Nomogram for predicting the overall survival of patients with inflammatory breast cancer: A SEER-based study

Pan, Xinliang; Yang, Wen; Chen, Yongfa; Tong, Lihua; Li, Churong; Li, Hui

doi:10.1016/j.breast.2019.05.015

Cited by 58 publications

(52 citation statements)

References 18 publications

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“…Surgery, radiotherapy, and chemotherapy were all independent prognostic risk factors for IBC patients, indicating that multimodal comprehensive treatment could benefit IBC patients significantly (Diao et al, 2019). Similar results were also obtained in Pan X's study (Pan et al, 2019). Comparing the two studies with ours, our enrollment was significantly smaller, mainly because our research time span was from 2010 to 2013.The main reason for choosing this time range is that the HER-2 factor was not available prior to 2010 in the SEER database.…”

Section: Discussionsupporting

confidence: 79%

Radiotherapy after mastectomy has significant survival benefits for inflammatory breast cancer: a SEER population-based retrospective study

Zhang

Yang

et al. 2020

PeerJ

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Objectives The survival benefit of postmastectomy radiotherapy (PMRT) has not been fully proven in inflammatory breast cancer (IBC). Thus, in the present research, we aimed at elucidating the effects of PMRT on the survival of IBC patients. Methods Eligible patients were collected from the Surveillance, Epidemiology, and End Results (SEER) dataset between 2010 and 2013. The Kaplan-Meier method along with the log-rank test was utilized for the comparison of both the overall survival (OS) andthe cancer-specific survival (CSS) in patients undergoing PMRT or not. Additionally, multivariate survival analysis of CSS and OS were performed using the Cox proportional hazard model. Results In total, 293 eligible cases were identified, with the median follow-up time of 27 months (range: 5–59 months). After propensity score matching (PSM), 188 patients (94 for each) were classified intothe No-PMRT and the PMRT group. Consequently, significantly higher OS rates were detected in the PMRT group compared with the No-PMRT group prior to PSM (P = 0.034), and significantly higher CSS (P = 0.013) and OS (P = 0.0063) rates were observed following PSM. Furthermore, multivariate analysis revealed thatPMRT [CSS (HR: 0.519, 95% CI [0.287–0.939], P = 0.030); OS (HR: 0.480, 95% CI [0.269–0.859], P = 0.013)], as well as Her2+/HR+ subtype, was independent favorable prognostic factors.Besides, black ethnicity, AJCC stage IV and triple-negative subtype were independent unfavorable prognostic factors. Further subgroup analysis revealed that most of the study population could benefit from PMRT, no matter OS or CSS. Conclusions Our findings support that PMRT could improve the survival of IBC patients.

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Section: Discussionsupporting

confidence: 79%

Radiotherapy after mastectomy has significant survival benefits for inflammatory breast cancer: a SEER population-based retrospective study

Zhang

Yang

et al. 2020

PeerJ

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“…The national cancer institute's SEER database contains the most authoritative domestic data on cancer incidence and survival (https://seer.cancer.gov/), which covers about 34.6 percent of the United States population [19]. A large population of women with NSCC was retrieved from additional treatment eld of SEER 18 Regs Custom Data, Nov2018 Sub via SEERStat software (v8.3.6).…”

Section: Cases Sources and Study Cohortmentioning

confidence: 99%

“…The C-index and the area under the receiver operating characteristic curve(AUC)are often used to assess discrimination in clinical models and its high value indicates high accuracy in predicting prognosis [21], whose value between 0.70 and 0.90 indicate that the model has good resolving ability. The calibration plot is often applied to evaluate performance of clinical prediction models, and an outstanding accurate model would present a plot on which predictions would coincide with the 45°d iagonal line [19]. DCA is a model for evaluating clinical utility, and the applied value increases as the curve of the nomogram moves away from the two lines representing extreme cases [22].…”

Section: Construction and Validation Of The Modelmentioning

confidence: 99%

Nomogram for predicting the overall survival of cervical cancer patients with nonsurgical treatment

Song

et al. 2020

Preprint

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Background: Surgery is an important treatment for cervical cancer, but some patients choose not to operate on the primary site. The purpose of this study was to establish nomogram for predicting overall survival (OS) in nonsurgical cervical cancer on the primary site(NSCC) patients by using cases in the public database.Methods: All patients diagnosed between 2004 and 2015 were randomly divided into training (n=4283) or validation (n=1832) cohort. Cox regression analysis was used on the training cohort to select independent prognostic factors to construct nomogram for predicting 3- and 5-year OS. In two cohorts, receiver operating characteristic curve (ROC), Harrell’s concordance index (C-index), calibration curves and decision curve analysis (DCA) were used to evaluate the accuracy and the reliability of the model. We made a risk stratification system based on the model and performed Kaplan-Meier survival analysis on the risk level.Results: In the training set, ten clinicopathological factors were significantly correlated with survival outcomes and were included in the nomogram. In the training cohort and validation cohort, the C-index, ROC and calibration plots exhibited an excellent consistency between actual OS and model predictions. DCA indicated great clinical benefit. Compared with FIGO staging, nomogram's evaluation effect is superior.Conclusions: Age, histological type, grade, tumor size, extension, lymph node involvement, distant metastasis, lymph node removed, chemotherapy and radiotherapy were independent prognostic factors for OS in NSCC patients. The model showed more satisfactory accuracy and clinical practicability than FIGO staging system, and may provide integration and improvement for therapeutic decisions.

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“…Nomogram, as a simple graphical visualization of statistical model, is capable of providing individual patient with accurate survival information [17], and it has been proved to be favorable for a range of cancer types [18][19][20][21][22]. Such a prognostic tool has the potential to become an alternative and even a novel standard in cancer prognosis evaluation.…”

Section: Introductionmentioning

confidence: 99%

Prognostic nomogram to predict overall survival for patients with perihilar cholangiocarcinoma: A population-based study of SEER database

Wang

Gong

Zhang

et al. 2020

Preprint

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Abstract Background Perihilar cholangiocarcinoma (pCCA) is a highly aggressive malignancy with poor prognosis. Accurate prediction is of great significance for patients’ survival outcome. The present study aimed to propose a prognostic nomogram for predicting the overall survival (OS) for patients with pCCA. Methods We conducted a retrospective analysis in a total of 940 patients enrolled from the Surveillance, Epidemiology, and End Results (SEER) program and developed a nomogram based on the prognostic factors identified from the cox regression analysis. Concordance index (C-index), risk group stratification and calibration curves were adopted to test the discrimination and calibration ability of the nomogram with bootstrap method. Decision curves were also plotted to evaluate net benefits in clinical use against TNM staging system. Results On the basis of multivariate analysis, five independent prognostic factors including age, summary stage, surgery, chemotherapy, together with radiation were selected and entered into the nomogram model. The C-index of the model was significantly higher than TNM system in the training set (0.703 vs 0.572, P<0.001), which was also proved in the validation set (0.718 vs 0.588, p<0.001). The calibration curves for 1-, 2-, and 3-year OS probabilities exhibited good agreements between the nomogram-predicted and the actual observation. Decision curves displayed that the nomogram obtained more net benefits than TNM staging system in clinical context. The OS curves of two distinct risk groups stratified by nomogram-predicted survival outcome illustrated statistical difference. Conclusions We established and validated an easy-to-use prognostic nomogram, which can provide more accurate individualized prediction and assistance in decision making for pCCA patients.

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Nomogram for predicting the overall survival of patients with inflammatory breast cancer: A SEER-based study

Cited by 58 publications

References 18 publications

Radiotherapy after mastectomy has significant survival benefits for inflammatory breast cancer: a SEER population-based retrospective study

Radiotherapy after mastectomy has significant survival benefits for inflammatory breast cancer: a SEER population-based retrospective study

Nomogram for predicting the overall survival of cervical cancer patients with nonsurgical treatment

Prognostic nomogram to predict overall survival for patients with perihilar cholangiocarcinoma: A population-based study of SEER database

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