Predictor Of Recurrence-free Survival Research Articles

A Prognostic Model of Differentiated Thyroid Cancer Based on Up-Regulated Glycolysis-Related Genes

ObjectiveThis study aims to identify reliable prognostic biomarkers for differentiated thyroid cancer (DTC) based on glycolysis-related genes (GRGs), and to construct a glycolysis-related gene model for predicting the prognosis of DTC patients.MethodsWe retrospectively analyzed the transcriptomic profiles and clinical parameters of 838 thyroid cancer patients from 6 public datasets. Single factor Cox proportional risk regression analysis and Least Absolute Shrinkage and Selection Operator (LASSO) were applied to screen genes related to prognosis based on 2528 GRGs. Then, an optimal prognostic model was developed as well as evaluated by Kaplan-Meier and ROC curves. In addition, the underlying molecular mechanisms in different risk subgroups were also explored via The Cancer Genome Atlas (TCGA) Pan-Cancer study.ResultsThe glycolysis risk score (GRS) outperformed conventional clinicopathological features for recurrence-free survival prediction. The GRS model identified four candidate genes (ADM, MKI67, CD44 and TYMS), and an accurate predictive model of relapse in DTC patients was established that was highly correlated with prognosis (AUC of 0.767). In vitro assays revealed that high expression of those genes increased DTC cancer cell viability and invasion. Functional enrichment analysis indicated that these signature GRGs are involved in remodelling the tumour microenvironment, which has been demonstrated in pan-cancers. Finally, we generated an integrated decision tree and nomogram based on the GRS model and clinicopathological features to optimize risk stratification (AUC of the composite model was 0.815).ConclusionsThe GRG signature-based predictive model may help clinicians provide a prognosis for DTC patients with a high risk of recurrence after surgery and provide further personalized treatment to decrease the chance of relapse.

Development and Validation of a Prognostic Model to Predict Recurrence-Free Survival After Curative Resection for Perihilar Cholangiocarcinoma: A Multicenter Study

BackgroundRecurrence is the main cause of death in perihilar cholangiocarcinoma (pCCA) patients after surgery. Identifying patients with a high risk of recurrence is important for decision-making regarding neoadjuvant therapy to improve long-term outcomes.AimThe objective of this study was to develop and validate a prognostic model to predict recurrence-free survival (RFS) after curative resection of pCCA.MethodsPatients following curative resection for pCCA from January 2008 to January 2016 were identified from a multicenter database. Using random assignment, 70% of patients were assigned to the training cohort, and the remaining 30% were assigned to the validation cohort. Independent predictors of RFS after curative resection for pCCA were identified and used to construct a prognostic model. The predictive performance of the model was assessed using calibration curves and the C-index.ResultsA total of 341 patients were included. The median overall survival (OS) was 22 months, and the median RFS was 14 months. Independent predictors associated with RFS included lymph node involvement, macrovascular invasion, microvascular invasion, maximum tumor size, tumor differentiation, and carbohydrate antigen 19-9. The model incorporating these factors to predict 1-year RFS demonstrated better calibration and better performance than the 8th American Joint Committee on Cancer (AJCC) staging system in both the training and validation cohorts (C-indexes: 0.723 vs. 0.641; 0.743 vs. 0.607).ConclusionsThe prognostic model could identify patients at high risk of recurrence for pCCA to inform patients and surgeons, help guide decision-making for postoperative adjuvant therapy, and improve survival.

Predictors for the Recurrence of Clinically Uterine-Confined Endometrial Cancer and the Role of Cytokeratin Immunohistochemistry Stain in the Era of Sentinel Lymph Node Mapping

Simple SummarySentinel lymph node (SLN) mapping in women with endometrial cancer is gradually gaining popularity worldwide. The objectives of this retrospective study were to elucidate the predictors for cancer recurrence in the era of SLN mapping, and to compare the clinical outcomes between SLN mapping and traditional lymphadenectomy, as well as to investigate the role of cytokeratin immunohistochemistry stain in detecting lymph node metastases. Para-aortic lymph node metastasis was found to be the sole predictor for cancer recurrence. Cytokeratin immunohistochemistry stain detects more lymph node metastases. In addition, both SLN mapping and traditional lymphadenectomy have similar probabilities of cancer recurrence.Background: The primary objective of this study was to elucidate the predictors for cancer recurrence in women with clinically uterine-confined endometrial cancer in the era of sentinel lymph node (SLN) mapping. Methods: All consecutive women with clinically determined uterine-confined endometrial cancer who had lymph node assessment by either SLN mapping or traditional pelvic lymphadenectomy were reviewed. Results: Women in the SLN mapping group had lower total dissected pelvic nodes, lower incidence of para-aortic lymph node dissection, less intraoperative blood loss and lower complication rates, but a longer operation time compared to the traditional lymphadenectomy group. Para-aortic lymph node metastasis (hazard ratio = 7.60, p = 0.03) was the sole independent predictor for recurrence-free survival. In addition, the utilization of cytokeratin immunohistochemistry stain detected more lymph node metastases (adjusted odds ratio = 3.04, p = 0.03). Recurrence-free survival did not differ between SLN mapping and traditional lymphadenectomy groups (p = 0.24). Conclusions: Para-aortic lymph node metastasis is an important predictor of cancer recurrence. Women with negative hematoxylin and eosin stain should undergo cytokeratin immunohistochemistry stain to increase the detection rate of positive lymph node metastasis. Besides, the probabilities of recurrence seem to be similar between SLN mapping and traditional lymphadenectomy groups in women with clinically uterine-confined endometrial cancer.

Impact of deformable registration methods for prediction of recurrence free survival response to neoadjuvant chemotherapy in breast cancer: Results from the ISPY 1/ACRIN 6657 trial

PurposeImage registration plays a vital role in spatially aligning multiple MRI scans for better longitudinal assessment of tumor morphological features. The objective was to evaluate the effect of registration accuracy of six established deformable registration methods(ANTs, DRAMMS, ART, NiftyReg, SSD-FFD, and NMI-FFD) on the predictive value of extracted radiomic features when modeling recurrence-free-survival(RFS) for women after neoadjuvant chemotherapy(NAC) for locally advanced breast cancer. Methods130 women had DCE-MRI scans available from the first two visits in the ISPY1/ACRIN-6657 cohort. We calculated the transformation field from each of the different deformable registration methods, and used it to compute voxel-wise parametric-response-maps(PRM) for established four kinetic features.104-radiomic features were computed from each PRM map to characterize intra-tumor heterogeneity. We evaluated performance for RFS using Cox-regression, C-statistic, and Kaplan-Meier(KM) plots. ResultsA baseline model(F1:Age, Race, and Hormone-receptor-status) had a 0.54 C-statistic, and model F2(baseline + functional-tumor-volume at early treatment visit(FTV2)) had 0.63. The F2+ANTs had the highest C-statistic(0.72) with the smallest landmark differences(5.40±4.40mm) as compared to other models. The KM curve for model F2 gave p=0.004 for separation between women above and below the median hazard compared to the model F1(p=0.31). A models augmented with radiomic features, also achieved significant KM curve separation(p<0.001) except the F2+ART model. ConclusionIncorporating image registration in quantifying changes in tumor heterogeneity during NAC can improve prediction of RFS. Radiomic features of PRM maps derived from warping the DCE-MRI kinetic maps using ANTs registration method further improved the early prediction of RFS as compared to other methods.

Prognostic impact of insulin-like growth factor-I and its binding proteins, insulin-like growth factor-I binding protein-2 and -3, on adverse histopathological features and survival outcomes after radical cystectomy.

ObjectivesInsulin‐like growth factor‐I and its binding proteins are involved in cancer development, progression, and metastasis. In urothelial carcinoma, the impact of this pathway is still poorly investigated. The present large cohort study aimed to evaluate the association of preoperative circulating levels of insulin‐like growth factor‐I, insulin‐like growth factor‐I binding protein‐2 and ‐3 on outcomes after radical cystectomy.MethodsA retrospective cohort study of the plasma specimens from 1036 consecutive urothelial carcinoma patients who were treated with radical cystectomy. The primary and secondary outcomes were adverse histopathological features and survival outcomes. Binominal logistic regression and multivariable Cox regression analyses were performed to assess the association of plasma levels of insulin‐like growth factor‐I, insulin‐like growth factor‐I binding protein‐2 and ‐3 with outcomes.ResultsOn multivariable analysis adjusting for the effects of preoperative variables, lower insulin‐like growth factor‐I binding protein‐2 levels were associated with an increased risk of lymph node metastasis and (any non‐organ confined disease) any non‐organ confined disease. Insulin‐like growth factor‐I binding protein‐3 levels were also inversely independently associated with lymph node metastasis. Receiver operating characteristic curve analysis showed that the addition of insulin‐like growth factor‐I binding proteins biomarkers to a reference model significantly improved the discriminating ability for the prediction of lymph node metastasis (+10.0%, P < 0.001). On multivariable Cox regression models, lower levels of both insulin‐like growth factor‐I binding protein‐2 and ‐3 plasma levels were associated with recurrence‐free survival, cancer‐specific survival, and overall survival. insulin‐like growth factor‐I binding protein‐2 and ‐3 levels and improved the discrimination of a standard reference model for the prediction of recurrence‐free survival, cancer‐specific survival, and overall survival (+4.9%, 4.9%, 2.3%, respectively).ConclusionsPreoperative insulin‐like growth factor‐I binding protein‐2 and ‐3 are significantly associated with features of biologically and clinically aggressive urothelial carcinoma. These biomarkers improved prognostic urothelial carcinoma models.

Impact of adjuvant chemotherapy on prognosis in intrahepatic cholangiocarcinoma patients underwent radical resection

Objectives: To investigate the clinical value of adjuvant chemotherapy(ACT) in patients with intrahepatic cholangiocarcinoma(ICC) who underwent radical resection and to explore the optimal population that can benefit from ACT. Methods: A retrospective cohort study method was adopted. The clinical and pathological data of 685 patients with ICC who underwent curative intent resection in 10 Chinese hepatobiliary surgery centers from January 2010 to December 2018 were collected;There were 355 males and 330 females. The age(M(IQR)) was 58(14) years (range: 22 to 83 years). Propensity score matching(PSM) was applied to balance the differences between the adjuvant and non-adjuvant chemotherapy groups. Log-rank test was used to compare the prognosis of the two groups of patients. A Bayesian network recurrence-free survival(RFS) prediction model was constructed using the median RFS time (14 months) as the target variable, and the importance of the relevant prognostic factors was ranked according to the multistate Birnbaum importance calculation. A survival prognostic prediction table was established to analyze the population benefiting from adjuvant chemotherapy. Results: Among 685 patients,214 received ACT and 471 did not receive ACT. A total of 124 pairs of patients were included after PSM, and patients in the ACT group had better overall survival (OS) and RFS than those in the non-ACT group(OS: 32.2 months vs. 18.0 months,P=0.003;RFS:18.0 months vs. 10.0 months,P=0.001). The area under the curve of the Bayesian network RFS prediction model was 0.7124. The results of the prognostic factors in order of importance were microvascular invasion (0.158 2),perineural invasion (0.158 2),N stage (0.155 8),T stage (0.120 9), hepatic envelope invasion (0.090 3),adjuvant chemotherapy (0.072 1), tumor location (0.057 5), age (0.042 3), pathological differentiation (0.034 0), sex (0.029 3), alpha-fetoprotein (0.028 9) and preoperative jaundice (0.008 5). A survival prediction table based on the variables with importance greater than 0.1 (microvascular invasion,perineural invasion,N stage,T staging) and ACT showed that all patients benefited from ACT (increase in the probability of RFS≥14 months from 2.21% to 7.68%), with a more significant increase in the probability of RFS≥14 months after ACT in early-stage patients. Conclusion: ACT after radical resection in patients with ICC significantly prolongs the OS and RFS of patients, and the benefit of ACT is greater in early patients.

Neutrophil-to-Lymphocyte Ratio Predicts Cancer Outcome in Locally Advanced Clear Renal Cell Carcinoma

To evaluate the association of neutrophil-to-lymphocyte ratio (NLR) with recurrence-free survival (RFS) and overall survival (OS) in patients with locally advanced nonmetastatic clear cell renal cell carcinoma (ccRCC) undergoing radical nephrectomy. We retrospectively identified 880 nephrectomies performed between January 2009 and December 2016 in a single center, reviewed data from 478 radical nephrectomies for kidney tumors and identified 187 patients with locally advanced nonmetastatic ccRCC (pT3-T4 N0M0). NLR was obtained preoperatively and calculated by dividing absolute neutrophil count by absolute lymphocyte count. OS and RFS were evaluated by the Kaplan-Meier method. Cox proportional-hazards regression models were used to evaluate predictors of RFS and OS. Among 187 patients with ccRCC (mean age 63.4 ± 11.5 years; 118 [63.1%] male), the median follow-up was 48.7 months. On univariate analysis, in patients with Fuhrman nuclear grade of differentiation 3-4, the median time to recurrence was significantly shorter with NLR ≥ 4 than < 4 (24 vs. 55 months, P=.045). On multivariable analysis adjusted for NLR ≥ 4, among all variables analyzed (NLR, microvascular invasion, sarcomatoid differentiation, tumor size and body mass index), only nuclear grade of differentiation was an independent predictor of recurrence (hazard ratio 2.18; 95% confidence interval 1.07-4.92, P=.03). The 3-year OS had no statistically significant difference between patients with NLR ≥ 4 or < 4. For patients with locally advanced, nonmetastatic ccRCC, RFS was reduced with high nuclear grade of differentiation and high preoperative NLR. These findings suggest an association between higher NLR and worse outcomes in locally advanced ccRCC.

The Clinical Value of Lipid Abnormalities in Early Stage Cervical Cancer.

BackgroundTo describe the characteristics of plasma lipid proliferation in cervical cancer and further evaluate the prognostic significance of lipid levels in cervical cancer.MethodsWe retrospectively reviewed 1713 patients with cervical cancer in our hospital. The preoperative plasma lipid profile, including cholesterol (TC), triglyceride (TG), high-density lipoprotein cholesterol (HDL), and low-density lipoprotein cholesterol (LDL), of 1713 cervical cancer patients was compared with that of 10,397 healthy women. Then, we evaluated the impact of lipids on overall survival (OS) and recurrence-free survival (RFS) in cervical cancer using univariate and multivariate Cox models.ResultsWhile plasma TC, TG, and LDL were significantly higher, HDL was lower in patients with cervical cancer than in healthy women. TG was identified as an independent predictor for RFS and OS among patients with cervical cancer. Further stratified by age, patients with higher TGs showed a significantly worse RFS and OS than those with lower TGs among patients ≥50 years old but not among those <50 years old.ConclusionCervical cancer was associated with a disordered lipid profile. Hypertriglyceridemia was an independent poor prognostic indicator for cervical cancer, especially for elderly patients. Strengthening lipid management may be beneficial for improving postoperative OS and RFS in patients with cervical cancer.

Deep learning for prediction of hepatocellular carcinoma recurrence after resection or liver transplantation: a discovery and validation study

BackgroundThere is a growing need for new improved classifiers of prognosis in hepatocellular carcinoma (HCC) patients to stratify them effectively.MethodsA deep learning model was developed on a total of 1118 patients from 4 independent cohorts. A nucleus map set (n = 120) was used to train U-net to capture the nuclear architecture. The training set (n = 552) included HCC patients that had been treated by resection. The liver transplantation (LT) set (n = 144) contained patients with HCC that had been treated by LT. The train set and its nuclear architectural information extracted by U-net were used to train the MobileNet V2-based classifier (MobileNetV2_HCC_class). The classifier was then independently tested on the LT set and externally validated on the TCGA set (n = 302). The primary outcome was recurrence free survival (RFS).ResultsThe MobileNetV2_HCC_class was a strong predictor of RFS in both LT set and TCGA set. The classifier provided a hazard ratio of 3.44 (95% CI 2.01–5.87, p < 0.001) for high risk versus low risk in the LT set, and 2.55 (95% CI 1.64–3.99, p < 0.001) when known prognostic factors, remarkable in univariable analyses on the same cohort, were adjusted. The MobileNetV2_HCC_class maintained a relatively higher discriminatory power [time-dependent accuracy and area under curve (AUC)] than other factors after LT or resection in the independent validation set (LT and TCGA set). Net reclassification improvement (NRI) analysis indicated MobileNetV2_HCC_class exhibited better net benefits for the Stage_AJCC beyond other independent factors. A pathological review demonstrated that tumoral areas with the highest recurrence predictability featured the following features: the presence of stroma, a high degree of cytological atypia, nuclear hyperchromasia, and a lack of immune cell infiltration.ConclusionA prognostic classifier for clinical purposes had been proposed based on the use of deep learning on histological slides from HCC patients. This classifier assists in refining the prognostic prediction of HCC patients and identifies patients who have been benefited from more intensive management.

The radiomics-based tumor heterogeneity adds incremental value to the existing prognostic models for predicting outcome in localized clear cell renal cell carcinoma: a multicenter study.

Tumor heterogeneity, which is associated with poor outcomes, has not been exhibited in the University of California, Los Angeles, Integrated Staging System (UISS), and the Stage, Size, Grade and Necrosis (SSIGN) scores. Radiomics allows an in-depth characterization of heterogeneity across the tumor, but its incremental value to the existing prognostic models for clear cell renal cell carcinoma (ccRCC) outcome is unknown. The purpose of this study was to evaluate the association between the radiomics-based tumor heterogeneity and postoperative risk of recurrence in localized ccRCC, and to assess its incremental value to UISS and SSIGN. A multicenter 866 ccRCC patients derived from 12 Chinese hospitals were studied. The endpoint was recurrence-free survival (RFS). A CT-based radiomics signature (RS) was developed and assessed in the whole cohort and in the subgroups stratified by UISS and SSIGN. Two combined nomograms, the R-UISS (combining RS and UISS) and R-SSIGN (combining RS and SSIGN), were developed. The incremental value of RS to UISS and SSIGN in RFS prediction was evaluated. R statistical software was used for statistics. Patients with low radiomics scores were 4.44 times more likely to experience recurrence than those with high radiomics scores (P<0.001). Stratified analysis suggested the association is significant among low- and intermediate-risk patients identified by UISS and SSIGN. The R-UISS and R-SSIGN showed better predictive capability than UISS and SSIGN did with higher C-indices (R-UISS vs. UISS, 0.74 vs. 0.64; R-SSIGN vs. SSIGN, 0.78 vs. 0.76) and higher clinical net benefit. The radiomics-based tumor heterogeneity can predict outcome and add incremental value to the existing prognostic models in localized ccRCC patients. Incorporating radiomics-based tumor heterogeneity in ccRCC prognostic models may provide the opportunity to better surveillance and adjuvant clinical trial design.

Prognostic Role of Preoperative Vascular Cell Adhesion Molecule-1 Plasma Levels in Urothelial Carcinoma of the Bladder Treated With Radical Cystectomy

BackgroundAngiogenesis-related marker vascular cell adhesion molecule-1 (VCAM-1) has been shown to be elevated in urothelial carcinoma of the bladder (UCB), but its predictive/prognostic role has not been determined. Thus, this study aimed to investigate the predictive/prognostic role of VCAM-1 for patients who have UCB treated with radical cystectomy (RC).MethodsThe study enrolled 1036 patients with clinically non-metastatic advanced UCB who underwent RC, and plasma VCAM-1 was evaluated preoperatively. The correlation of plasma VCAM-1 with pathologic and survival outcomes was assessed using binominal logistic regression and multivariable Cox regression analyses. Discrimination was assessed using the area under the curve and concordance indices. The clinical net benefit was evaluated using decision curve analysis (DCA).ResultsPreoperative VCAM-1 was significantly elevated in patients with adverse pathologic features. Higher VCAM-1 levels were independently associated with increased risk of lymph-node-metastasis (LNM), ≥pT3 disease, and non-organ-confined disease (NOCD (p < 0.001 for each). Preoperative plasma VCAM-1 was independently associated with recurrence-free survival (RFS), cancer-specific survival (CSS), and overall survival (OS) in pre- and postoperative multivariable models. Adding VCAM-1 to these predictive models improved their discriminatory ability to predict all outcomes by a significant margin. In the DCA, VCAM-1 addition to the reference models for prediction of LNM, NOCD, RFS, and CSS resulted in relevant improvement.ConclusionsElevated plasma VCAM-1 was associated with biologically and clinically aggressive UCB disease features. After validation, preoperative VCAM-1 may serve as a biomarker to help identify patients likely to benefit from intensified/multimodal therapy. In addition, VCAM-1 improved the discriminatory power of predictive/prognostic models and can be used to refine personalized clinical decision-making.

Risk stratification of LI-RADS M and LI-RADS 4/5 combined hepatocellular cholangiocarcinoma: prognostic values of MR imaging features and clinicopathological factors.

To investigate the role of clinicopathological factors and MR imaging factors in risk stratification of combined hepatocellular cholangiocarcinoma (cHCC-CCA) patients who were classified as LR-M and LR-4/5. We retrospectively identified consecutive patients who were confirmed as cHCC-CCA after surgical surgery in our institution from June 2015 to November 2020. Two radiologists evaluated the preoperative MR imaging features independently, and each lesion was assigned with a LI-RADS category. Preoperative clinical data were also collected. Multivariate Cox proportional hazards model was applied to separately identify the independent factors correlated with the recurrence of cHCC-CCAs in LR-M and LR-4/5. Risk stratifications were conducted separately in LR-M and LR-4/5. Recurrence-free survival (RFS) rates and overall survival (OS) rates were analyzed by using the Kaplan-Meier survival curves and log-rank test. A total of 131 patients with single primary lesion which met the 2019 WHO classification criteria were finally included. Corona enhancement, delayed central enhancement, and microvascular invasion (MVI) were identified as predictors of RFS in LR-M. Mosaic architecture, CA19-9, and MVI were independently associated with RFS in LR-4/5. Based on the number of these independent predictors, patients were stratified into favorable-outcome groups (LR-ML subgroup and LR-4/5L subgroup) and dismal-outcome groups (LR-MH subgroup and LR-4/5H subgroup). The corresponding median RFS for LR-ML, LR-MH, LR-5L, and LR-5H were 25.6 months, 8.2 months, 51.7 months, and 18.1 months. Our study explored the prognostic values of imaging and clinicopathological factors for LR-M and LR-4/5 cHCC-CCA patients, and different survival outcomes were observed among four subgroups after conducting risk stratifications. • Corona enhancement, delayed central enhancement, and MVI were identified as predictors of RFS in cHCC-CCAs which were classified into LR-M. Mosaic architecture, CA19-9, and MVI were independently associated with RFS in cHCC-CCAs which were classified into LR-4/5. • Based on the identified risk factors, LR-M and LR-4/5 cHCC-CCA patients could be stratified into two subgroups respectively, with significantly different RFS and OS. • cHCC-CCA patients from LR-M did not always have worse RFS and OS than those from LR-4/5 in some cases.

Prediction of local tumor control and recurrence-free survival in patients with pancreatic cancer undergoing curative resection after neoadjuvant chemoradiotherapy.

There is little data on the correlation between the reduction in fluorodeoxyglucose positron emission tomography (FDG-PET) radioactive accumulation and carbohydrate antigen 19-9 (CA19-9) levels with pathological tumor responses (PTRs) and prognosis after neoadjuvant chemoradiotherapy (NACRT) for patients with pancreatic ductal adenocarcinoma (PDAC). This study was a retrospective analysis of prospectively collected data from 102 patients with resectable (R-) and borderline resectable (BR-) PDAC who received NACRT,followed by curative resection. Data were prospectively collected and compared between the responders and nonresponders to NACRT. Patients with 60% or more reduction in maximum standardized uptake value (SUVmax) on FDG-PET, with 75% or more reduction in CA19-9 levels, or with 50%-100% of tumor cells destroyed due to NACRT had significantly better recurrence-free survival (RFS) than each of the nonresponders (p = 0.028, <0.001, and 0.022, respectively). The reduction rates of SUVmax and CA19-9 levels were correlated with PTR. The combined evaluation of these biomarkers reflected RFS. Reduction rates of FDG uptake and CA19-9 levels were preoperative predictors of pathological response to NACRT. These biomarkers of local response had prognostic value in R-PDAC and BR-PDAC. The combined evaluation of these biomarkers allowed for reliable prediction of RFS after surgery.

Ipsilateral Recurrence of DCIS in Relation to Radiomics Features on Contrast Enhanced Breast MRI.

The purpose of this retrospective study was to investigate the association between ipsilateral recurrence of ductal carcinoma in situ (DCIS) and radiomics features from DCIS and contralateral normal breast on contrast enhanced breast MR imaging. A total of 163 patients with DCIS who underwent preoperative MR imaging between January 2010 and December 2014 were included (training cohort; n = 117, validation cohort; n = 46). Radiomics features were extracted from whole tumor volume of DCIS on early dynamic T1-subtraction images and from the contralateral normal breast on precontrast T1 and early dynamic T1-subtraction images. After feature selection, a Rad-score was established by LASSO Cox regression model. Performance of Rad-score was evaluated by the receiver operating characteristic (ROC) curve and Kaplan Meier curve with log rank test. The Rad-score was significantly associated with ipsilateral recurrence free survival (RFS). The low-risk group with a low Rad-score showed higher ipsilateral RFS than the high-risk group with a high Rad-score in both training and validation cohorts (p < 0.01). The Rad-score based on radiomics features from DCIS and contralateral normal breast on breast MR imaging showed the potential for prediction of ipsilateral RFS of DCIS.

Factors affecting clinical outcomes in women with non-gastric gastrointestinal stromal tumors

ObjectiveThe clinical presentation of non-gastric GISTs might mimic adnexal cancer, and non-gastric GIST might be managed and treated by gynecologists. Knowledge of the clinical outcomes of women with non-gastric gastrointestinal stromal tumors (GISTs) is important. Our aim is to elucidate the factors affecting the clinical outcomes of women with non-gastric GISTs. Materials and methodsBetween January 2000 and October 2019, all consecutive women with non-gastric GISTs who underwent surgery in a tertiary referral center were reviewed. ResultsTwenty-six women were reviewed. Eight (31%) women experienced recurrence. The probabilities of recurrence-free survival (RFS) at 60 and 120 months were 65.2% and 55.9%, respectively. The probabilities of overall survival (OS) at 60 and 120 months were 71.1% and 63.9%, respectively. Cancer stage was the only independent predictor of RFS (hazard ratio = 6.00, p = 0.007) and OS (hazard ratio = 3.88, p = 0.04). However, excluding cancer stage, metastasis (hazard ratio = 8.74) was the only independent predictor of RFS, and tumor size (hazard ratio = 1.20) and metastasis (hazard ratio = 6.03) were independent predictors of OS. Tumor size ≥13.9 cm was the optimum cut-off value to predict death and had an area under the receiver operating characteristic curve of 0.75 (95% confidence interval = 0.53 to 0.98). Among the above 5 women with non-gastric GISTs admitted to the Gynecology Department, optimal debulking surgery was performed in two women, and small bowel resection was performed in three women; and all five women remained alive without disease. ConclusionNon-gastric GISTs may mimic gynecologic tumors. Metastasis was an independent predictor of PFS. In addition, metastasis and large tumor size (especially ≥13.9 cm) were independent predictors of OS in women with non-gastric GISTs.

Establishment and Validation of Coagulation Factor-Based Nomogram for Predicting the Recurrence-Free Survival of Prostate Cancer

Introduction: We aimed to establish and validate a coagulation feature-based nomogram to predict recurrence-free survival in prostate cancer patients. Methods: The study included 168 prostate cancer patients who had received radical prostatectomy between 2012 and 2018. Kaplan-Meier plot and log-rank analysis were used to screen recurrence-free survival-related features. The nomogram was established by combining the significant coagulation features with clinicopathological characteristics by using Cox regression analysis. The accuracy and clinical significance of the nomogram model were assessed by the receiver operating characteristic curve, Kaplan-Meier plot, and calibration plot. We explored the correlation between coagulation pathway activity and patient prognosis in public datasets by using gene set variation analysis (GSVA). Results: The results suggested that patients classified by the nomogram into the high-risk subgroup showed unfavorable prognoses compared with those in the low-risk subgroup in both the training (log-rank p < 0.0001) and validation (log-rank p = 0.0004) cohorts. The nomogram model exhibited high discriminative accuracy in the training cohort (1-year area under the curve [AUC] of 0.74 and 3-year AUC of 0.69), which was confirmed in the internal validation cohort (C-index = 0.651). The calibration plots confirmed good concordance for the prediction of recurrence-free survival at 1 and 3 years. Subgroup analyses confirmed the utility of this model in different clinicopathological subgroups. Finally, GSVA suggested that patients with higher coagulation pathway scores mostly had unfavorable prognoses compared to those with lower scores, a result consistent with the findings above. Conclusions: We developed a practical nomogram model for predicting recurrence-free survival in prostate cancer patients. This model may offer clinicians prognostic assessments and facilitate personalized treatment.

Abstract P4-06-02: Clinically feasible pharmacokinetic model of dynamic contrast-enhanced MRI is prognostic of recurrence free survival in breast cancer patients treated with neoadjuvant therapy

Abstract Background Dynamic contrast-enhanced (DCE) MRI is commonly used for diagnosis and treatment planning of cancers. Its main use is the identification of tumors in soft tissues, where the tumor progression-induced angiogenic changes result in leaky vasculature which is readily highlighted by contrast enhancement. While allowing tumor morphology assessment, DCE MRI also contains rich information on perfusion and permeability which can be modeled as a pharmacokinetic (PK) process, a subject of extensive investigation in the clinical research setting. Several breast DCE MRI studies have suggested that PK parameters might be indicative of response to therapy and recurrence. However, these studies rely on high temporal resolution DCE MRI for accurate PK modeling, which presents a hurdle to adoption in clinical settings where DCE MRI is acquired with low temporal resolution. Methods We present a novel two-parameter modeling framework which circumvents this temporal limitation, allowing kinetic parameters to be extracted from clinical DCE MRI containing 3-6 timepoints spaced 60-90 seconds apart. We sought to examine whether these kinetic parameters (hereafter KP1 and KP2) binned into "high" and "low" values had prognostic value in determining disease recurrence. KP1 reflects the rate of leakiness from vessels into extravascular space, while KP2 reflects the rate of the reverse process. A study was conducted with a cohort of 458 breast cancer patients treated with neoadjuvant therapy (NAT) in which 117 recurrences occurred. Model parameters were extracted from pre-treatment clinical DCE MRI with low temporal resolution. Univariate and multivariate (Cox Proportional Hazard; CPH) analyses were performed to test the prognostic value of covariates in predicting recurrence free survival (RFS). Results A CPH model was constructed that included age, receptor status, cancer stage, kinetic parameters, and pathologic complete response (pCR) as covariates (Table 1). KP2 and pCR were statistically significantly prognostic markers of RFS (p&amp;lt;0.05). KP1 was not a significant prognostic marker of RFS (p=0.055). Interestingly, KP2 had a hazard ratio (HR) similar to pCR (HR: -1.04 [-1.75, -0.33]; p&amp;lt;0.0039 vs. HR: -0.97 [-1.5, -0.44], p&amp;lt;0.00034). Using univariate analysis, we investigated whether KP2 was prognostic of recurrence. Patients were stratified by therapy type, whether they achieved pCR or had residual disease (RD), and by disease subtype. KP2 was found to be predictive of RFS for patients with RD after treatment with NAT chemotherapy (p&amp;lt;0.0004, n=241, log-rank test), but not for patients treated with anti-HER2 NAT (p=0.84, n=124) or patients that achieved pCR (p=0.68, n=139). KP2 was also found to be prognostic in Hormone Receptor+/HER2- patients with RD (p&amp;lt;0.012, n=151) and Hormone Receptor-/HER2+ patients treated with NAT chemotherapy (p&amp;lt;0.001, n=64). The parameter was not found to be prognostic in patients with triple-negative disease. Conclusions We developed a new prognostic imaging marker for disease recurrence in breast cancer patients treated with NAT that relies on only pre-treatment standard-of-care, low temporal resolution DCE MRI. Since the marker was found to have similar prognostic value in terms of hazard ratio as pCR, but in patients with RD, it could prove to be a powerful tool in patient management after surgery. Table 1.Results of Cox Proportional Hazard model.FactorHazard Ratio95% CIp-valueAge-0.01[-0.02, 0.01]0.51ER+-0.35[-0.85, 0.15]0.17HER2+0.02[-0.38, 0.41]0.93PR+0.05[-0.46, 0.56]0.85Stage II0.54[-0.62, 1.7]0.36Stage III1.08[-0.1, 2.27]0.074KP1-0.68[-1.38, 0.01]0.055KP2-1.04[-1.75, -0.33]0.0039pCR-0.97[-1.5, -0.44]0.00034 Citation Format: Joseph R Peterson, Tyler M. Earnest, Wei Huang, Hiroyuki Abe, John A Cole, Jr. Clinically feasible pharmacokinetic model of dynamic contrast-enhanced MRI is prognostic of recurrence free survival in breast cancer patients treated with neoadjuvant therapy [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P4-06-02.

Clinical usefulness of postoperative serum carcinoembryonic antigen in colorectal cancer patients with liver metastases.

178 Background: Colorectal cancer with liver metastases (CLM) has high post operative recurrence rates, and optimizing the perioperative treatment is imperative. Post operative carcinoembryonic antigen (CEA) can help detecting minimal residual disease in colon cancer after curative resection. Methods: The aim of this study was to identify the potential role of serum CEA after liver resection in patients with CLM. This study was conducted at the Cancer Institute Hospital, Japanese Foundation for Cancer Research from 2004 to 2018. Patients with CLM who underwent complete resection of primary tumors and liver metastases were enrolled in this study. We studied the associations between the perioperative CEA levels and characteristics of recurrence. Results: Recurrence was detected during the median follow-up time of 50.9 months in 343 (54.1%) of the total 633 patients analyzed. Patients with postoperative CEA (&gt;5) group had a significantly higher recurrence rate (75.7% vs 50.0%, p &lt; 0.01), with a shorter time until recurrence (4.4 months vs 36.9 months, p &lt; 0.01) than those with a postoperative CEA level (≤5) group. In multivariate analysis, a postoperative CEA level &gt;5 ng/ ml was an independent predictor, with the highest hazard ratio for both recurrence free survival (RFS) and overall survival (OS) (RFS: 2.77, 95% confidence interval [CI] 2.14–3.60, p &lt;0.01, OS: 3.18, 95% CI 2.41–4.19, p &lt;0.01). In addition, there was a significantly shorter RFS in the postoperative CEA level (&gt;5) group who did not have normalized CEA levels after adjuvant chemotherapy compared to normalized CEA group (3.3 months vs 18.5 months, p = 0.008). Conclusions: The postoperative CEA and postadjuvant chemotherapy CEA level in the CEA level (&gt;5) group after surgery may be a predictor of RFS and OS.

Validation of GIST nomogram performance from a statewide community cancer center.

654 Background: Malignant behavior of Gastrointestinal Stromal Tumors (GISTs) can be predicted based on characteristics (size, location, etc.) which have been used to create risk calculators to anticipate recurrence. The most utilized nomogram (Gold et al 2009) was applied to a patient population from a statewide academic community-based cancer center to evaluate performance compared to that of Memorial Sloan Kettering (MSK), Mayo Clinic and National Spanish Registry (GEIS) populations. Methods: A retrospective review of all operative pathology reports for the past 14 years (January 2005 – May 2019) identified all patients diagnosed with GISTs. Patient demographics, pathology characteristics and recurrence free survival (RFS) was compiled. Those without recurrence or death were censored at the date of their last follow-up within hospital system. The nomogram prediction of RFS was estimated using methods described in the original text. Concordance probabilities for risk stratified quartiles were calculated based on nomogram scores to test performance of the nomogram against our Kaplan-Meier curve. Results: A total of 195 patients were treated for GISTs at our institution within the study timeline. The small majority were female (54%) with an average age of 64 years at presentation (21-90). Only one patient did not follow up within our system (n=194). The most prevalent tumor location was in the stomach (68%) and overall mitotic index was preferentially less than 5 mitosis per high power field (77%). Surgical margins negative of microscopic disease were obtained in 93% of resections. The average tumor size on final pathology was 3.4cm (0.2-29). Within our patient population, 16 (8%) developed recurrences with 1 patient deceased. Kaplan-Meier estimated RFS rates were 91% at 2 years and 88% at 5 years with a mean disease-free survival of 8.8 years (SE=0.2). Concordance probability of the nomogram with our data was found to be 0.82 (95% CI: 0.71-0.92), compared to concordance within the MSK (0.78), GEIS (0.76) and the Mayo Clinic (0.80) populations. Overall, the nomogram predicts a worse 2- and 5-year RFS particularly for the highest risk malignant GISTs (0.82 vs 0.38 and 0.76 vs. 0.21). Conclusions: The concordance of the predictive nomogram was similar in our population to other published series. However, the nomogram overpredicts recurrence rates for the highest risk quartile of GIST patients. Our patient population fared better than the nomogram predicted, in particular for the patients at highest risk of recurrence.[Table: see text]

Lymph node ratio is superior to AJCC N stage for predicting recurrence in papillary thyroid carcinoma.

ObjectiveRecently, lymph node ratio (LNR) has emerged as an alternative to American Joint Committee on Cancer (AJCC) N stage, with superior prognostic value. The utility of LNR in Middle Eastern papillary thyroid carcinoma (PTC) remains unknown. Therefore, we retrospectively analyzed a large cohort of 1407 PTC patients for clinicopathological associations of LNR.MethodsReceiver operating characteristics (ROC) curve was used to determine the cut-off for LNR. We also performed multivariate logistic regression analysis to determine whether LNR or AJCC N stage was superior in predicting recurrence in PTC.ResultsBased on ROC curve analysis, a cut-off of 0.15 was chosen for LNR. High LNR was significantly associated with adverse clinicopathological characteristics such as male sex, extrathyroidal extension, lymphovascular invasion, multifocality, bilateral tumors, T4 tumors, lateral lymph node (N1b) involvement, distant metastasis, advanced tumor stage, American Thyroid Association (ATA) high-risk category and tumor recurrence. On multivariate analysis, we found that LNR was a better predictor of tumor recurrence than AJCC N stage (odds ratio: 1.96 vs 1.30; P value: 0.0184 vs 0.3831). We also found that LNR combined with TNM stage and ATA risk category improved the prediction of recurrence-free survival, compared to TNM stage or ATA risk category alone.ConclusionsThe present study suggests LNR is an independent predictor of recurrence in Middle Eastern PTC. Integration of LNR with 8th edition AJCC TNM staging system and ATA risk stratification will improve the accuracy to predict recurrence in Middle Eastern PTC and help in tailoring treatment and surveillance strategies in these patients.