AIMS: Investigators from the Memorial Sloan Kettering Cancer Centre (MSKCC) have proposed a nomogram for predicting the sentinel node (SN) status in patients with cutaneous melanoma. The negative predictive value (NPV) of this test, which might help identify low-risk patients who might be safely spared SN biopsy (SNB), has not been yet investigated. METHODS: We tested the discrimination (area under the curve [AUC]), the calibration (linear regression) and the NPV of MSKCC nomogram in 543 patients treated at our institution. Different cut-off values were tested to assess the NPV, the reduction of SNB performed and the overall error rate obtained with the MSKCC nomogram. RESULTS: SN was positive in 147 patients (27%). Mean predicted probability was 17.8% (95%CI: 16.8-18.8%). Nomogram discrimination was significant (area under the curve = 0.68; P < 0.0001) and mean predicted probabilities of SN positivity well correlated with the observed risk (R(2) = 0.99). Cut-off values between 4% and 9% led to a NPV, SNB reduction and overall error rates ranging between 100 and 91.2%, 2.2 and 27.2%, and 0 and 2.3%, respectively. CONCLUSION: In our series, the nomogram showed a significant predictive accuracy, although the incidence of SN metastasis was higher than that observed in the MSKCC series (27% vs 16%). Using the nomogram, a NPV greater than 90% could be obtained, which would be associated with a clinically meaningful reduction of the SNB rate and an acceptable error rate. If validated in large prospective series, this tool might be implemented in the clinical setting for SNB patient selection.
AIMS: Investigators from the Memorial Sloan Kettering Cancer Centre (MSKCC) have proposed a nomogram for predicting the sentinel node (SN) status in patients with cutaneous melanoma. The negative predictive value (NPV) of this test, which might help identify low-risk patients who might be safely spared SN biopsy (SNB), has not been yet investigated. METHODS: We tested the discrimination (area under the curve [AUC]), the calibration (linear regression) and the NPV of MSKCC nomogram in 543 patients treated at our institution. Different cut-off values were tested to assess the NPV, the reduction of SNB performed and the overall error rate obtained with the MSKCC nomogram. RESULTS: SN was positive in 147 patients (27%). Mean predicted probability was 17.8% (95%CI: 16.8-18.8%). Nomogram discrimination was significant (area under the curve = 0.68; P < 0.0001) and mean predicted probabilities of SN positivity well correlated with the observed risk (R(2) = 0.99). Cut-off values between 4% and 9% led to a NPV, SNB reduction and overall error rates ranging between 100 and 91.2%, 2.2 and 27.2%, and 0 and 2.3%, respectively. CONCLUSION: In our series, the nomogram showed a significant predictive accuracy, although the incidence of SN metastasis was higher than that observed in the MSKCC series (27% vs 16%). Using the nomogram, a NPV greater than 90% could be obtained, which would be associated with a clinically meaningful reduction of the SNB rate and an acceptable error rate. If validated in large prospective series, this tool might be implemented in the clinical setting for SNB patient selection.
Authors: Serigne N Lo; Jiawen Ma; Richard A Scolyer; Lauren E Haydu; Jonathan R Stretch; Robyn P M Saw; Omgo E Nieweg; Kerwin F Shannon; Andrew J Spillane; Sydney Ch'ng; Graham J Mann; Jeffrey E Gershenwald; John F Thompson; Alexander H R Varey Journal: J Clin Oncol Date: 2020-06-12 Impact factor: 44.544
Authors: C A Castaneda; C Torres-Cabala; M Castillo; V Villegas; S Casavilca; L Cano; J Sanchez; J Dunstan; G Calderon; M De La Cruz; J M Cotrina; H L Gomez; R Galvez; J Abugattas Journal: Clin Transl Oncol Date: 2017-06-02 Impact factor: 3.405
Authors: Alyss V Robinson; Claire Keeble; Michelle C I Lo; Owen Thornton; Howard Peach; Marc D S Moncrieff; Donald J Dewar; Ryckie G Wade Journal: Cancer Immunol Immunother Date: 2020-01-23 Impact factor: 6.968