Prognostic group stratification and nomogram for predicting overall survival in patients who received radiotherapy for abdominal lymph node metastasis from hepatocellular carcinoma: a multi-institutional retrospective study (KROG 15-02)

Kim, Youngkyong; Park, Hee Chul; Yoon, Sang Min; Kim, Tae Hyun; Lee, Jieun; Choi, Ji Sun; Yu, Jeong Il; Park, Jin‐Hong; Kim, Jong Hoon; Park, Joong-Won; Seong, Jinsil

doi:10.18632/oncotarget.21775

Cited by 16 publications

(17 citation statements)

References 27 publications

(51 reference statements)

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“…Thus, to develop a nomogram specific for RT is essential. Except for the nomograms from HCC patients treated with fractionated RT for lymph node metastasis [28,29], to our knowledge, our nomogram is the first linked to survival for stage C patients undergoing SBRT for primary liver tumors.…”

Section: Discussionmentioning

confidence: 99%

Development and Validation of a Nomogram for Patients with Nonmetastatic BCLC Stage C Hepatocellular Carcinoma after Stereotactic Body Radiotherapy

et al. 2020

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Background: Stereotactic body radiotherapy (SBRT) is an emerging treatment modality for hepatocellular carcinoma (HCC) with promising outcome. However, appropriate survival prediction models are scarce. This study aimed to develop a simple and clinically useful prognostic nomogram for patients with nondistant metastatic Barcelona Clinic Liver Cancer (BCLC) stage C HCC undergoing SBRT. Methods: The data were based on a prospective multi-institutional registry enrolling 246 patients with nondistant metastatic BCLC stage C HCC treated with SBRT between January 1, 2008 and December 31, 2016. They were randomly divided into two subsets: 164 into the development cohort and 82 into the validation cohort. We identified and included prognostic factors for survival to derive a nomogram in the development cohort. The predictability of the nomogram was evaluated in the validation cohort. The area under the receiver operating characteristic curve (AUROC) and the calibration plot were used to evaluate the performance of the nomogram. Results: The median survival was 13.5 months, with 1-and 2-year overall survival (OS) rates of 55.0 and 32.9%, respectively. Number of tumors, largest tumor size, macrovascular invasion, Child-Turcotte-Pugh class, and biologically effective dose were significantly associated with OS (p < 0.05). These predictors were included to develop a nomogram with an AUROC of 0.77 (0.73-0.87). The prediction model was well

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Section: Discussionmentioning

confidence: 99%

Development and Validation of a Nomogram for Patients with Nonmetastatic BCLC Stage C Hepatocellular Carcinoma after Stereotactic Body Radiotherapy

et al. 2020

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“…Compared with the current prognostic prediction system like AJCC staging system, the nomogram showed advantages in many studies on different cancers [16,17]. They can also establish individualized risk stratification and help clinicians identify suitable patients for optimal managements, and good results had been obtained in many studies of different tumor types [18][19][20].…”

Section: Discussionmentioning

confidence: 99%

Development and validation of a preoperative nomogram for predicting survival of patients with locally advanced prostate cancer after radical prostatectomy

et al. 2020

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Background: For selected locally advanced prostate cancer (PCa) patients, radical prostatectomy (RP) is one of the first-line treatments. We aimed to develop a preoperative nomogram to identify what kinds of patients can get the most survival benefits after RP. Methods: We conducted analyses with data from the Surveillance, Epidemiology, and End Results (SEER) database. Covariates used for analyses included age at diagnosis, marital status, race, American Joint Committee on Cancer (AJCC) 7th TNM stage, Prostate specific antigen, Gleason biopsy score (GS), percent of positive cores. We estimated the cumulative incidence function for cause-specific death. The Fine and Gray's proportional subdistribution hazard approach was used to perform multivariable competing risk analyses and reveal prognostic factors. A nomogram was built by these factors (including GS, percent of positive cores and N stage) and validated by concordance index and calibration curves. Risk stratification was established based on the nomogram. Results: We studied 14,185 patients. N stage, GS, and percent of positive cores were the independent prognostic factors used to construct the nomogram. For validating, in the training cohort, the C-index was 0.779 (95% CI 0.736-0.822), and in the validation cohort, the C-index was 0.773 (95% CI 0.710-0.836). Calibration curves showed that the predicted survival and actual survival were very close. The nomogram performed better over the AJCC staging system (C-index 0.779 versus 0.764 for training cohort, and 0.773 versus 0.744 for validation cohort). The new stratification of risk groups based on the nomogram also showed better discrimination than the AJCC staging system. Conclusions: The preoperative nomogram can provide favorable prognosis stratification ability to help clinicians identify patients who are suitable for surgery.

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“…They can also establish individualized risk stratification and help clinicians identify suitable patients for optimal managements, and good results had been obtained in many studies of different tumor types. [18][19][20].…”

Section: Discussionmentioning

confidence: 99%

Development and Validation of a Preoperative Nomogram for Predicting Survival of Patients with Locally Advanced Prostate Cancer after Radical Prostatectomy

Zhou

Ning

Jin

et al. 2020

Preprint

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Background: For selected locally advanced prostate cancer (PCa) patients, radical prostatectomy (RP) is one of the first-line treatments. We aimed to develop a preoperative nomogram to identify what kinds of patients can get the most survival benefits after RP. Methods: We conducted analyses with data from the Surveillance, Epidemiology, and End Results (SEER) database. Covariates used for analyses included age at diagnosis, marital status, race, American Joint Committee on Cancer (AJCC) 7th TNM stage, Prostate specific antigen, Gleason biopsy score (GS), percent of positive cores. We estimated the cumulative incidence function for cause-specific death. The Fine and Gray’s proportional subdistribution hazard approach was used to perform multivariable competing risk analyses and reveal prognostic factors. A nomogram was built by these factors (including GS, percent of positive cores and N stage) and validated by concordance index and calibration curves . Risk stratification was established based on the nomogram. Results: We studied 14185 patients. N stage, GS, and percent of positive cores were the independent prognostic factors used to construct the nomogram. For validating, in the training cohort, the C-index was 0.779 (95% CI 0.736–0.822), and in the validation cohort, the C-index was 0.773 (95% CI 0.710–0.836). Calibration curves showed that the predicted survival and actual survival were very close. The nomogram performed better over the AJCC staging system (C-index 0.779 versus 0.764 for training cohort, and 0.773 versus 0.744 for validation cohort). The new stratification of risk groups based on the nomogram also showed better discrimination than the AJCC staging system. Conclusions: The preoperative nomogram can provide favorable prognosis stratification ability to help clinicians identify patients who are suitable for surgery.

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Prognostic group stratification and nomogram for predicting overall survival in patients who received radiotherapy for abdominal lymph node metastasis from hepatocellular carcinoma: a multi-institutional retrospective study (KROG 15-02)

Cited by 16 publications

References 27 publications

Development and Validation of a Nomogram for Patients with Nonmetastatic BCLC Stage C Hepatocellular Carcinoma after Stereotactic Body Radiotherapy

Development and Validation of a Nomogram for Patients with Nonmetastatic BCLC Stage C Hepatocellular Carcinoma after Stereotactic Body Radiotherapy

Development and validation of a preoperative nomogram for predicting survival of patients with locally advanced prostate cancer after radical prostatectomy

Development and Validation of a Preoperative Nomogram for Predicting Survival of Patients with Locally Advanced Prostate Cancer after Radical Prostatectomy

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