| Literature DB >> 27931238 |
Franco Di Filippo1, Simona Di Filippo2, Anna Maria Ferrari3, Raffaele Antonetti4, Alessandro Battaglia5, Francesca Becherini6, Laia Bernet7, Renzo Boldorini8, Catherine Bouteille9, Simonetta Buglioni10, Paolo Burelli6, Rafael Cano11, Vincenzo Canzonieri12, Pierluigi Chiodera13, Alfredo Cirilli14, Luigi Coppola15, Stefano Drago15, Luca Di Tommaso16, Privato Fenaroli17, Roberto Franchini18, Andrea Gianatti17, Diana Giannarelli10, Carmela Giardina19, Florence Godey20, Massimo M Grassi21, Giuseppe B Grassi15, Siobhan Laws22, Samuele Massarut12, Giuseppe Naccarato23, Maria Iole Natalicchio24, Sergio Orefice25, Fabrizio Palmieri26, Tiziana Perin12, Manuela Roncella27, Massimo G Roncalli28, Antonio Rulli29, Angelo Sidoni29, Corrado Tinterri28, Maria C Truglia30, Isabella Sperduti10.
Abstract
BACKGROUND: Tumor-positive sentinel lymph node (SLN) biopsy results in a risk of non sentinel node metastases in micro- and macro-metastases ranging from 20 to 50%, respectively. Therefore, most patients underwent unnecessary axillary lymph node dissections. We have previously developed a mathematical model for predicting patient-specific risk of non sentinel node (NSN) metastases based on 2460 patients. The study reports the results of the validation phase where a total of 1945 patients were enrolled, aimed at identifying a tool that gives the possibility to the surgeon to choose intraoperatively whether to perform or not axillary lymph node dissection (ALND).Entities:
Keywords: CK19 mRNA number copies; Nomogram; Non Sentinel Node status; OSNA method
Mesh:
Substances:
Year: 2016 PMID: 27931238 PMCID: PMC5146809 DOI: 10.1186/s13046-016-0460-6
Source DB: PubMed Journal: J Exp Clin Cancer Res ISSN: 0392-9078
Clinicopathological characteristics of patients
| Characteristics | N of patients | Percent |
|---|---|---|
| Histology | ||
| IDL | 1278 | 85.5 |
| ILC | 184 | 12.3 |
| Other | 33 | 2.2 |
| Grading | ||
| G1 | 129 | 8.6 |
| G2 | 827 | 55.4 |
| G3 | 490 | 32.8 |
| Unk | 49 | 3.2 |
| ER | ||
| Pos | 1297 | 86.7 |
| Neg | 147 | 9.8 |
| Unk | 51 | 3.4 |
| PgR | ||
| Pos | 1174 | 78.5 |
| Neg | 268 | 17.9 |
| Unk | 53 | 3.5 |
| HER2 | ||
| Pos | 147 | 9.8 |
| Neg | 927 | 62.0 |
| Unk | 421 | 28.2 |
| Ki67 | ||
| Low | 876 | 58.6 |
| High | 515 | 34.4 |
| Unk | 104 | 7.0 |
| T | ||
| ≤ 12 | 398 | 26.6 |
| ≥ 13–18 | 364 | 24.3 |
| ≥ 19–25 | 400 | 26.8 |
| > 25 | 333 | 22.3 |
| Type | ||
| Multiple | 364 | 24.3 |
| Single | 1131 | 75.7 |
| Molecular subtype | ||
| Luminal A | 452 | 30.2 |
| Luminal B | 628 | 42.0 |
| HER2-like | 50 | 3.3 |
| Triple Negative | 58 | 3.9 |
| Unk | 307 | 20.5 |
Characteristics of non sentinel node and sentinel node
| Number | Percent | |
|---|---|---|
| NSLNs Examined | ||
| Median (range) | 15 (11–52) | |
| N° of positive NSLNs | 610 | 40.8 |
| Median (range) | 2 (1–41) | |
| N° of Copies (Highest copy number) | ||
| ≤ 1500 | 305 | 20.4 |
| > 1500–12,000 | 329 | 22.0 |
| > 12,000–111,000 | 460 | 30.8 |
| > 111,000 | 401 | 26.8 |
Fig. 1ROC curve of of number of CK19 mRNA, T size (quartiles) and the model containing these two variables
Fig. 2The model performs well and correctly at low and in high risk as shown in calibration plot. The linear regression model has a slope of 0.96 (95% C.I. 0.98/1.40) and a constant of -13.8 between predicted and actual probabilities (95%C.I. -22.9/-4.85)
Percentage of FN and FP rates according to value risk categories are reported
| Risk Categories | 11% | 20% | 30% | 45% | 50% | 31% |
|---|---|---|---|---|---|---|
| % False negative (FN) | 1% | 3.5% | 8.2% | 18.4% | 24.4% | 8.9% |
| % False positive FP) | 56.0% | 45.6% | 31.4% | 15.6% | 9.0% | 30.1% |