scholarly journals Nomogram for Predicting Recurrence-Free Survival in Chinese Women with Endometrial Cancer after Initial Therapy: External Validation

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Yuan Cheng ◽  
Yangyang Dong ◽  
Wenjuan Tian ◽  
Hua Zhang ◽  
Xiaoping Li ◽  
...  
Keyword(s):  
Endometrial Cancer ◽  
Chinese Women ◽  
External Validation ◽  
Figo Stage ◽  
Peritoneal Cytology ◽  
Tumor Diameter ◽  
Recurrence Free Survival ◽  
Free Survival ◽  
Training Cohort ◽  
Gynecology And Obstetrics

This study aimed at developing an available recurrence-free survival (RFS) model of endometrial cancer (EC) for accurate and individualized prognosis assessment. A training cohort of 520 women with EC who underwent initial surgical treatment and an external validation cohort of 445 eligible EC patients from 2006 to 2016 were analyzed retrospectively. Multivariable Cox proportional hazards regression models were used to develop nomograms for predicting recurrence. The concordance index (C-index) and the area under the receiver operating characteristic curve (AUC) were calculated to determine the discrimination of RFS prognostic scoring systems. Calibration plots were generated to examine the performance characteristics of the predictive nomograms. Regression analysis revealed that an advanced International Federation of Gynecology and Obstetrics (FIGO) stage, histological grade 3, primary tumor diameter ≥2 cm, and positive peritoneal cytology were independent prognostic factors for RFS in EC in the training set. The nomograms estimated RFS according to these four variables, with a C-index of 0.860, which was superior to that of FIGO stage (2009 criteria), at 0.809 (P=0.034), in the training cohort. Encouragingly, consistent results were observed in the validation set, with a C-index of 0.875 for the nomogram and a C-index of 0.833 for the FIGO staging (P=0.0137). Furthermore, the calibrations of the nomograms predicting 3- and 5-year RFS strongly corresponded to the actual survival outcome. In conclusion, this study developed an available nomogram with effective external validation and relatively appreciable discrimination and conformity for the accurate assessment of 3- and 5-year RFS in Chinese women with EC.

scholarly journals FIGO 2018 stage IB endocervical adenocarcinomas: an international study of outcomes informed by prognostic biomarkers

2020 ◽  
pp. ijgc-2020-001893
Author(s):  
Simona Stolnicu ◽  
Monica Boros ◽  
Lien Hoang ◽  
Noorah Almadani ◽  
Louise de Brot ◽  
...  
Keyword(s):  
Overall Survival ◽  
Lymph Node ◽  
Lymphovascular Invasion ◽  
Figo Stage ◽  
Prognostic Biomarkers ◽  
Recurrence Free Survival ◽  
Free Survival ◽  
Stage Ib ◽  
Gynecology And Obstetrics ◽  
Hpv Status

ObjectivePrognostic factors for endocervical adernocarcinomas are well known, but little is known about prognostic biomarkers influencing outcome for the newly defined International Federation of Gynecology and Obstetrics (FIGO) 2018 IB sub-stages. The aim of this study was to identify prognostic biomarkers influencing recurrence-free and overall survival for FIGO 2018 stage IB cervical adenocarcinoma sub-types. We sought to identify these factors using a large international multi-institutional series of cases.MethodsStage IB endocervical adenocarcinomas were retrospectively collected from nine international institutions; full slide sets (n=464) were used to assign prognostic biomarkers. Inclusion criteria were the following: FIGO stage IB endocervical adenocarcinomas with follow-up in which all paraffin blocks/glass slides were available for review and/or additional studies and the patient was surgically treated from 1985 to 2019. The types of specimens included in the study were conizations, trachelectomies, and simple/radical hysterectomies with or without lymph node samples. We excluded in situ carcinomas, squamous cell carcinomas, adenosquamous carcinomas, tumors with a neuroendocrine component, carcinosarcomas, and any tumor showing clinical, macroscopic, or microscopic features suggesting a lower uterine segment, uterine corpus, or an adnexal primary origin. Tumors treated with neoadjuvant chemotherapy and/or radiation therapy were also excluded, as well as biopsies and loop electrosurgical excision procedures.ResultsOf 464 cases, 225 (48%) were stage IB1, 177 (38%) were stage IB2, and 62 (13%) were stage IB3. Five-year and 10-year recurrence-free survivals were statistically different among stage IB sub-types (p=0.005). Silva pattern of invasion was significant for recurrence-free survival at 5 and 10 years (p=0.04); overall survival and recurrence-free survival were higher in human papillomavirus (HPV)-associated cases (p=0.007 and p=0.001, respectively) and in cases without lymphovascular invasion (p=0.004 and p=0.00001, respectively). Factors that significantly influenced recurrence-free survival were HPV-independent status (p=0.05; HR 2.31; 95% CI 1.02 to 5.46), presence of lymphovascular invasion (p=0.011; HR 3.50; 95% CI 1.33 to 9.19), and presence of lymph node metastasis (p=0.016; HR 2.66; 95% CI 1.20 to 5.90).ConclusionHPV status and the presence of lymphovascular invasion are prognosticators in stage IB endocervical adenocarcinoma sub-types. These parameters should be included in future sub-staging modifications of FIGO stage IB endocervical adenocarcinomas and in treatment strategies.

scholarly journals Development, Validation, and Visualization of A Web-Based Nomogram for Predicting the Recurrence-Free Survival Rate of Patients With Desmoid Tumors

2021 ◽  
Vol 11 ◽  
Author(s):  
Haotian Liu ◽  
Kai Huang ◽  
Tao Li ◽  
Tielong Yang ◽  
Zhichao Liao ◽  
...  
Keyword(s):  
Risk Factors ◽  
Desmoid Tumor ◽  
External Validation ◽  
Roc Curves ◽  
Tumor Diameter ◽  
Recurrence Free Survival ◽  
Web Based ◽  
Free Survival ◽  
Tumor Number ◽  
Cox Analysis

BackgroundSurgery is an important treatment option for desmoid tumor (DT) patients, but how to decrease and predict the high recurrence rate remains a major challenge.MethodsDesmoid tumor patients diagnosed and treated at Tianjin Cancer Institute & Hospital were included, and a web-based nomogram was constructed by screening the recurrence-related risk factors using Cox regression analysis. External validation was conducted with data from the Fudan University Shanghai Cancer Center.ResultsA total of 385 patients were identified. Finally, after excluding patients without surgery, patients who were lost to follow-up, and patients without complete resection, a total of 267 patients were included in the nomogram construction. Among these patients, 53 experienced recurrence, with a recurrence rate of 19.85%. The 3-year and 5-year recurrence-free survival (RFS) rates were 82.5% and 78%, respectively. Age, tumor diameter, admission status, location, and tumor number were correlated with recurrence in univariate Cox analysis. In multivariate Cox analysis, only age, tumor diameter and tumor number were independent risk factors for recurrence and were then used to construct a web-based nomogram to predict recurrence. The concordance index (C-index) of the nomogram was 0.718, and the areas under the curves (AUCs) of the 3-year and 5-year receiver operating characteristic (ROC) curves were 0.751 and 0.761, respectively. In the external validation set, the C-index was 0.706, and the AUCs of the 3-year and 5-year ROC curves are 0.788 and 0.794, respectively.ConclusionsAge, tumor diameter, and tumor number were independent predictors of recurrence for DTs, and a web-based nomogram containing these three predictors could accurately predict RFS (https://stepforward.shinyapps.io/Desmoidtumor/).

scholarly journals A Molecule Based Nomogram Optimized the Prediction of Relapse in Stage I NSCLC

2021 ◽  
Author(s):  
Rongrong Bian ◽  
Guorong Zhu ◽  
Feng Zhao ◽  
Rui Chen ◽  
Wengji Xia ◽  
...  
Keyword(s):  
Cox Regression ◽  
Early Stage ◽  
External Validation ◽  
Stage I ◽  
Recursive Feature Elimination ◽  
Support Vector ◽  
Recurrence Free Survival ◽  
Free Survival ◽  
Training Cohort ◽  
Discovery Phase

Abstract Background: Early-stage non-small cell lung cancer (NSCLC) is being diagnosed increasingly, and in 30% of diagnosed patients, recurrence will develop within 5 years. Thus, it is urgent to identify recurrence-related markers in order to optimize the management of patient-tailored therapeutics. The aim of the study was to develop a feasible tool to optimize the recurrence prediction of stage I NSCLC. Methods: The eligible datasets were downloaded from TCGA and GEO. In discovery phase, two algorithms, Least Absolute Shrinkage and Selector Operation and Support Vector Machine-Recursive Feature Elimination, were used to identify candidate genes. Recurrence associated signature was developed by penalized cox regression. The nomogram was constructed and further tested via two independent cohorts. Results: In this retrospective study, 14 eligible datasets and 7 published signatures were included. In discovery phase, 42 significant genes were highlighted as candidate predictors by two algorithms. A 13-gene based signature was generated by penalized cox regression categorized training cohort into high-risk and low-risk subgroups (HR = 8.873, 95% CI:4.228–18.480 P < 0.001). Furthermore, a nomogram integrating the recurrence related signature, age, and histology was developed to predict the recurrence-free survival in the training cohort, which performed well in the two external validation cohorts (concordance index: 0.737, 95%CI:0.732–0.742, P < 0.001; 0.666, 95%CI: 0.650–0.682, P < 0.001; 0.651, 95%CI:0.637–0.665, P < 0.001 respectively). Conclusions: The proposed nomogram is a promising tool for estimating recurrence free survival in stage I NSCLC, which might have tremendous value in guiding adjuvant therapy. Prospective studies are needed to test the clinical utility of the nomogram in individualized management of stage I NSCLC.

Comparison of survival outcomes between laparoscopic and open surgery in patients with low-risk endometrial cancer

2020 ◽  
Vol 50 (11) ◽  
pp. 1261-1264
Author(s):  
Shinichi Togami ◽  
Toshihiko Kawamura ◽  
Shintaro Yanazume ◽  
Masaki Kamio ◽  
Hiroaki Kobayashi
Keyword(s):  
Overall Survival ◽  
Endometrial Cancer ◽  
Laparoscopic Surgery ◽  
Open Surgery ◽  
Low Risk ◽  
Recurrence Free Survival ◽  
Free Survival ◽  
Surgery Group ◽  
Gynecology And Obstetrics ◽  
Surgical Data

Abstract Objective To evaluate the feasibility, safety and surgical outcomes of laparoscopic surgery for the treatment of low-risk endometrial cancer. Methods Of 155 patients with low-risk endometrial cancer, who were included in this retrospective study between May 2008 and March 2017, 82 and 73 underwent laparoscopic and open surgery, respectively. Clinicopathological and surgical data, recurrence-free survival and overall survival were analyzed. Results No statistically significant differences in median age, final pathological type, International Federation of Gynecology and Obstetrics stage and lymphovascular space involvement were observed between the laparoscopic and open surgery groups. No procedure in the laparoscopic surgery group was converted to open surgery. The median follow-up period was 60 months, with oncologic recurrence identified in three cases (one lung carcinoma and two pelvic cavity carcinomas) in the laparoscopic surgery group. There was no significant between-group difference in 5-year recurrence-free survival (laparoscopic surgery group: 96.3%, open surgery group: 92.6%) and overall survival (laparoscopic surgery group: 100%, open surgery group: 95.4%). Conclusions Laparoscopic surgery is a feasible and safe treatment for endometrial cancer and should be considered as a standard treatment option for low-risk endometrial cancer.

scholarly journals Preoperative Assessment for Event-Free Survival With Hepatoblastoma in Pediatric Patients by Developing a CT-Based Radiomics Model

2021 ◽  
Vol 11 ◽  
Author(s):  
Yi Jiang ◽  
Jingjing Sun ◽  
Yuwei Xia ◽  
Yan Cheng ◽  
Linjun Xie ◽  
...  
Keyword(s):  
Risk Factors ◽  
Clinical Decision Making ◽  
Validation Cohort ◽  
External Validation ◽  
Multivariable Analysis ◽  
Tumor Diameter ◽  
Event Free Survival ◽  
Free Survival ◽  
Training Cohort ◽  
Radiomics Signature

Objective: To explore a CT-based radiomics model for preoperative prediction of event-free survival (EFS) in patients with hepatoblastoma and to compare its performance with that of a clinicopathologic model.Patients and Methods: Eighty-eight patients with histologically confirmed hepatoblastoma (mean age: 2.28 ± 2.72 years) were recruited from two institutions between 2002 and 2019 for this retrospective study. They were divided into a training cohort (65 patients from institution A) and a validation cohort (23 patients from institution B). Radiomics features were extracted manually from pretreatment CT images in the portal venous (PV) phase. The least absolute shrinkage and selection operator (LASSO) Cox regression model was applied to construct a “radiomics signature” and radiomics score (Rad-score) for EFS prediction. Then, a nomogram incorporating the Rad-score, updated staging system, and significant variables of clinicopathologic risk (age, alpha-fetoprotein (AFP) level, histology subtype, tumor diameter) as the radiomic model, clinicopathologic model, and combined clinicopathologic-radiomic model were built for EFS estimation in the training cohort, the performance of which was assessed in an external-validation cohort with respect to clinical usefulness, discrimination, and calibration.Results: Nine survival-relevant features were selected for a radiomics signature and Rad-score building. Multivariable analysis revealed that histology subtype (P = 0.01), PV (P = 0.001) invasion, and metastasis (P = 0.047) were independent risk factors of EFS. Patients were divided into low- and high-risk groups based on the Rad-score with a cutoff of 0.08 according to survival outcome. The radiomics signature-incorporated nomogram showed good performance (P &lt; 0.001) for EFS estimation (C-Index: 0.810; 95% CI: 0.738–0.882), which was comparable with that of the clinicopathological model for EFS estimation (C-Index: 0.81 vs. 0.85). The radiomics-based nomogram failed to show incremental prognostic value compared with that using the clinicopathologic model. The combined model (radiomics signature plus clinicopathologic parameters) showed significant improvement in the discriminatory accuracy, along with good calibration and greater net clinical benefit, of EFS (C-Index: 0.88; 95% CI: 0.829–0.933).Conclusion: The radiomics signature can be used as a prognostic indicator for EFS in patients with hepatoblastoma. A combination of the radiomics signature and clinicopathologic risk factors showed better performance in terms of EFS prediction in patients with hepatoblastoma, which enabled precise clinical decision-making.

The Importance of Lymphovascular Invasion in Uterine Adenosarcomas: Analysis of Clinical, Prognostic, and Treatment Outcomes

2018 ◽  
Vol 28 (7) ◽  
pp. 1297-1310 ◽  
Author(s):  
Michael J. Nathenson ◽  
Anthony P. Conley ◽  
Heather Lin ◽  
Nicole Fleming ◽  
Alexander Lazar ◽  
...  
Keyword(s):  
Survival Data ◽  
Lymphovascular Invasion ◽  
Prognostic Significance ◽  
Disease Free Survival ◽  
Myometrial Invasion ◽  
Figo Stage ◽  
Adjuvant Radiation ◽  
Free Survival ◽  
Gynecology And Obstetrics ◽  
Resection Status

ObjectiveThis retrospective study examined the clinicopathologic features of adenosarcoma patients to determine potential prognostic factors and retrospectively evaluated overall survival (OS), disease-free survival (DFS), and local recurrence-free survival (LRFS) after primary treatment of adenosarcoma including surgery, radiation, and chemotherapy.MethodsOne hundred sixty-five patients with adenosarcoma were identified from the MD Anderson Cancer Center tumor registry between 1982 and 2014. Clinical data were collected retrospectively. Pathologic characteristics were examined by sarcoma pathologists. We used the Kaplan-Meier method to estimate OS, DFS, and LRFS. The log-rank test was performed to test the difference in survival between groups. Multivariate regression analyses of survival data were conducted using the Cox proportional hazards model.ResultsMedian OS and DFS for all patients were 8.5 and 4.7 years, respectively. Pathologic characteristics that influence OS and DFS were sarcomatous overgrowth (SO), myometrial invasion (MI), lymphovascular invasion (LVI), tumor size, number of mitosis, estrogen receptor, progesterone receptor, International Federation of Gynecology and Obstetrics (FIGO) stage, age, and resection status. Median OS for adenosarcoma patients with SO was 5.2 versus 14.5 years for patients without SO (P < 0.0001). Median OS for adenosarcoma patients with MI was 5.8 years versus not reached for patients without MI (P = 0.0005). Median OS for adenosarcoma patients with LVI was 1.0 versus 8.9 years for patients without LVI (P = 0.0021). On Cox analysis for OS and DFS and LRFS, only SO, MI, LVI, age, resection status, and FIGO stage remained significant. There was no difference in OS or LRFS for adjuvant radiation versus no adjuvant radiation (P = 0.17, P = 0.076).ConclusionsThis study highlights the importance of LVI as a prognostic factor and confirms the prognostic significance of SO, MI, age, resection status, and FIGO stage for adenosarcoma. Furthermore, this study suggests that there is no additional benefit to adjuvant radiation. The standard-of-care treatment for adenosarcoma should remain total abdominal hysterectomy bilateral salpingo-oophorectomy +/− lymphadenectomy and no adjuvant radiation.

scholarly journals Establishment and Validation of an Integrated Model to Predict Postoperative Recurrence in Patients With Atypical Meningioma

2021 ◽  
Vol 11 ◽  
Author(s):  
Xiao-Yong Chen ◽  
Jin-Yuan Chen ◽  
Yin-Xing Huang ◽  
Jia-Heng Xu ◽  
Wei-Wei Sun ◽  
...  
Keyword(s):  
Cox Regression ◽  
Validation Cohort ◽  
Clinical Laboratory ◽  
External Validation ◽  
Postoperative Recurrence ◽  
Integrated Model ◽  
Atypical Meningioma ◽  
Tumor Diameter ◽  
Roc Curve Analysis ◽  
Training Cohort

BackgroundThis study aims to establish an integrated model based on clinical, laboratory, radiological, and pathological factors to predict the postoperative recurrence of atypical meningioma (AM).Materials and MethodsA retrospective study of 183 patients with AM was conducted. Patients were randomly divided into a training cohort (n = 128) and an external validation cohort (n = 55). Univariable and multivariable Cox regression analyses, the least absolute shrinkage and selection operator (LASSO) regression analysis, time-dependent receiver operating characteristic (ROC) curve analysis, and evaluation of clinical usage were used to select variables for the final nomogram model.ResultsAfter multivariable Cox analysis, serum fibrinogen &gt;2.95 g/L (hazard ratio (HR), 2.43; 95% confidence interval (CI), 1.05–5.63; p = 0.039), tumor located in skull base (HR, 6.59; 95% CI, 2.46-17.68; p &lt; 0.001), Simpson grades III–IV (HR, 2.73; 95% CI, 1.01–7.34; p = 0.047), tumor diameter &gt;4.91 cm (HR, 7.10; 95% CI, 2.52–19.95; p &lt; 0.001), and mitotic level ≥4/high power field (HR, 2.80; 95% CI, 1.16–6.74; p = 0.021) were independently associated with AM recurrence. Mitotic level was excluded after LASSO analysis, and it did not improve the predictive performance and clinical usage of the model. Therefore, the other four factors were integrated into the nomogram model, which showed good discrimination abilities in training cohort (C-index, 0.822; 95% CI, 0.759–0.885) and validation cohort (C-index, 0.817; 95% CI, 0.716–0.918) and good match between the predicted and observed probability of recurrence-free survival.ConclusionOur study established an integrated model to predict the postoperative recurrence of AM.

scholarly journals A methylomics-correlated nomogram predicts the recurrence free survival risk of kidney renal clear cell carcinoma

2021 ◽  
Vol 18 (6) ◽  
pp. 8559-8576
Author(s):  
Xiuxian Zhu ◽  
◽  
Xianxiong Ma ◽  
Chuanqing Wu
Keyword(s):  
Dna Methylation ◽  
Cell Carcinoma ◽  
Roc Analysis ◽  
Clear Cell ◽  
Clear Cell Carcinoma ◽  
External Validation ◽  
Renal Clear Cell Carcinoma ◽  
Recurrence Free Survival ◽  
Free Survival ◽  
Validation Set

<abstract> <sec><title>Background</title><p>Various studies have suggested that the DNA methylation signatures were promising to identify novel hallmarks for predicting prognosis of cancer. However, few studies have explored the capacity of DNA methylation for prognostic prediction in patients with kidney renal clear cell carcinoma (KIRC). It's very promising to develop a methylomics-related signature for predicting prognosis of KIRC.</p> </sec> <sec><title>Methods</title><p>The 282 patients with complete DNA methylation data and corresponding clinical information were selected to construct the prognostic model. The 282 patients were grouped into a training set (70%, n = 198 samples) to determine a prognostic predictor by univariate Cox proportional hazard analysis, least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analysis. The internal validation set (30%, n = 84) and an external validation set (E-MTAB-3274) were used to validate the predictive value of the predictor by receiver operating characteristic (ROC) analysis and Kaplan–Meier survival analysis.</p> </sec> <sec><title>Results</title><p>We successfully identified a 9-DNA methylation signature for recurrence free survival (RFS) of KIRC patients. We proved the strong robustness of the 9-DNA methylation signature for predicting RFS through ROC analysis (AUC at 1, 3, 5 years in internal dataset (0.859, 0.840, 0.817, respectively), external validation dataset (0.674, 0.739, 0.793, respectively), entire TCGA dataset (0.834, 0.862, 0.842, respectively)). In addition, a nomogram combining methylation risk score with the conventional clinic-related covariates was constructed to improve the prognostic predicted ability for KIRC patients. The result implied a good performance of the nomogram.</p> </sec> <sec><title>Conclusions</title><p>we successfully identified a DNA methylation-associated nomogram, which was helpful in improving the prognostic predictive ability of KIRC patients.</p> </sec> </abstract>

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