Ki-67 labeling index may be a promising indicator to identify "very high-risk" gastrointestinal stromal tumor: a multicenter retrospective study of 1022 patients

Radiomics model based on dual-energy CT venous phase parameters to predict Ki-67 levels in gastrointestinal stromal tumors

Objective

To develop and validate a radiomics model based on the features of the Dual-Energy CT (DECT) venous phase iodine density maps and effective atomic number maps to predict Ki-67 expression levels in gastrointestinal stromal tumors (GISTs).

Methods

A total of 91 patients with GIST were retrospectively analyzed, including 69 patients with low Ki-67 expression (≤5%) and 22 patients with high Ki-67 expression (>5%). Four clinical features (gender, age, maximum tumor diameter, and tumor location) were extracted to construct a clinical model. The venous phase enhanced CT iodine density maps and effective atomic number maps of DSCT were used to build radiomics models. Logistic regression was used to combine radiomics features with clinical features to build a combined model. Finally, the optimal model's discrimination, calibration, and clinical decision curve were validated using the Bootstrap method.

Results

The combined model was identified as the best model, with high predictive performance. The model's discrimination had an AUC of 0.982 (95% CI, 0.9603-1). The calibration test showed a Hosmer-Lemeshow test P-value of 0.99. The clinical decision curve demonstrated a probability threshold range of 15% to 98%, with a high net benefit.

Conclusion

The nomogram model combining clinical features and radiomics (iodine density map radscore + effective atomic number map radscore) has the highest accuracy for preoperative prediction of Ki-67 expression in GISTs.

Sub-regional CT Radiomics for the Prediction of Ki-67 Proliferation Index in Gastrointestinal Stromal Tumors: A Multi-center Study

RATIONALE AND OBJECTIVES

The objective was to assess and examine radiomics models derived from contrast-enhanced CT for their predictive capacity using the sub-regional radiomics regarding the Ki-67 proliferation index (PI) in patients with pathologically confirmed gastrointestinal stromal tumors (GIST).

METHODS

In this retrospective study, a total of 412 GIST patients across three institutions (223 from center 1, 106 from center 2, and 83 from center 3) was enrolled. Radiomic features were derived from various sub-regions of the tumor region of interest employing the K-means approach. The Least Absolute Shrinkage and Selection Operator (LASSO) regression was employed to identify features correlated with Ki-67 PI level in GIST patients. A support vector machine (SVM) model was then constructed to predict the high level of Ki-67 (Ki-67 index >8%), drawing on the radiomics features from each sub-region within the training cohort.

RESULTS

After features selection process, 6, 9, 9, 7 features were obtained to construct SVM models based on sub-region 1, 2, 3 and the entire tumor, respectively. Among different models, the model developed by the sub-region 1 achieved an area under the receiver operating characteristic curve (AUC) of 0.880 (95% confidence interval [CI]: 0.830 to 0.919), 0.852 (95% CI: 0.770-0.914), 0.799 (95% CI: 0.697-0.879) in the training, external test set 1, and 2, respectively.

CONCLUSION

The results of the present study suggested that SVM model based on the sub-regional radiomics features had the potential of predicting Ki-67 PI level in patients with GIST.

Development and interpretation of a multimodal predictive model for prognosis of gastrointestinal stromal tumor

Gastrointestinal stromal tumor (GIST) is the most common mesenchymal original tumor in gastrointestinal (GI) tract and is considered to have varying malignant potential. With the advancement of computer science, radiomics technology and deep learning had been applied in medical researches. It's vital to construct a more accurate and reliable multimodal predictive model for recurrence-free survival (RFS) aiding for clinical decision-making. A total of 254 patients underwent surgery and pathologically diagnosed with GIST in The First Hospital of China Medical University from 2019 to 2022 were included in the study. Preoperative contrast enhanced computerized tomography (CE-CT) and hematoxylin/eosin (H&E) stained whole slide images (WSI) were acquired for analysis. In the present study, we constructed a sum of 11 models while the multimodal model (average C-index of 0.917 on validation set in 10-fold cross validation) performed the best on external validation cohort with an average C-index of 0.864. The multimodal model also reached statistical significance when validated in the external validation cohort (n = 42) with a p-value of 0.0088 which pertained to the recurrence-free survival (RFS) comparison between the high and low groups using the optimal threshold on the predictive score. We also explored the biological significance of radiomics and pathomics features by visualization and quantitative analysis. In the present study, we constructed a multimodal model predicting RFS of GIST which was prior over unimodal models. We also proposed hypothesis on the correlation between morphology of tumor cell and prognosis.

Clinical characteristics and prognostic analysis of postoperative recurrence or metastasis of low-risk gastrointestinal stromal tumors

BACKGROUND

Gastrointestinal stromal tumors (GISTs) are the most common mesenchymal tumors of the digestive tract. This study aimed to investigate the clinical characteristics and prognosis of postoperative recurrence or metastasis in patients with low-risk stromal tumors, in order to take individualized postoperative management and treatment for patients with low-risk GISTs with relatively high recurrence.

METHODS

We retrospectively analyzed the clinicopathological and follow-up data of patients with GISTs who underwent surgical resection in Nanjing Drum Tower Hospital from March 2010 to December 2021. A total of 282 patients with low-risk GISTs were included, none of whom were treated with imatinib. Univariate and multivariate Cox analysis and survival curves were used to explore the relationship between clinical features and recurrence or metastasis in patients with low-risk GISTs.

RESULTS

Of the 282 patients with low-risk GISTs who met inclusion criteria, 14 (4.96%) had recurrence or metastasis. There was a correlation between tumor size, primary site, resection type, Ki67 index, neutrophil lymphocyte ratio (NLR) and CD34 expression and postoperative recurrence or metastasis of GISTs (P < 0.05). Subsequently, multifactorial analysis showed that tumor primary site, tumor size, and Ki67 index were independent risk factors affecting postoperative recurrent or metastasis in patients with low-risk GISTs (P < 0.05). Ultimately, According to Kaplan-Meier analysis, non-gastric primary tumors, larger tumors, and high Ki67 index were significantly associated with poor progression-free survival ( PFS ).

CONCLUSIONS

Tumor location, tumor size and Ki-67 were independent risk factors for postoperative recurrence and metastasis in patients with low-risk GISTs. Based on the 2008 modified NIH recurrence risk grading system, combined with the above three factors, it can be used to evaluate the prognosis of patients with low-risk GISTs and provide personalized postoperative review and follow-up management recommendations.

Deep learning based registration of serial whole-slide histopathology images in different stains

For routine pathology diagnosis and imaging-based biomedical research, Whole-slide image (WSI) analyses have been largely limited to a 2D tissue image space. For a more definitive tissue representation to support fine-resolution spatial and integrative analyses, it is critical to extend such tissue-based investigations to a 3D tissue space with spatially aligned serial tissue WSIs in different stains, such as Hematoxylin and Eosin (H&E) and Immunohistochemistry (IHC) biomarkers. However, such WSI registration is technically challenged by the overwhelming image scale, the complex histology structure change, and the significant difference in tissue appearances in different stains. The goal of this study is to register serial sections from multi-stain histopathology whole-slide image blocks. We propose a novel translation-based deep learning registration network CGNReg that spatially aligns serial WSIs stained in H&E and by IHC biomarkers without prior deformation information for the model training. First, synthetic IHC images are produced from H&E slides through a robust image synthesis algorithm. Next, the synthetic and the real IHC images are registered through a Fully Convolutional Network with multi-scaled deformable vector fields and a joint loss optimization. We perform the registration at the full image resolution, retaining the tissue details in the results. Evaluated with a dataset of 76 breast cancer patients with 1 H&E and 2 IHC serial WSIs for each patient, CGNReg presents promising performance as compared with multiple state-of-the-art systems in our evaluation. Our results suggest that CGNReg can produce promising registration results with serial WSIs in different stains, enabling integrative 3D tissue-based biomedical investigations.

The relationship between Ki-67 expression and imaging signs and pathological features in GISTs

Introduction

To investigate the correlations between the Ki-67 index and plain-scan computerized tomography (CT) signs and pathological features of gastrointestinal stromal tumor (GIST) tissue.

Materials and methods

Data from 186 patients with GIST diagnosed by pathology and immunohistochemistry (IHC) in Peking University First Hospital from May 2016 to May 2022 were analyzed. The patients were divided into two groups: Ki-67 ≤5% and &gt;5%. Correlation analysis, univariate and multivariate Logistic regression analysis were used to explore the correlations between CT signs, pathological features, and Ki-67 expression.

Results

Univariate indicators correlated with the Ki-67 index were mitotic count, pathological grade, tumor hemorrhage, tumor necrosis, tumor size, and tumor density. Multivariate Logistic regression indicated that the mitotic count [odds ratio (OR) 10.222, 95% confidence interval (CI) 4.312–31.039], pathological grade (OR 2.139, 95% CI 1.397–3.350), and tumor size (OR 1.096, 95% CI 1.020–1.190) were independently associated with the Ki-67 expression level. The concordance indexes (C-index) for the pathological features and CT signs models were 0.876 (95% CI 0.822–0.929) and 0.697 (95% CI 0.620–0.774), respectively, with positive predictive values of 93.62% and 58.11% and negative predictive values of 81.29% and 75.89%, respectively. After internal verification by the Bootstrap method, the fitting degree of the pathological features model was found to be better than that of the CT signs model.

Conclusion

Mitotic count, pathological risk grading, and tumor size are independent risk factors correlating with high Ki-67 index. These results indicate that the Ki-67 index reflects tumor malignancy and can predict recurrence and metastasis of GIST.

Radiomics signatures based on contrast-enhanced CT for preoperative prediction of the Ki-67 proliferation state in gastrointestinal stromal tumors

PURPOSE

This study aimed to evaluate the Ki-67 proliferation state in patients with gastrointestinal stromal tumors (GISTs) using radiomics prediction signatures based on contrast-enhanced computed tomography (CE-CT).

MATERIALS AND METHODS

This single-center, retrospective study involved 103 patients (48 men and 55 women, mean age 61.1 ± 10.6 years) who had pathologically confirmed GISTs after curative resection, including 63 with low Ki-67 proliferation level (Ki-67 labeling index ≤ 6%) and 40 with high Ki-67 proliferation level (Ki-67 labeling index > 6%). Radiomics features of the delineated lesions were preoperatively extracted from three-phase CE-CT images, including the arterial, venous, and delayed phases. The most relevant features were selected to construct the radiomics signatures using a logistic regression algorithm. Significant demographic characteristics and semantic features on CT were selected to develop a nomogram along with the optimal radiomics feature. We calculated the sensitivity, specificity, accuracy, F1 score, and area under the receiver operating characteristic (ROC) curve to evaluate the predictive performance of radiomics signatures.

RESULTS

Ten quantitative radiomics features (two first-order and eight texture features) were selected to construct radiomics signatures. The radiomics signature based on the three-phase CE-CT images showed better predictive performance than that based on the single-phase CE-CT images, with an area under the curve (AUC) of 0.83 (95% CI 0.73-0.92) and F1 score of 82% in the training dataset and an AUC of 0.80 (95% CI 0.63-0.95) and F1 score of 75% in the testing dataset. The nomogram showed good calibration.

CONCLUSION

Radiomics signatures using CE-CT images are generalizable and could be used in clinical practice to determine the proliferation state of Ki-67 in GISTs.

Elevated preoperative controlling nutritional status (CONUT) scores as a predictor of postoperative recurrence in gastrointestinal stromal tumors

BACKGROUND

The controlling nutritional status (CONUT) score is associated with the postoperative outcomes in various types of tumors, and its prognostic role in gastrointestinal stromal tumors (GISTs) needs to be clarified.

METHODS

Patients with completely resected primary GISTs in the absence of imatinib adjuvant therapy were included. Recurrence-free survival (RFS) was estimated with the Kaplan-Meier method and compared using log-rank test. Prognostic factors were compared using Cox proportional hazards model.

RESULTS

A total of 455 patients were included. The median follow-up time was 132.0 months (range: 7.0-253.0). Recurrence/metastasis developed in 92 (20.2%) patients. Patients were assigned to three groups: 219 (48.1%) were in normal nutrition group (CONUT = 0-1), 196 (43.1%) were in mild malnutrition group (CONUT = 2-4) and 40 (8.8%) were in moderate-severe malnutrition group (CONUT ≥ 5). Nongastric primary tumor site, large tumor size, high mitotic index, tumor rupture and high CONUT score were independent prognostic factors for shorter RFS using multivariate analysis (p < 0.05).

CONCLUSIONS

Elevated preoperative CONUT score was a predictor of recurrence for patients with resected GIST. The clinical application of the CONUT score is simple and feasible, and might contribute to the individualized treatment of GIST patients.

Building contrast-enhanced CT-based models for preoperatively predicting malignant potential and Ki67 expression of small intestine gastrointestinal stromal tumors (GISTs)

PURPOSE

To assess contrast-enhanced computed tomography (CE-CT) features for predicting malignant potential and Ki67 in small intestinal gastrointestinal stromal tumors (GISTs) and the correlation between them.

METHODS

We retrospectively analyzed the pathological and imaging data for 123 patients (55 male/68 female, mean age: 57.2 years) with a histopathological diagnosis of small intestine GISTs who received CE-CT followed by curative surgery from May 2009 to August 2019. According to postoperatively pathological and immunohistochemical results, patients were categorized by malignant potential and the Ki67 index, respectively. CT features were analyzed to be associated with malignant potential or the Ki67 index using univariate analysis, logistic regression and receiver operating curve analysis. Then, we explored the correlation between the Ki67 index and malignant potential by using the Spearman rank correlation.

RESULTS

Based on univariate and multivariate analysis, a predictive model of malignant potential of small intestine GISTs, consisting of tumor size (p < 0.001) and presence of necrosis (p = 0.033), was developed with the area under the receiver operating curve (AUC) of 0.965 (95% CI, 0.915-0.990; p < 0.001), with 91.53% sensitivity, 96.87% specificity, 96.43% PPV, 92.54% NPV, 94.31% diagnostic accuracy. For high Ki67 expression, a model made up of tumor size (p = 0.051), presence of ulceration (p = 0.054) and metastasis (p = 0.001) may be the best predictive combination with an AUC of 0.785 (95% CI, 0.702-0.854; p < 0.001), 63.33% sensitivity, 76.34% specificity, 46.34% PPV, 86.59% NPV, 73.17% diagnostic accuracy. Ki67 index showed a moderate positive correlation with mitotic count (r = 0.578, p < 0.001), a weak positive correlation with tumor size (r = 0.339, p < 0.001) and with risk stratification (r = 0.364, p < 0.001).

CONCLUSION

Features on CE-CT could preoperatively predict malignant potential and high Ki67 expression of small intestine GISTs, and Ki67 index may be a promising prognostic factor in predicting the prognosis of small intestine GISTs, independent of the risk stratification system.

The analysis of prognostic factors of primary small intestinal gastrointestinal stromal tumors with R0 resection: A single-center retrospective study

OBJECTIVE

We aim to assess factors that affect overall survival in patients with primary small intestinal gastrointestinal stromal tumors (GISTs) who had undergone R0 resection.

METHOD

A retrospective analysis reviewed the data of 82 consecutive confirmed GIST patients at a single medical center in China from January 2012 to June 2020. The survival curve was estimated using the Kaplan-Meier method, and independent prognostic factors were confirmed using the Cox regression model.

RESULTS

A total of 82 patients were included in the study: 42 men and 40 women, the mean age was 59 years old (23-83 years old). Tumors were commonly found in the jejunum (46.3%), ileum (20.7%), and duodenum (32.9%). The median tumor size was 6.0 cm (range: 1.0-15.0 cm). The number of mitoses per one 50 high-power field was used to define the mitotic rates. In our present study, 56 patients presented a mitotic rate ≤5 (68.3%) and 26 patients showed a rate >5 (31.7%) at the time of diagnosis. All patients accepted tumor resection without lymph node resection. The positivity rate was 97.6% for CD117, 96.3% for delay of germination 1, 65.9% for CD34, 6.1% for S-100, and 59.8% for smooth muscle actin using immunohistochemistry. Tumor size, tumor rupture, Ki67 index, mitotic index, and postoperative imatinib were independent prognostic factors for small intestinal GISTs.

CONCLUSIONS

In this study, larger tumor size, high Ki67 index, high mitotic index, the occurrence of tumor rupture, and use of imatinib were independent unfavorable prognostic indicators.

Ki67 for evaluating the prognosis of gastrointestinal stromal tumors: A systematic review and meta‑analysis

Overexpression of Ki67 is observed in tumor cells, and it has been suggested to be a marker for cancer prognosis. However, the relationship between Ki67 expression and the risk of recurrence of gastrointestinal stromal tumors (GISTs) remains poorly defined. In the present study, a meta-analysis was used to examine the associations between Ki67 levels and GIST recurrence. Studies reporting GIST and Ki67 were found by searching Cochrane Library, PubMed and Embase until October 14, 2021. The Newcastle-Ottawa Scale (NOS) was used to verify the quality of the evidence. Totally, 1682 patient cases were included. The odds ratio (OR) estimates and 95% confidence interval (CI) for each publication were determined by a fixed-effects (Mantel-Haenszel) model. A total of 20 studies that fulfilled the inclusion criteria were finally included in the analysis. The average score of quality evaluation was 6.4 points according to NOS. It was found that Ki67 levels were significantly higher in the NIH L group compared with the NIH VL group (OR: 0.51; 95% CI: 0.26-0.99; P=0.04; P heterogeneity=0.44). There was also greater Ki67 overexpression in the NIH I group compared with the NIH L group (OR: 0.45, 95% CI: 0.31-0.65; P<0.0001; P heterogeneity=0.32), while Ki67 levels were greater in the NIH H group than in the NIH I group (OR: 0.20; 95% CI: 0.15-0.28; P<0.00001; P heterogeneity=0.56). In conclusion, Ki67 overexpression may be a useful marker of the risk of recurrent GIST transformation.

Prediction of the Ki-67 expression level and prognosis of gastrointestinal stromal tumors based on CT radiomics nomogram

PURPOSE

To build and validate a radiomics nomogram integrated with the radiomics signature and subjective CT characteristics to predict the Ki-67 expression level of gastrointestinal stromal tumors (GISTs). Moreover, the purpose was to compare the performance of pathological Ki-67 expression level with predicted Ki-67 expression level in estimating the prognosis of GISTs patients.

METHODS

According to pathological results, patients were classified into high-Ki-67 labeling index group (Ki-67 LI ≥ 5%) and low-Ki-67 LI group (Ki-67 LI < 5%). Radiomics features extracted from contrast-enhanced CT(CECT) images were selected and classified to build a radiomics signature. A combined model was built by incorporating radiomics signature and determinant subjective CT characteristics using multivariate logistic regression analysis. The diagnostic performance of the radiomics signature, subjective CT model and combined model were explored by receiver operating characteristic (ROC) curve analysis and Delong test. The model with best diagnostic performance was then set up for the prediction nomogram. Recurrence-free survival (RFS) rates were compared utilizing Kaplan-Meier curve.

RESULTS

The generated combined model yielded the best diagnostic performance with area under the curve (AUC) values of 0.738 [95% confidence interval (CI): 0.669-0.807] and 0.772 (95% CI 0.683-0.860) in the training set and testing set respectively. The nomogram based on the combined model demonstrated good calibration in the training set and testing set (both P > 0.05). Patients of high-Ki-67 LI group predicted by our nomogram had a poorer RFS than patients of low-Ki-67 LI group (P < 0.0001).

CONCLUSION

This radiomics nomogram based on CECT had a satisfactory performance in predicting both the Ki-67 expression level and prognosis noninvasively in patients with GISTs, which may serve as an effective imaging tool that can assist in guiding personalized clinical treatment.

Utility of preoperative computed tomography features in predicting the Ki-67 labeling index of gastric gastrointestinal stromal tumors

PURPOSE

To evaluate the value of preoperative computed tomography (CT) features including morphologic and quantitative features for predicting the Ki-67 labeling index (Ki-67LI) of gastric gastrointestinal stromal tumors (GISTs).

METHODS

We retrospectively included 167 patients with gastric GISTs who underwent preoperative contrast-enhanced CT. We assessed the morphologic features of preoperative CT images and the quantitative features including the maximum diameter of tumor, total tumor volume, mean total tumor CT value, necrosis volume, necrosis volume ratio, enhanced tissue volume, and mean CT value of enhanced tissue. Potential predictive parameters to distinguish the high-level Ki-67LI group (>4%, n = 125) from the low-level Ki-67LI group (≤4%, n = 42) were compared and subsequently determined in multivariable logistic regression analysis.

RESULTS

Growth pattern (p = 0.036), shape (p = 0.000), maximum diameter (p = 0.018), total tumor volume (p = 0.021), mean total tumor CT value (p = 0.009), necrosis volume (p = 0.006), necrosis volume ratio (p = 0.000), enhanced tissue volume (p = 0.027), and mean CT value of enhanced tissue (p = 0.004) were significantly different between the two groups. Multivariate logistic regression analysis indicated that lobulated/irregular shape (odds ratio [OR] = 3.817; p = 0.000) and high necrosis volume ratio (OR = 1.935; p = 0.024) were independent factors of high-level Ki-67LI.

CONCLUSIONS

Higher necrosis volume ratio in combination with lobulated/irregular shape could potentially predict high expression of Ki-67LI for gastric GISTs.

Gastric and Small Intestine Gist: Results of 156 Cases in 20 Years

PURPOSE

Gastric and small intestine are the most common gastrointestinal stromal tumors (GISTs). There are few studies of patients who underwent surgical treatment with disparate findings. We aimed to evaluate the differences between groups and the risk factors for recurrence and mortality.

METHODS

A retrospective study of 96 gastric and 60 small intestine GIST was performed between 1995 and 2015. Both groups were compared in terms of clinicopathologic features, morbidity, recurrence, and mortality. Statistical analysis was performed with SPSS®.

RESULTS

Eighty-one gastric GISTs and 56 small intestine GISTs underwent surgical treatment. Gastrointestinal bleeding was the most common cause of emergency surgery being more frequent in gastric GIST (P = 0.009); however, emergency surgery was indicated more frequently in the small intestinal GIST (P = 0.004) and was mostly due to perforation (P = 0.009). With a median follow-up of 66.9 (39.7-94.8) months, 28 (20.4%) patients had recurrence. A mitotic index > 5 (P ≤ 0.001) and the intestinal location (P = 0.012) were significantly associated to recurrence. Tumor size > 15 cm (P = 0.001) and an age of ≥ 75 years (P = 0.014) were associated to mortality. On univariate analysis, higher mean values of Ki-67 were associated to higher mortality (P = 0.0032). Small intestine GIST presented lower disease-free survival (DFS) than that of gastric GIST (65.7% vs 90.8%) with P = 0.003. The overall survival (OS) of gastric and small intestine GIST was 74.7% and 71.6%, respectively (P = 0.68).

CONCLUSION

Small intestine GIST received emergency surgery more frequently showing lower DFS and same OS than that of gastric GIST. We found that Ki-67 could be a prognostic factor. Further studies are necessary to assess whether Ki-67 is a prognostic risk factor for GISTs.

Evaluation of Ki67 Index in Endoscopic Ultrasound-Guided Fine Needle Aspiration Samples for the Assessment of Malignancy Risk in Gastric Gastrointestinal Stromal Tumors

BACKGROUND

The risk of malignancy in resected gastrointestinal stromal tumors (GISTs) depends on tumor size, location, and mitotic index. Reportedly, the Ki67 index has a prognostic value in resected GISTs. We aimed to analyze the accuracy of endoscopic ultrasound (EUS)-guided fine needle aspiration (FNA) samples with reference to Ki67 index, using surgical specimens as the gold standard.

METHODS

Fifty-five patients who underwent EUS-FNA followed by surgical resection for gastric GISTs were retrospectively analyzed. Patients' age and sex; tumors' size and location; mitotic index, cell type, cellularity, pleomorphism, presence of ulceration, hemorrhage, necrosis, mucosal or serosal invasion, growth pattern, and Ki67 index based on pathology were investigated.

RESULTS

Location in fundus, ulceration, hemorrhage, mucosal invasion, and Ki67 index in surgical specimens were significant in predicting high-risk groups (p < 0.05) on univariate analysis. Frequency of bleeding (p = 0.034) and the Ki67 index (p = 0.018) were the only independent significant factors in multivariate analysis. The optimal cutoff level of Ki67 was 5%, with 88.2% sensitivity and 52.8% specificity (p = 0.021). The mean Ki67 index was lower in EUS-FNA samples than in surgical specimens (2% [1-15] versus 10% [1-70], p = 0.001). The rank correlation coefficient value of Ki67 was 0.199 (p = 0.362) between EUS-FNA and surgical samples and showed no reliability for EUS-FNA samples.

CONCLUSION

The Ki67 index in resected specimens correlated with high-risk GISTs, although it had no additive value to the current criteria. The Ki67 index in EUS-guided FNA samples is not a reliable marker of proliferation in GISTs.

Development and validation of a prognostic nomogram to predict recurrence in high-risk gastrointestinal stromal tumour: A retrospective analysis of two independent cohorts

BACKGROUND

The risk of recurrence in localised, primary gastrointestinal stromal tumour (GIST) classified as high-risk after complete resection varies significantly. Thus, we aimed to develop a nomogram to predict the recurrence of high-risk GIST after surgery to aid patient selection.

METHODS

We retrospectively evaluated patients (n = 424) with high-risk GIST who underwent curative resection as the initial treatment at two high-volume medical centres, between January 2005 and September 2019. The least absolute shrinkage and selection operator (LASSO) regression model was utilised to select potentially relevant features. Multivariate Cox proportional hazards analysis was used to develop a novel nomogram.

FINDINGS

The nomogram comprised age, fibrinogen levels, prognostic nutritional index (PNI), platelet-lymphocyte ratio (PLR), mitotic counts and tumour size, which provided favourable calibration and discrimination in the training dataset with an AUC of 0•749 and a C-index of 0•742 (95%CI:0•689-0•804). Further, it showed acceptable discrimination in the validation cohort, with an AUC of 0•778 and C-index of 0•735 (95%CI:0•634-0•846). The time-dependant receiver operating characteristic (ROC) curves performed well throughout the observation period. Additionally, the nomogram could classify high-risk GISTs into 'very high-risk' and 'general high-risk' groups with a hazard ratio (HR) of 5•190 (95%CI: 3•202-8•414) and 5•438 (95%CI: 2•236-13•229) for the training and validation datasets, respectively.

INTERPRETATION

The nomogram independently predicted post-operative recurrence-free survival (RFS) in high-risk GIST and showed favourable discrimination and calibration values. It may be a useful clinical tool for identifying 'very high-risk' GIST, by allowing treatment strategy optimisation in these patients.

FUNDING

National Natural Science Foundation of China (No. 81702386 and 81874184).

Ki-67 labelling index is related to the risk classification and prognosis of gastrointestinal stromal tumours: a retrospective study

BACKGROUND AND AIMS

Gastrointestinal stromal tumours (GISTs) are the most common mesenchymal tumours of the digestive tract with malignant potential. The current risk classification standard is unable to accurately evaluate the invasiveness and clinical outcomes of GISTs. Ki-67 labelling index (LI) may be an effective indicator in assessing tumour invasiveness and prognosis, however, its exact value in GISTs is still uncertain. The aims of our study were to evaluate the correlation of the Ki-67 LI and clinicopathological features of GISTs and to assess the potential value of the Ki-67 LI in GISTs classification and prognosis.

METHODS

The clinical, pathological and prognostic data were collected and analysed to identify the independent influential factors of GISTs risk stratification and the predictors of GISTs prognosis.

RESULTS

The Ki-67 LI was significantly associated with the clinicopathological features of tumour progression (P<0.05). It was an independent influential factor of GISTs risk classification (odds ratio: 1.322; 95% confidence interval: 1.031-1.696) (P=0.028), and the area under the curve (AUC) value of the Ki-67 LI on the discrimination ability of GISTs risk stratification was 0.906 (P<0.001). The optimal cutoff value of the Ki-67 LI was 6% (sensitivity of 87.5% and specificity of 76.2%), and patients with Ki-67 LI≥6% exhibited significantly poorer progression-free survival (PFS) than those with Ki-67 LI<6% (P<0.001). The AUC value of the Ki-67 LI for predicting PFS in postoperative patients was 0.813 (P=0.03).

CONCLUSIONS

The Ki-67 LI has appreciated value to predict the risk grade and prognosis of GISTs. Patients with Ki-67 LI≥6% are prone to recurrence and metastasis after operation and may need a close follow-up.

The current status of and prospects in research regarding gastrointestinal stromal tumors in China

China still lacks statistical data regarding the incidence of gastrointestinal stromal tumors (GISTs). Data from 3 regions have demonstrated that the incidence of GISTs in China is similar to that in the United States. Furthermore, no significant differences between both nations with regard to epidemiological characteristics and genotyping of GISTs have been reported. Chinese physicians are demonstrating an increased interest in studies regarding GISTs. Currently, to the authors' knowledge, China publishes the most research articles regarding GIST annually worldwide. Despite the paucity of relevant research regarding the clinical practices for GISTs, a series of studies performed by Chinese physicians in the fields of recurrence risk classification, laparoscopic surgery, and adjuvant therapy have contributed to the diagnosis and treatment of GISTs. The lack of innovative drugs, slow approval of new drugs, and insufficient research funds have limited further advancements in GIST-related research in China. In recent years, increased investment in scientific research has allowed for these advancements to be made by creating conditions for Chinese physicians to conduct high-level clinical research. Chinese researchers hope to further shorten the gap between China and the rest of the world in the field of GIST research within a relatively short period. The purpose of the current review article was to present the most updated information regarding the diagnosis and treatment of GISTs in Chinese medical practice and to suggest prospective research in this field.

Standard Approach to Gastrointestinal Stromal Tumors - Differences between China and Europe

Gastrointestinal stromal tumors (GISTs) are the most common mesenchymal tumors of the gastrointestinal tract. With the considerable research and application of molecular-targeted therapy for GISTs in the last two decades, GISTs have become a model of multidisciplinary oncological treatment. Although Western clinical guidelines are available for GISTs, such as those by the European Society of Medical Oncology (ESMO), the clinical situations in China are different from those in European countries. There are distinct differences between the clinical practice, diagnostic methods, surgical approach, and availability of new targeted agents in China and those in Europe. This review summarizes the Chinese GIST consensus guidelines compared to the European ones, which may provide an optimal approach to the diagnosis and management of GIST patients.

Tumor Digital Masking Allows Precise Patient Triaging: A Study Based on Ki-67 Scoring in Gastrointestinal Stromal Tumors

BACKGROUND

Technological advances constantly provide cutting-edge tools that enhance the progress of diagnostic capabilities. Gastrointestinal stromal tumors belong to a family of mesenchymal tumors where patient triaging is still based on traditional criteria such as mitotic count, tumor size, and tumor location. Limitations of the human eye and randomness in choice of area for mitotic figure counting compel us to seek more objective solutions such as digital image analysis. Presently, the labelling of proliferative activity is becoming a routine task amidst many cancers. The purpose of the present study was to compare the traditional method of prediction based on mitotic ratio with digital image analysis of cell cycle-dependent proteins.

METHODS

Fifty-seven eligible cases were enrolled. Furthermore, a digital analysis of previously performed whole tissue section immunohistochemical assays was executed. Digital labelling covered both hotspots and not-hotspots equally.

RESULTS

We noted a significant diversity of proliferative activities, and consequently, the results pointed to 6.5% of Ki-67, counted in hotspots, as the optimal cut-off for low-high-grade GIST. ROC analysis (AUC = 0.913; 95% CI: 0.828-0.997, p < 0.00001) and odds ratio (OR = 40.0, 95% CI: 6.7-237.3, p < 0.0001) pointed to Ki-67 16% as the cut-off for very high-grade (groups 5-6) cases. With help of a tumor digital map, we revealed possible errors resulting from a wrong choice of field for analysis. We confirmed that Ki-67 scores are in line with the level of intracellular metabolism that could be used as the additional biomarker.

CONCLUSIONS

Tumor digital masking is very promising solution for repeatable and objective labelling. Software adjustments of nuclear shape, outlines, size, etc. are helpful to omit other Ki-67-positive cells especially small lymphocytes. Our results pointed to Ki-67 as a good biomarker in GIST, but concurrently, we noted significant differences in used digital approaches which could lead to unequivocal results.

Clinico-pathological characteristics and prognostic factors of gastrointestinal stromal tumors among a Chinese population

Gastrointestinal stromal tumors (GISTs) are the most common mesenchymal neoplasms in the gastrointestinal tract, exhibiting wide variability in their biological behavior. The aim of the present study was to investigate the clinicopathological characteristics and prognostic factors of GISTs in Chinese patients. All GIST cases (n=182) retrieved from the pathology database and the archived files in Shanghai Changzheng Hospital between January 2011 and December 2014 were reviewed. The clinical symptoms, preoperative investigations, treatments, pathological characteristics and follow-up data of these patients were reviewed, and univariate and multivariate survival analyses were performed. A total of 73.1% of the GISTs were located in the stomach, and the most common three symptoms included abdominal pain (30.2%), dyspepsia (23.1%) and gastrointestinal bleeding (21.4%). Univariate analysis revealed that larger tumor size (P<0.001), higher mitotic rate (P<0.001), aggressive behavior (P<0.001), negative smooth muscle actin expression (P=0.009) and palliative resection (P<0.001) contributed toward poor overall survival (OS). In addition, non-gastric disease location (P<0.001), larger tumor size (P<0.001), higher mitotic rate (P=0.004), aggressive behavior (P<0.001) and palliative resection (P<0.001) were associated with poor relapse-free survival (RFS). Multivariate analysis indicated that mitotic rate [hazard ratio (HR=3.761, P=0.015)] and aggressive behavior (HR=3.916, P=0.010) were independent risk factors for OS, while non-gastric location (HR=4.740, P=0.002) and aggressive behavior (HR=4.009, P=0.004) were independent risk factors for RFS. The present study provided information on the clinicopathological characteristics and epidemiology of GISTs in the Chinese population. Non-gastric disease location, higher mitotic rate and tumor metastasis or local invasion prior to treatment were identified as predictors of a poor prognosis.