Nomograms to predict the long‐time prognosis in patients with alpha‐fetoprotein negative hepatocellular carcinoma following radical resection

Huang, Jian; Liu, Fu‐Chen; Li, Li; Zhou, Weiping; Jiang, Bei‐Ge; Pan, Ze‐Ya

doi:10.1002/cam4.2944

Cited by 23 publications

(27 citation statements)

References 44 publications

(50 reference statements)

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“…Additionally, C-index and calibration curves were derived in the validation set. Decision curve analysis was employed to examine the clinical net bene t of a predictive model by using rmda package in R software 21 . Finally, we compared the performance of the nomograms with AJCC 8th edition TNM staging system by using the c-index and decision curve analysis methods.…”

Section: Discussionmentioning

confidence: 99%

Nomograms to Predict the Prognosis in Locally Advanced Oral Squamous Cell Carcinoma After Curative Resection

Nie

Zhao

Shang³

et al. 2021

Preprint

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Background: Oral squamous cell carcinoma (OSCC), the dominant histologic type of oral cancer. Locally advanced OSCC remains a major therapeutic challenge. Our study aimed to develop and validate nomograms predicting survival prognosis in patients with locally advanced oral squamous cell carcinoma (OSCC) after curative resection. Methods: A total of 269 consecutive patients with primary OSCC who received curative resection between September 2007 and March 2020 were retrospectively enrolled in our study. Patients were randomly assigned to the training cohort (n=201) or the validation cohort (n=68). Multivariate Cox regression analyses were conducted to determine independent prognostic factors for overall survival (OS) and cancer specific survival (CSS) in the training set, which were used for the construction of nomogram models estimating 3-, and 5-year OS and CSS. We also evaluated the nomograms using concordance indices (c-index), calibration curves, and decision curve analyses (DCA), and compared those with the AJCC 8th staging system. The results were externally validated in the validation cohort.Results: Age, Kaplan-Feinstein (KFI) index, pT, the number of positive nodes and systemic inflammatory index (SII) were significant prognostic predictors for OS and CSS. The OS nomogram had c-index values of 0.712 in the training set and 0.697 in the validation set, while the CSS nomograms had c-index values of 0.709 in the training set and 0.675 in the validation set. These data were superior to those of AJCC 8th staging system, suggesting high discriminative ability of the nomograms. Calibration curves exhibited good agreement between observed and predicted survival. DCA curves indicated the nomograms were with potential clinical usefulness. These results were validated in the validation set.Conclusions: The novel nomograms incorporating clinically available characteristics for OS and CSS prediction were developed in the locally advanced OSCC patients after curative surgery. Validation revealed good discrimination and calibration, indicating the clinical utility of the nomograms in the individualized prognosis prediction of locally advanced OSCC after curative surgery.

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Section: Discussionmentioning

confidence: 99%

Nomograms to Predict the Prognosis in Locally Advanced Oral Squamous Cell Carcinoma After Curative Resection

Nie

Zhao

Shang³

et al. 2021

Preprint

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show abstract

“…Additionally, c-index values and calibration curves were derived in the validation set. Decision curve analysis (DCA) was employed to examine the clinical net benefit of a predictive model by the rmda package in R software [ 21 ]. Finally, we compared the performance of the nomograms with AJCC 8th edition TNM staging system by using the c-index values and DCA methods.…”

Section: Methodsmentioning

confidence: 99%

Nomograms to predict the prognosis in locally advanced oral squamous cell carcinoma after curative resection

Nie

Zhao

Shang³

et al. 2021

BMC Cancer

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Background Oral squamous cell carcinoma (OSCC) is the dominant histologic type of oral cancer. Locally advanced OSCC remains a major therapeutic challenge. Our study aimed to develop and validate nomograms predicting survival prognosis in patients with locally advanced oral squamous cell carcinoma (OSCC) after curative resection. Methods A total of 269 consecutive patients with primary OSCC who received curative resection between September 2007 and March 2020 were retrospectively enrolled in our study. Patients were randomly assigned to the training cohort (n = 201) or the validation cohort (n = 68). Multivariate Cox regression analyses were conducted to determine independent prognostic factors for overall survival (OS) and cancer specific survival (CSS) in the training set, which were used to develop nomogram models estimating 3-, and 5-year OS and CSS. We also evaluated the nomograms using concordance indices (c-index), calibration curves, and decision curve analyses (DCA), and compared those with the AJCC 8th staging system. The results were externally validated in the validation cohort. Results Age, Kaplan-Feinstein (KFI) index, pT, the number of positive nodes and systemic inflammatory index (SII) were significant prognostic predictors for OS and CSS. The OS nomogram had c-index values of 0.712 in the training set and 0.697 in the validation set, while the CSS nomogram exhibited c-index values of 0.709 in the training set and 0.675 in the validation set. These data were superior to those of AJCC 8th staging system, suggesting high discriminative ability of the nomograms. Calibration curves exhibited good agreement between observed and predicted survival. DCA curves indicated the nomograms were with potential clinical usefulness. These results were validated in the validation set. Conclusions The novel nomograms incorporating clinically available characteristics for OS and CSS prediction were developed in the locally advanced OSCC patients after curative surgery. Validation revealed good discrimination and calibration, indicating the clinical utility of the nomograms in the individualized prognosis prediction of locally advanced OSCC after curative surgery.

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“… 20 The threshold level of HBV-DNA, microvascular invasion (MVI) and satellite lesions were considered as we previously described. 21 To mathematically derive APRI, we used the following formula: [AST (IU/L) ÷ highest normal level] ÷ PLT (×10 9 /L). 22 …”

Section: Methodsmentioning

confidence: 99%

“…The interval between the surgical operation date to the final date of follow-up or death was used to measure overall survival (OS), while the duration from the date of surgery to the initial diagnosed recurrence was used to determine recurrence-free survival (RFS). 21 March 2016 was the last date of follow-up for all patients.…”

Section: Methodsmentioning

confidence: 99%

Prediction of Patient Survival Following Hepatic Resection in Early-Stage Hepatocellular Carcinoma with Indexed Ratios of Aspartate Aminotransferase to Platelets: A Retrospective Cohort Study

Huang¹,

Yang²,

Xia³

et al. 2021

CMAR

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Purpose To predict patient survival in early-stage hepatocellular carcinoma (HCC) following hepatic resection. We evaluated the prognostic potential of the aspartate aminotransferase to platelet ratio index (APRI) in order to use it to model a nomogram. Patients and Methods We randomized 901 early-stage HCC patients treated with hepatic resection at our center into training and validation cohorts that were followed from January 2009 to December 2012. X-tile software was used to establish the APRI cut-off threshold in the training cohort. The validation cohort was subsequently assessed to determine threshold value accuracy. Data generated from the multivariate analysis in the training cohort were used to design a prognostic nomogram. Decision curve analyses (DCA), concordance index values (C-index) and calibration curves were used to determine the performance of the nomogram. Results X-tile software revealed that the optimal APRI cut-off threshold in the training cohort that distinguished between patients with different prognoses was 0.9. We, therefore, validated its prognostic value. Multivariate analyses showed that poor overall survival was associated with APRI above 0.9, blood loss of more than 400 mL, liver cirrhosis, multiple tumors, tumor size greater than 5 cm, microvascular invasion and satellite lesions. When the independent risk factors were integrated into the prognostic nomogram, it performed well with accurate predictions. Indeed, the performance was better than comparative prognosticators ( P <0.05 for all) with 0.752 as the C-index (95% CI: 0.706–0.798). These results were verified by the validation cohort. Conclusion APRI was a noninvasive and accurate predictive indicator for patients with early-stage HCC. Following hepatic resection to treat early-stage HCC, individualized patient survival predictions can be aided by the nomogram based on APRI.

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Nomograms to predict the long‐time prognosis in patients with alpha‐fetoprotein negative hepatocellular carcinoma following radical resection

Cited by 23 publications

References 44 publications

Nomograms to Predict the Prognosis in Locally Advanced Oral Squamous Cell Carcinoma After Curative Resection

Nomograms to Predict the Prognosis in Locally Advanced Oral Squamous Cell Carcinoma After Curative Resection

Nomograms to predict the prognosis in locally advanced oral squamous cell carcinoma after curative resection

Prediction of Patient Survival Following Hepatic Resection in Early-Stage Hepatocellular Carcinoma with Indexed Ratios of Aspartate Aminotransferase to Platelets: A Retrospective Cohort Study

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