Optimizing the Sensitivity of a Pelvic Sentinel Node Algorithm Requires a Hybrid Algorithm Combining Indocyanine Green Based Mapping and the Removal of Non-Mapped Nodes at Defined Anatomic Positions
Abstract
:Simple Summary
Abstract
1. Introduction
2. Materials and Methods
3. Results
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Variable n (%) or Median (Range) as Appropriate | Node Negative Cohort (n = 504) | Node Positive Cohort (n = 116) a | p Value b |
---|---|---|---|
Age (years) | 69 (31–95) | 77 (41–88) | <0.01 |
Body mass index (kg/m²) | 28.7 (17.6–66.1) | 27 (16.6–47.5) | <0.01 |
Final histology | |||
Low grade endometrioid adenocarcinoma (grade I-II) | 384 (76.2) | 67 (57.7) | <0.01 |
High grade endometrioid adenocarcinoma (grade III) | 37 (7.3) | 13 (11.2) | 0.23 |
Serous adenocarcinoma | 45 (8.9) | 22 (18.9) | <0.01 |
Clear cell adenocarcinoma | 14 (2.8) | 6 (5.2) | 0.30 |
Carcinosarcoma | 21 (4.2) | 7 (6) | 0.53 |
other | 3 (0.6) | 1 (0.8) | 1.0 |
Stage (FIGO 2009) | |||
IA | 382 (75.8) | - | |
IB | 90 (17.8) | - | |
II | 23 (4.6) | - | |
III A-B | 5 (0.9) | - | |
IIIC1 | - | 89 (76.7) | |
IIIC2 | - | 27 (23.3) | |
IVA-B | 5 (0.9) | 0 | |
Uterine stage (Irrespective of overall surgical stage) | |||
IA | 397 (78.7) | 48 (41.7) | <0.01 |
IB | 107 (21.3) | 67 (58.3) | <0.01 |
II | 31 (6.1) | 21 (17.9) | <0.01 |
Lymph node assessment | |||
SLN biopsy only c | 455 (90.3) | 68 (58.6) | <0.01 |
SLN biopsy only c + PALND | 49 (9.7) | 48 (41.4) | <0.01 |
Upper Paracervical Pathway | |||
---|---|---|---|
External Iliac Area | Obturator Area | Parauterine Lymphovascular Tissue | |
SLN ICG | 45/114 (39.5%) | 84/114 (73.7%) | 15/114 (13.2%) |
SLN ICG isolated | 14/114 (12.3%) | 25/114 (21.9%) | 2/114 (1.7%) |
“SLN anatomy” | |||
10/114 (8.8%) | 14/114 (12.3%) | - | |
10/30 (33.3%) * | 14/41 (34.1%) * | ||
“SLN anatomy” isolated | |||
2/114 (1.7%) | 3/114 (2.6%) | - |
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Bollino, M.; Geppert, B.; Reynisson, P.; Lönnerfors, C.; Persson, J. Optimizing the Sensitivity of a Pelvic Sentinel Node Algorithm Requires a Hybrid Algorithm Combining Indocyanine Green Based Mapping and the Removal of Non-Mapped Nodes at Defined Anatomic Positions. Cancers 2024, 16, 3242. https://doi.org/10.3390/cancers16183242
Bollino M, Geppert B, Reynisson P, Lönnerfors C, Persson J. Optimizing the Sensitivity of a Pelvic Sentinel Node Algorithm Requires a Hybrid Algorithm Combining Indocyanine Green Based Mapping and the Removal of Non-Mapped Nodes at Defined Anatomic Positions. Cancers. 2024; 16(18):3242. https://doi.org/10.3390/cancers16183242
Chicago/Turabian StyleBollino, Michele, Barbara Geppert, Petur Reynisson, Celine Lönnerfors, and Jan Persson. 2024. "Optimizing the Sensitivity of a Pelvic Sentinel Node Algorithm Requires a Hybrid Algorithm Combining Indocyanine Green Based Mapping and the Removal of Non-Mapped Nodes at Defined Anatomic Positions" Cancers 16, no. 18: 3242. https://doi.org/10.3390/cancers16183242
APA StyleBollino, M., Geppert, B., Reynisson, P., Lönnerfors, C., & Persson, J. (2024). Optimizing the Sensitivity of a Pelvic Sentinel Node Algorithm Requires a Hybrid Algorithm Combining Indocyanine Green Based Mapping and the Removal of Non-Mapped Nodes at Defined Anatomic Positions. Cancers, 16(18), 3242. https://doi.org/10.3390/cancers16183242