1. HISTOLOGY-SPECIFIC NOMOGRAM FOR PATIENTS AFFECTED BY PRIMARY RSTS
Connective Tissue Oncology Society
15th Annual Meeting
Miami, November 5-7th 2009
HISTOLOGY-SPECIFIC NOMOGRAM FOR PATIENTS AFFECTED BY PRIMARY RSTS
Alessandro Gronchi

2. Prognostication a duty for the clinician for taking decision on
Complementary treatments
Post-operative surveillance
for informing the patient

3. Background

4. 288 pts

5. 122 pts

6. 268 pts

7. 268 pts

8. Methods

9. 5641 pts, collected from 1982 to 2009
Institutional STS DB

10. INT 1985 - 2007 Localized STS 3085 Extremity 2043 Retroperitoneum 396
Trunk wall
Head & Neck
Visceral
Other
We selected the localized ones, located in the extremities

11. Local recurrence at presentation Pediatric histologies (pPNET…)
We excluded…
We excluded DFSP and patients presenting to our center having been operated elewhere and having already developed a local recurrence
Local recurrence at presentation
Pediatric histologies (pPNET…)

12. Parameters investigated
Age
Size
Histotype
Liposarcoma
Leiomiosarcoma
MPNST
SFT
Other
Grade
Completeness of surgical resection (Y/N)
Gronchi et al Cancer 2004; 100:
Gronchi et al J Clin Oncol 2009; 27(1): 24-30

13. Statistical methods End point was OS at 5 and 10 yrs.
Piecewise Regression Model (instead of the usual Cox Model).
Age and size were modelled as continuous variables.
Model performance evaluated through discriminating ability and calibration assessments.

14. Results

15. 198 patients Gender Median age 55 (17-80) Median size 16 (4-75)
Male 99
Female 93
Median age (17-80)
Median size (4-75)
Completeness of resection (y/n) 178/14
GIII GI
GII

16. Survival at 5 and 10 years (+ 95% CI)

17. β SE HR
95% CI
Age* 55 vs 43 years 66 vs 55 years
0.02
0.010
(0.99, 1.58) (0.99, 1.52)
Tumour Size Linear Non linear 20 vs 10 cm 30 vs 20 cm
(1.08, 3.11) (0.95, 1.04)
Histological Subtype Leiomyiosarcoma vs Liposarcoma SFT vs Liposarcoma MPNST vs Liposarcoma Other vs Liposarcoma
(0.30, 1.30) (0.02, 1.24) (0.32, 1.99) (0.71, 3.49)
Grading II vs I III vs I
(1.54, 7.14) (3.70, 16.2)
Surgical Margins Macro (R2) vs Micro (R0/R1)
1.43
0.364
4.18
(2.05, 8.54)

18. …liposarcoma rarely get cured…

19. Log-Relative hazard of death for all causes according to tumour size from the piecewise regression model.

20. …our nomogram…

21. Model performance
Predictive performance: adjusted C Index=0.73 (satisfactory accuracy)
Calibration plots: predicted and observed survival probabilities in good agreement.

22. We do have now different tools… Which one should we choose ?

23. INT - Milan
MDACC - Houston
MSKCC - NY
MSKCC - NY

24. 10 yr OS 5 yr OS Liposarcoma 60 yr 25 cm GI 75% 85% 85% 80%
GII 40% _ _ 40%
GIII 10% 55% 46% 10%
GI 65% _ 63% 60%
GII 15% _ _ 15%
GIII 0% _ 27% 0%

25. 10 yr OS 5 yr OS Leiomyosarcoma 60 yr 25 cm GI 65% _ 52% _
GII 35% _ _ _
GIII 0% _ 16% _
GI 80% _ 80% _
GII 50% 45% _ _
GIII 15% _ 33% _

26. 10 yr OS 5 yr OS MPNST 60 yr 25 cm GI 65% _ 28% _ GII 20% _ _ _
GIII 0% _ 3% _
GI 80% _ 64% _
GII 35% 45% _ _
GIII 0% _ 12% _

27. 10 yr OS 5 yr OS SFT 60 yr 25 cm GI 90% _ 49% _ GI 95% _ 78% _
GII _ _ _ _
GIII 45% _ 13% _
GI 95% _ 78% _
GII _ 45% _ _
GIII 68% _ 30% _

28. Conclusions

29. Different nomograms for RSTS are available
They seem to be quite consistent in the prediction of liposarcoma’s outcome (the commonest histology).
Wy tried to improve the available nomograms by:
using size as a continuous variable (and age…)
introducing the histological subtype more frequently found at this site
complementing histological subtype by histological grade of aggressiveness (a 3-tier grade according to FNCLCC)

30. …next step…

31. Cross-check comparisons
INT - Milan
MDACC - Houston

32. Call for somebody else in the game for external validation
MDACC - Houston
INT - Milan

33. Combine series to come out with a possibly better tool