Connective Tissue Oncology Society

15th Annual MeetingMiami, November 5-7th 2009

HISTOLOGY-SPECIFIC NOMOGRAM FOR PATIENTS AFFECTED BY

PRIMARY RSTS

Alessandro Gronchialessandro.gronchi@istitutotumori.mi.it

Prognostication

• a duty for the clinician

– for taking decision on • Complementary treatments• Post-operative surveillance

– for informing the patient

Background

288 pts

122 pts

268 pts

268 pts

Methods

5641 pts, collected from 1982 to 2009

Institutional STS DB

INT 1985 - 2007

• Localized STS 3085

• Extremity 2043

• Retroperitoneum 396

• Trunk wall 273

• Head & Neck 76

• Visceral 112

• Other 185

We excluded…

Local recurrence at presentation

Pediatric histologies (pPNET…)

Parameters investigated

• Age

• Size

• Histotype– Liposarcoma– Leiomiosarcoma– MPNST– SFT– Other

• Grade

• Completeness of surgical resection (Y/N)Gronchi et al Cancer 2004; 100: 2448-2455

Gronchi et al J Clin Oncol 2009; 27(1): 24-30

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.

Results

198 patients• Gender

– Male 99– Female 93

• Median age 55 (17-80)

• Median size 16 (4-75)

• Completeness of resection (y/n) 178/14

GIII

GII

GI

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

β SE HR 95% CI

Age*

55 vs 43 years66 vs 55 years

0.02 0.0101.251.23

(0.99, 1.58)(0.99, 1.52)

Tumour SizeLinearNon linear20 vs 10 cm30 vs 20 cm

0.09-0.12

0.0410.053

1.781.02

(1.08, 3.11)(0.95, 1.04)

Histological SubtypeLeiomyiosarcoma vs LiposarcomaSFT vs LiposarcomaMPNST vs LiposarcomaOther vs Liposarcoma

-0.46-1.79-0.220.45

0.3741.0290.4670.406

0.630.170.801.58

(0.30, 1.30)(0.02, 1.24)(0.32, 1.99)(0.71, 3.49)

GradingII vs IIII vs I

1.202.05

0.3910.377

3.327.74

(1.54, 7.14)(3.70, 16.2)

Surgical MarginsMacro (R2) vs Micro (R0/R1) 1.43 0.364 4.18 (2.05, 8.54)

…liposarcoma rarely get cured…

Log-Relative hazard of death for all causes according to tumour size from the

piecewise regression model.

…our nomogram…

Model performancePredictive performance: adjusted C Index=0.73 (satisfactory accuracy)

Calibration plots: predicted and observed survival probabilities in good agreement.

We do have now different tools…

Which one should we choose ?

INT - Milan

MDACC - Houston

MSKCC - NY

MSKCC - NY

GI 75% 85% 85% 80%

GII 40% _ _ 40%

GIII 10% 55% 46% 10%

60 yr 25 cm

5 yr OS

GI 65% _ 63% 60%

GII 15% _ _ 15%

GIII 0% _ 27% 0%

10 yr OS

Liposarcoma

GI 80% _ 80% _

GII 50% 45% _ _

GIII 15% _ 33% _

5 yr OS

GI 65% _ 52% _

GII 35% _ _ _

GIII 0% _ 16% _

10 yr OS

60 yr 25 cm

Leiomyosarcoma

GI 80% _ 64% _

GII 35% 45% _ _

GIII 0% _ 12% _

5 yr OS

GI 65% _ 28% _

GII 20% _ _ _

GIII 0% _ 3% _

10 yr OS

60 yr 25 cm

MPNST

GI 95% _ 78% _

GII _ 45% _ _

GIII 68% _ 30% _

5 yr OS

GI 90% _ 49% _

GII _ _ _ _

GIII 45% _ 13% _

10 yr OS

60 yr 25 cm

SFT

Conclusions

• 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)

…next step…

INT - Milan

MDACC - Houston

•Cross-check comparisons

MDACC - Houston

INT - Milan

•Call for somebody else in the game for external validation

•Combine series to come out with a possibly better tool

alessandro.gronchi@istitutotumori.mi.it