metastasis at the lung, and for CSS, age, race, marital, primary site, and metastasis at the lung were the independent prognosis factors. Three web-based nomograms were constructed based on these independent factors, respectively. The ROC curves, calibration curves, and DCA were performed in the training, testing, and validation sets which confirmed the high accuracy and strong clinical practice power for the nomograms.

CONCLUSION

Population-based nomograms can help clinicians predict the occurrence and prognosis of distant metastases in patients with GIST, which may be helpful for clinicians to formulate clinical management and appropriate treatment strategies.

Neuropsychiatric Adverse Drug Reactions with Tyrosine Kinase Inhibitors in Gastrointestinal Stromal Tumors: An Analysis from the European Spontaneous Adverse Event Reporting System

Tyrosine kinase inhibitors (TKIs) are widely used in gastrointestinal stromal tumors (GISTs). The aim of this study is to evaluate the reporting frequency of neuropsychiatric adverse drug reactions (ADRs) for TKIs through the analysis of European individual case safety reports (ICSRs). All ICSRs collected in EudraVigilance up to 31 December 2021 with one TKI having GISTs as an indication (imatinib (IM), sunitinib (SU), avapritinib (AVA), regorafenib (REG), and ripretinib (RIP)) were included. A disproportionality analysis was performed to assess the frequency of reporting for each TKI compared to all other TKIs. The number of analyzed ICSRs was 8512, of which 57.9% were related to IM. Neuropsychiatric ADRs were reported at least once in 1511 ICSRs (17.8%). A higher reporting probability of neuropsychiatric ADRs was shown for AVA. Most neuropsychiatric ADRs were known, except for a higher frequency of lumbar spinal cord and nerve root disorders (reporting odds ratio, ROR 4.46; confidence interval, CI 95% 1.58–12.54), olfactory nerve disorders (8.02; 2.44–26.33), and hallucinations (22.96; 8.45–62.36) for AVA. The analyses of European ICSRs largely confirmed the safety profiles of TKIs in GISTs, but some ADRs are worthy of discussion. Further studies are needed to increase the knowledge of the neuropsychiatric disorders of newly approved TKIs.

Pre-Therapeutic Sarcopenia among Cancer Patients: An Up-to-Date Meta-Analysis of Prevalence and Predictive Value during Cancer Treatment

This study will address the prevalence of pre-therapeutic sarcopenia (PS) and its clinical impact during cancer treatment among adult cancer patients ≥ 18 years of age. A meta-analysis (MA) with random-effect models was performed via a MEDLINE systematic review, according to the PRISMA statement, focusing on articles published before February 2022 that reported observational studies and clinical trials on the prevalence of PS and the following outcomes: overall survival (OS), progression-free survival (PFS), post-operative complications (POC), toxicities (TOX), and nosocomial infections (NI). A total of 65,936 patients (mean age: 45.7-85 y) with various cancer sites and extensions and various treatment modes were included. Mainly defined by CT scan-based loss of muscle mass only, the pooled prevalence of PS was 38.0%. The pooled relative risks were 1.97, 1.76, 2.70, 1.47, and 1.76 for OS, PFS, POC, TOX, and NI, respectively (moderate-to-high heterogeneity, I²: 58-85%). Consensus-based algorithm definitions of sarcopenia, integrating low muscle mass and low levels of muscular strength and/or physical performance, lowered the prevalence (22%) and heterogeneity (I² < 50%). They also increased the predictive values with RRs ranging from 2.31 (OS) to 3.52 (POC). PS among cancer patients is prevalent and strongly associated with poor outcomes during cancer treatment, especially when considering a consensus-based algorithm approach.

Sarcopenia as a risk factor of progression-free survival in patients with metastases: a systematic review and meta-analysis

BACKGROUND

Metastasis of cancer causes more than 90% of cancer deaths and is severely damaging to human health. In recent years, several studies have linked sarcopenia to shorter survival in patients with metastatic cancer. Several predictive models exist to predict mortality in patients with metastatic cancer, but have reported limited accuracy.

METHODS

We systematically searched Medline, EMBASE, and the Cochrane Library for articles published on or before October 14, 2022. Pooled Hazard Ratio (HR) estimates with 95% confidence intervals (CIs) were calculated using a random effects model. The primary outcome was an increased risk of death or tumor progression in patients with metastatic cancer, which is expressed as progression-free survival (PFS). In addition, we performed subgroup analyses and leave-one-out sensitivity analyses to explore the main sources of heterogeneity and the stability of the results.

RESULTS

Sixteen retrospective cohort studies with 1,675 patients were included in the 888 papers screened. The results showed that sarcopenia was associated with lower progression-free survival (HR = 1.56, 95% CI = 1.19-2.03, I2 = 76.3%, P < 0.001). This result was further confirmed by trim-and-fill procedures and leave-one-out sensitivity analysis.

CONCLUSIONS

This study suggests that sarcopenia may be a risk factor for reduced progression-free survival in patients with metastatic cancer. Further studies are still needed to explain the reason for this high heterogeneity in outcome.

TRIAL REGISTRATION

CRD42022325910.

SPK1/S1P axis confers gastrointestinal stromal tumors (GISTs) resistance of imatinib

BACKGROUND

Imatinib mesylate (IM) is highly effective in the treatment of gastrointestinal stromal tumors (GISTs). However, the most of GISTs patients develop secondary drug resistance after 1-3 years of IM treatment. The aim of this study was to explore the IM-resistance mechanism via the multi-scope combined with plasma concentration of IM, genetic polymorphisms and plasma sensitive metabolites.

METHODS

This study included a total of 40 GISTs patients who had been regularly treated and not treated with IM. The plasma samples were divided into three experiments, containing therapeutic drug monitoring (TDM), OCT1 genetic polymorphisms and non-targeted metabolomics. According to the data of above three experiments, the IM-resistant cell line, GIST-T1/IMR cells, was constructed for verification the IM-resistance mechanism.

RESULTS

The results of non-targeted metabolomics analysis suggested that the sphingophospholipid metabolic pathway including the SPK1/S1P axis was inferred in IM-insensitive patients with GISTs. A GIST cell line (GIST-T1) was immediately induced as an IM resistance cell model (GIST-T1/IMR) and we found that blocking the signal pathway of SPK1/S1P in the GIST-T1/IMR could sensitize treatment of IM and reverse the IM-resistance.

CONCLUSIONS

Our findings suggest that IM secondary resistance is associated with the elevation of S1P, and blockage the signaling pathway of SPK1/S1P warrants evaluation as a potential therapeutic strategy in IM-resistant GISTs. The design of this study from blood management, group information collection, IM plasma concentration with different elements, identification of sphingolipid metabolism and lastly verification the function of SPK1/S1P in the IM-resistance GISTs cells.

Construction and validation of a prognostic model for gastrointestinal stromal tumors based on copy number alterations and clinicopathological characteristics

Background

The increasing incidence of gastrointestinal stromal tumors (GISTs) has led to the discovery of more novel prognostic markers. We aim to establish an unsupervised prognostic model for the early prediction of the prognosis of future patients with GISTs and to guide clinical treatment.

Methods

We downloaded the GISTs dataset through the cBioPortal website. We extracted clinical information and pathological information, including the microsatellite instability (MSI) score, fraction genome altered (FGA) score, tumor mutational burden (TMB), and copy number alteration burden (CNAB), of patients with GISTs. For survival analysis, we used univariate Cox regression to analyze the contribution of each factor to prognosis and calculated a hazard ratio (HR) and 95% confidence interval (95% CI). For clustering groupings, we used the t-distributed stochastic neighbor embedding (t-SNE) method for data dimensionality reduction. Subsequently, the k-means method was used for clustering analysis.

Results

A total of 395 individuals were included in the study. After dimensionality reduction with t-SNE, all patients were divided into two subgroups. Cluster 1 had worse OS than cluster 2 (HR=3.45, 95% CI, 2.22-5.56, P<0.001). The median MSI score of cluster 1 was 1.09, and the median MSI score of cluster 2 was 0.24, which were significantly different (P<0.001). The FGA score of cluster 1 was 0.28, which was higher than that of cluster 2 (P<0.001). In addition, both the TMB and CNAB of cluster 1 were higher than those of cluster 2, and the P values were less than 0.001.

Conclusion

Based on the CNA of GISTs, patients can be divided into high-risk and low-risk groups. The high-risk group had a higher MSI score, FGA score, TMB and CNAB than the low-risk group. In addition, we established a prognostic nomogram based on the CNA and clinicopathological characteristics of patients with GISTs.

Development and validation of a prognostic model to predict the prognosis of patients with colorectal gastrointestinal stromal tumor: A large international population-based cohort study

Background

Colorectal gastrointestinal stromal tumors (GISTs), mesenchymal malignancy, only accounts for about 6% of GISTs, but prognosis is generally poor. Given the rarity of colorectal GISTs, the prognostic values of clinicopathological features in the patients remain unclear. Nomograms can provide a visual interface to help calculate the predicted probability of a patient meeting a specific clinical endpoint and communicate it to the patient.

Methods

We included a total of 448 patients with colorectal GISTs diagnosed between 2000 and 2019 from the Surveillance, Epidemiology, and End Results (SEER) database. For nomogram construction and validation, patients in the SEER database were divided randomly into the training cohort and internal validation cohort at a ratio of 7:3, while 44 patients with colorectal GISTs from our hospital patient data set between 2010 to 2016 served as the external validation cohort. The OS curves were drawn using the Kaplan–Meier method and assessed using the log-rank test. And, Fine and Gray’s competing-risks regression models were conducted to assess CSS. We performed univariate and multivariate analyses to select prognostic factors for survival time and constructed a predictive nomogram based on the results of the multivariate analysis.

Results

Through univariate and multivariate analyses, it is found that age, primary site, SEER stage, surgery, and tumor size constitute significant risk factors for OS, and age, primary site, histological grade, SEER stage, American Joint Committee for Cancer (AJCC) stage, surgery, and tumor size constitute risk factors for CSS. We found that the nomogram provided a good assessment of OS and CSS at 1-, 3- and 5- year in patients with colorectal GISTs. The calibration plots for the training, internal validation and external validation cohorts at 1-, 3- and 5- year OS and CSS indicated that the predicted survival rates closely correspond to the actual survival rates.

Conclusion

We constructed and validated an unprecedented nomogram to predict OS and CSS in patients with colorectal GISTs. The nomogram had the potential as a clinically predictive tool for colorectal GISTs prognosis, and can be used as a potential, objective and additional tool for clinicians in predicting the prognosis of colorectal GISTs patients worldwide. Clinicians could wield the nomogram to accurately evaluate patients’ OS and CSS, identify high-risk patients, and provide a baseline to optimize treatment plans.

Prognostic nomograms for gastric carcinoma after surgery to assist decision-making for postoperative treatment with chemotherapy cycles <9 or chemotherapy cycles ≥9

Objective

We sought to develop novel nomograms to accurately predict overall survival (OS) of chemotherapy cycles &lt;9 and chemotherapy cycles ≥9 and construct risk stratification to differentiate low-risk and high-risk of two cohorts.

Methods

Patients who underwent curative-intent resection for gastric cancer between January 2002 and May 2020 at a single China institution were identified. Variables associated with OS were recorded and analyzed according to multivariable Cox models. Nomograms predicting 3- and 5-year OS were built according to variables resulting from multivariable Cox models. Discrimination ability was calculated using the Harrell's Concordance Index. The constructed nomogram was subjected to 1,000 resamples bootstrap for internal validation. Calibration curves for the new nomograms were used to test the consistency between the predicted and actual 3- and 5-year OS. Decision curve analysis (DCA) was performed to assess the clinical net benefit. The Concordance index (C-index) and time-dependent receiver operating characteristic (t-ROC) curves were used to evaluate and compare the discriminative abilities of the new nomograms. Finally, prognostic risk stratification of gastric cancer was conducted with X-tile software and nomograms converted into a risk-stratified prognosis model.

Results

For the nomogram predict OS of chemotherapy cycles &lt;9, C-index was 0.711 (95% CI, 0.663–0.760) in internal validation and 0.722 (95% CI, 0.662–0.783) in external validation, which was better than AJCC 8th edition TNM staging (internal validation: 0.627, 95% CI, 0.585–0.670) and (external validation: 0.595,95% CI, 0.543–0.648). The C-index of the nomogram for chemotherapy cycles ≥9 in internal validation was 0.755 (95% CI, 0.728–0.782) and 0.785 (95% CI, 0.747–0.823) in external validation, which was superior to the AJCC 8th edition TNM staging (internal validation: 0.712 95% CI, 0.688–0.737) and (external validation 0.734, 95% CI, 0.699–0.770).The calibration curves, t-ROC curves and DCA of the two nomogram models show that the recognition performance of the two nomogram models was outstanding. The statistical differences in the prognosis among the two risk stratification groups further showed that our model had an excellent risk stratification performance.

Conclusion

This is first reported risk stratification for chemotherapy cycles of gastric carcinoma. Our proposed nomograms can effectively evaluate postoperative prognosis of patients with different chemotherapy cycles of gastric carcinoma. Chemotherapy cycles ≥9 is therefore recommended for high-risk patients with chemotherapy cycles &lt;9, but not for low-risk patients. Meanwhile, combination with multiple therapies are essential to high-risk patients with chemotherapy cycles ≥9 and unnecessary for low-risk patients.

Systemic Therapy for Gastrointestinal Stromal Tumor: Current Standards and Emerging Challenges

Gastrointestinal stromal tumor (GIST), though rare, is the most common mesenchymal tumors of the gastrointestinal tract. KIT or PDGFRα mutation plays as an oncogenic driver in the majority of GISTs. Surgical resection is the only curative treatment for localized disease. The discovery of imatinib with promising anti-tumor effect and successive tyrosine kinase inhibitors (TKI), including second-line sunitinib and third-line regorafenib, revolutionized the management of advanced and metastatic GIST over the past two decades. Recently, ripretinib and avapritinib were approved for the fourth line setting and for PDGFRA exon 18-mutant GIST in first-line setting, respectively. Despite multi-line TKIs exerted ability of disease control, drug resistance remained an obstacle for preventing rapid disease progression. Experimental TKIs or novel therapeutic targets may further improve treatment efficacy. Immune checkpoint inhibitors such as anti-programmed cell death protein-1 (PD1) and anti-CTL-associated antigen 4 (CTLA-4) showed moderate response in early phase trials composed of heavily pretreated patients. KIT/PDGFRα wild-type GISTs are generally less sensitive to imatinib and late-line TKIs. Recent studies demonstrated that targeting fibroblast growth factor receptor signaling may be a potential target for the wild-type GISTs.

Compassionate Use of Ripretinib for Patients With Metastatic Gastrointestinal Stromal Tumors: Taiwan and Hong Kong Experience

Background

Ripretinib was recently approved for the fourth-line targeted therapy for advanced gastrointestinal stromal tumor (GIST) refractory to imatinib, sunitinib, and regorafenib based on the pivotal INVICTUS phase III study. The INVICTUS study demonstrated significantly improved median progression-free survival (PFS) of 6.3 months and an overall survival (OS) insignificant benefit of ripretinib of 15.1 months as compared with placebo in 85 patients with advanced metastatic GIST. However, treatment outcome for the Chinese population, including in Taiwan and Hong Kong, was lacking.

Material and Method

A compassionate study regarding ripretinib use for patients with advanced/metastatic GIST was conducted from March 2020 to March 2021 to assess the treatment efficacy and safety in Taiwan and Hong Kong patients.

Result

Twenty evaluable patients (16 men and 4 women) with heavily pretreated metastatic GIST receiving ripretinib from March 2020 to March 2021 were enrolled to evaluate the treatment outcome. The response and clinical benefit rates to ripretinib were 25% (5/20) and 60% (12/20), respectively. The median PFS and OS in this compassionate cohort receiving ripretinib were 6.1 months and not reachable, respectively. Albumin less than 3.5 and disease progression after ripretinib use were the two independent unfavorable factors for PFS. There were 14 out of 20 (70%) experiencing any grade adverse event (AE). Loss of hair is the most common grade I to II AE with an incidence of 55%. Grade III AEs included diarrhea, skin rash, and anemia with one patient (5%) for each AE.

Conclusions

Late-line ripretinib use in pretreated Taiwan and Hong Kong patients with advanced GIST showed efficacy consistent with the INVICTUS study. Albumin less than 3.5 and disease progression after ripretinib use were the two independent unfavorable factors for PFS. Ripretinib is generally tolerable, with loss of hair being the most common AE.

Multikinase-Inhibitor Screening in Drug-resistant Osteosarcoma Patient-derived Orthotopic Xenograft Mouse Models Identifies the Clinical Potential of Regorafenib

BACKGROUND/AIM

Osteosarcoma is a recalcitrant heterogenous malignancy. The aim of the present study was to compare a series of multikinase inhibitors (MKIs) for efficacy on two drug-resistant osteosarcoma patient-derived orthotopic xenograft (PDOX) models in order to identify a clinical candidate.

MATERIALS AND METHODS

The two osteosarcoma PDOX models were tested for response to the following MKIs: pazopanib, sunitinib, sorafenib, crizotinib, and regorafenib, in comparison to first-line treatment with cisplatinum and an untreated control.

RESULTS

Regorafenib led to regression of osteosarcoma in both PDOXs. Total necrosis was observed pathologically in the regorafenib-treated tumors. Sorafenib arrested growth, without inducing regression, in one osteosarcoma model but not the other, and the other MKIs only slowed tumor growth.

CONCLUSION

The present study demonstrated that regorafenib is much more effective than the other MKIs tested and has clinical potential against recalcitrant osteosarcoma.