Outcome of patients with renal cell carcinoma nodal metastases (NM) is substantially worse than that of patients with localized disease. This justifies more thorough staging and possibly more aggressive treatment in those at risk of or with established NM. We developed and externally validated a nomogram capable of highly accurately predicting renal cell carcinoma NM in patients without radiographic evidence of distant metastases. Age, symptom classification, tumour size and the pathological nodal stage were available for 4,658 individuals. The data of 2,522 (54.1%) individuals from 7 centers were used to develop a multivariable logistic regression model-based nomogram predicting the individual probability of NM. The remaining data from 2,136 (45.9%) patients from 5 institutions were used for external validation. In the development cohort, 107/2,522 (4.2%) had lymph node metastases vs. 100/2,136 (4.7%) in the external validation cohort. Symptom classification and tumour size were independent predictors of NM in the development cohort. Age failed to reach independent predictor status, but added to discriminant properties of the model. A nomogram based on age, symptom classification and tumour size was 78.4% accurate in predicting the individual probability of NM in the external validation cohort. Our nomogram can contribute to the identification of patients at low risk of NM. This tool can help to risk adjust the need and the extent of nodal staging in patients without known distant metastases. More thorough staging can hopefully better select those in whom adjuvant treatment is necessary.

Outcome of patients with renal cell carcinoma nodal metastases (NM) is substantially worse than that of patients with localized disease. This justifies more thorough staging and possibly more aggressive treatment in those at risk of or with established NM. We developed and externally validated a nomogram capable of highly accurately predicting renal cell carcinoma NM in patients without radiographic evidence of distant metastases. Age, symptom classification, tumour size and the pathological nodal stage were available for 4,658 individuals. The data of 2,522 (54.1%) individuals from 7 centers were used to develop a multivariable logistic regression model-based nomogram predicting the individual probability of NM. The remaining data from 2,136 (45.9%) patients from 5 institutions were used for external validation. In the development cohort, 107/2,522 (4.2%) had lymph node metastases vs. 100/2,136 (4.7%) in the external validation cohort. Symptom classification and tumour size were independent predictors of NM in the development cohort. Age failed to reach independent predictor status, but added to discriminant properties of the model. A nomogram based on age, symptom classification and tumour size was 78.4% accurate in predicting the individual probability of NM in the external validation cohort. Our nomogram can contribute to the identification of patients at low risk of NM. This tool can help to risk adjust the need and the extent of nodal staging in patients without known distant metastases. More thorough staging can hopefully better select those in whom adjuvant treatment is necessary.

Patients with renal cell carcinoma nodal metastases can be accurately identified: external validation of a new nomogram

Luigi Schips;
2007-01-01

Abstract

Outcome of patients with renal cell carcinoma nodal metastases (NM) is substantially worse than that of patients with localized disease. This justifies more thorough staging and possibly more aggressive treatment in those at risk of or with established NM. We developed and externally validated a nomogram capable of highly accurately predicting renal cell carcinoma NM in patients without radiographic evidence of distant metastases. Age, symptom classification, tumour size and the pathological nodal stage were available for 4,658 individuals. The data of 2,522 (54.1%) individuals from 7 centers were used to develop a multivariable logistic regression model-based nomogram predicting the individual probability of NM. The remaining data from 2,136 (45.9%) patients from 5 institutions were used for external validation. In the development cohort, 107/2,522 (4.2%) had lymph node metastases vs. 100/2,136 (4.7%) in the external validation cohort. Symptom classification and tumour size were independent predictors of NM in the development cohort. Age failed to reach independent predictor status, but added to discriminant properties of the model. A nomogram based on age, symptom classification and tumour size was 78.4% accurate in predicting the individual probability of NM in the external validation cohort. Our nomogram can contribute to the identification of patients at low risk of NM. This tool can help to risk adjust the need and the extent of nodal staging in patients without known distant metastases. More thorough staging can hopefully better select those in whom adjuvant treatment is necessary.
2007
Outcome of patients with renal cell carcinoma nodal metastases (NM) is substantially worse than that of patients with localized disease. This justifies more thorough staging and possibly more aggressive treatment in those at risk of or with established NM. We developed and externally validated a nomogram capable of highly accurately predicting renal cell carcinoma NM in patients without radiographic evidence of distant metastases. Age, symptom classification, tumour size and the pathological nodal stage were available for 4,658 individuals. The data of 2,522 (54.1%) individuals from 7 centers were used to develop a multivariable logistic regression model-based nomogram predicting the individual probability of NM. The remaining data from 2,136 (45.9%) patients from 5 institutions were used for external validation. In the development cohort, 107/2,522 (4.2%) had lymph node metastases vs. 100/2,136 (4.7%) in the external validation cohort. Symptom classification and tumour size were independent predictors of NM in the development cohort. Age failed to reach independent predictor status, but added to discriminant properties of the model. A nomogram based on age, symptom classification and tumour size was 78.4% accurate in predicting the individual probability of NM in the external validation cohort. Our nomogram can contribute to the identification of patients at low risk of NM. This tool can help to risk adjust the need and the extent of nodal staging in patients without known distant metastases. More thorough staging can hopefully better select those in whom adjuvant treatment is necessary.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11564/682723
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