Nomogram for predicting central node metastasis in papillary thyroid carcinoma

Kim, Seo Ki; Chai, Young Jun; Park, Inhye; Woo, Jung-Woo; Lee, Jun Ho; Lee, Kyu Eun; Choe, Jun-Ho; Kim, Jung-Han; Kim, Jee Soo

doi:10.1002/jso.24512

Cited by 45 publications

(67 citation statements)

References 48 publications

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“…Moreover, in the previous studies for constructing nomograms, the size of the validation cohort was approximately one-third to half of training cohort. [10][11][12][13][14][15] Therefore, we randomly assigned 70% of the enrolled eligible patients to the training cohort (n = 692) and 30% of the enrolled eligible patients to the validation cohort (n = 296). The training cohort was used to establish the predictive model and to develop the nomogram.…”

Section: Discussionmentioning

confidence: 99%

“…To make the best use of our data for constructing the predictive model, we managed to make a higher ratio of training cohort, and we also kept a considerable number of patients for validation of our model. Moreover, in the previous studies for constructing nomograms, the size of the validation cohort was approximately one‐third to half of training cohort 10–15 . Therefore, we randomly assigned 70% of the enrolled eligible patients to the training cohort (n = 692) and 30% of the enrolled eligible patients to the validation cohort (n = 296).…”

Section: Methodsmentioning

confidence: 99%

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Development and validation of a nomogram for predicting cancer‐specific survival of surgical resected stage I‐II adenosquamous carcinoma of the lung

Wang

Yang

et al. 2020

Journal of Surgical Oncology

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Objectives Primary lung adenosquamous carcinoma (ASC) is a rare cancer subtype and has a poor prognosis. The prognostic factors for resected early‐stage ASC remain unclear. We aimed to develop a nomogram to predict lung cancer‐specific survival (LCSS) of patients undergoing surgical resection for stage I‐II ASC. Methods Data of patients undergoing resection for stage I‐II ASC and diagnosed between 2004‐2015 were identified from the Surveillance, Epidemiology, and End Results (SEER) database. All the included patients were randomized at a 7:3 ratio into a training and a validation cohort. We selected and integrated significant prognostic factors based on competing for risk regression to build a nomogram. The performance of the nomogram was evaluated using Harrell's concordance index (C‐index) and calibration plots. Results A total of 988 patients (530 men and 458 women) undergoing surgical resection for stage I‐II ASC were identified and randomized into a training (692, 70%) cohort and a validation cohort (296, 30%). The baseline characteristics were similar in the training and validation cohorts. Age, T stage, N stage, and the number of examined lymph nodes were independent prognostic factors for LCSS and were used in the nomogram. The calibration plots showed that the 3‐ and 5‐year LCSS probabilities were consistent between the nomogram prediction and the actual observation. The C‐index of the nomogram was 0.671 (95%CI: 0.618‐0.724) and 0.635 (95%CI: 0.557‐0.713) in the training cohort and validation cohort, respectively. We developed a risk classification system based on the nomogram to stratify patients into high‐ and low‐risk of cancer‐specific death groups. Patients with a similar risk shared similar prognostic prediction regardless of the stage category and patients with the same risk shared similar prognoses despite the different stage category. Conclusions We developed a competing risk nomogram to reliably predict cancer‐specific survival of patients undergoing surgical resection for stage I‐II ASC. The nomogram might be a useful tool to identify patients undergoing surgical resection for ASC who could be suitable candidates for adjuvant chemotherapy.

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Development and validation of a nomogram for predicting cancer‐specific survival of surgical resected stage I‐II adenosquamous carcinoma of the lung

Wang

Yang

et al. 2020

Journal of Surgical Oncology

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“…Nomograms have been used in most cancer types in recent years [25][26][27][28][29][30][31][32] , including for ccRCC [33][34][35] . However, there has been a lack of overall evaluations of the developed nomograms, or the variables used for prediction have not been readily available.…”

Section: Discussionmentioning

confidence: 99%

A practical nomogram for predicting cancer-specific survival in patients with clear-cell renal cell carcinoma

Wen

Wang

Bai

et al. 2020

Preprint

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Background: It has limitations in predicting patient cancer-specific survival to use of the traditional American Joint Committee on Cancer (AJCC) staging system alone. Objectives: We aimed to establish and evaluate a comprehensive prognostic nomogram and compare its prognostic value with the AJCC-7th staging system in adults diagnosed with ccRCC.Methods: We used the SEER database to identify 24477 cases of ccRCC between 2010 and 2015. In the development cohort, we used multivariate Cox proportional-hazards analyses to select significant variables, and used R software to establish a nomogram for predicting the 3-year and 5-year cancer-specific survival rates of ccRCC patients. In the development and validation cohorts, we compared our cancer-specific survival model with the AJCC-7th prognosis model to evaluate the performance of the nomogram by calculating the concordance index (C-index), Youden Index, area under the receiver operating characteristic curve (AUC), net reclassification improvement (NRI), and integrated discrimination improvement (IDI), and performing calibration plotting and decision curve analyses (DCAs). Results: Eleven identified independent prognostic factors were used to establish the nomogram. Age at diagnosis, being unmarried, higher grades, larger tumor size, higher AJCC-7th stage, lymph node metastases, bone metastases, liver metastases, lung metastases, radiotherapy, and no surgery were risk factors for the cancer-specific survival of ccRCC. The C-index, Youden Index, AUC, NRI, IDI, and calibration plots demonstrated the good performance of the nomogram compared to the AJCC-7th staging system. Moreover, the 3-year and 5-year DCA curves showed that the nomogram yielded net benefits that were greater than the traditional AJCC-7th staging system. Conclusion: This study is the first to indicate that married status is an important prognostic parameter in ccRCC. Our results also demonstrate that the developed nomogram can predict cancer-specific survival more accurately than the AJCC-7th staging system alone. The prognostic factors were easily obtained.

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“…Nomograms have been used in most cancer types in recent years [24][25][26][27][28][29][30][31] , including for ccRCC [32][33][34] .…”

Section: Discussionmentioning

confidence: 99%

A practical nomogram for predicting cancer-specific survival in patients with clear-cell renal cell carcinoma

Wen¹,

Wang²,

Bai³

et al. 2020

Preprint

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Background: It has limitations in predicting patient survival to use of the traditional American Joint Committee on Cancer (AJCC) staging system alone.Objectives: We aimed to establish and evaluate a comprehensive prognostic nomogram and compare its prognostic value with the AJCC staging system in adults diagnosed with ccRCC.Patients and Methods: We used the SEER database to identify 24477 cases of ccRCC between 2010 and 2015. The patients were randomly divided into two groups. In the development cohort, we used multivariate Cox proportional-hazards analyses to select significant variables, and used R software to establish a nomogram for predicting the 3-year and 5-year survival rates of ccRCC patients. In the development and validation cohorts, we compared our survival model with the AJCC prognosis model to evaluate the performance of the nomogram by calculating the concordance index (C-index), area under the receiver operating characteristic curve (AUC), net reclassification improvement (NRI), and integrated discrimination improvement (IDI), and performing calibration plotting and decision curve analyses (DCAs). Results: Eleven identified independent prognostic factors were used to establish the nomogram. Age at diagnosis, being unmarried, higher grades, larger tumor size, higher AJCC stage, lymph node metastases, bone metastases, liver metastases, lung metastases, radiotherapy, and no surgery were risk factors for the survival of ccRCC. The C-index, AUC, NRI, IDI, and calibration plots demonstrated the good performance of the nomogram compared to the AJCC staging system. Moreover, the 3-year and 5-year DCA curves showed that the nomogram yielded net benefits that were greater than the traditional AJCC staging system.Conclusion: This study is the first to indicate that married status is an important prognostic parameter in ccRCC. Our results also demonstrate that the developed nomogram can predict survival more accurately than the AJCC staging system alone. The prognostic factors were easily obtained.

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Nomogram for predicting central node metastasis in papillary thyroid carcinoma

Cited by 45 publications

References 48 publications

Development and validation of a nomogram for predicting cancer‐specific survival of surgical resected stage I‐II adenosquamous carcinoma of the lung

Development and validation of a nomogram for predicting cancer‐specific survival of surgical resected stage I‐II adenosquamous carcinoma of the lung

A practical nomogram for predicting cancer-specific survival in patients with clear-cell renal cell carcinoma

A practical nomogram for predicting cancer-specific survival in patients with clear-cell renal cell carcinoma

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