Multimodality therapy for locally advanced thymomas: a cohort study of prognostic

factors from a European multicentric database

Dr. GIOVANNI LEUZZIDepartment of Surgical Oncology

Thoracic Surgery Unit“Regina Elena” National Cancer Institute, Rome, Italy

Relevant Financial Relationship Disclosure Statement

95th ANNUAL MEETING OF AMERICAN ASSOCIATION FOR THORACIC SURGERY

Seattle (U.S.A.), April 25-29, 2015

Multimodality therapy for locally advanced thymomas: a cohort study of prognostic factors from a European multicentric database

Giovanni Leuzzi, M.D.

In Compliance with UEMS/EACCME Guidelines, potential conflicts of interest or support relevant to the above presentation that might cause a bias are declared

as follows:

No potential conflicts of interest to report

Conflicts of interest to report: (company name, type of relationship)

x

Background

Locally-advanced Thymomas (LATs): 20-29 %

Heterogeneous entity o Different tumor size o Different organ involvements

Radical resection not usually feasible (50-78%)

~ 50 % LATs experience recurrence after surgery

Higher stage (III-IV) and R+ resection decrease survival

Multimodality therapies Induction Therapy (IT)

Chemo and radio-responsivityFew studies (retrospective or clinical trials, small

samples)R0 resection: 22-92 % *7-y OS and RFS: ~70 % *Author Years Patients(Sta

ge)IT % R0 OS

Macchiarini et al.

1988–1990

7 (7-III) PEV 10 – 57 %

80% (2 years)

Rea et al. 1985–1991

16 (13-III, 3-IVA)

ADOC 69 – 100 %

70% (3 years)

Venuta et al. 1989–2002

15 (15-III) PAC 67 – 100 %

90% (10 years)

Kim et al. 1990–2000

22 (11-III, 11-IV)

ADOC 76 – 95 %

95% (5 years)

Lucchi et al. 1976–2003

25 (III + IVA) PEV 75 – 100 %

78% (5 years)

Wright et al. 1997–2006

10 (6-III, 3-IVA)

PE + RT

80 – 100 %

69% (5 years)

* Kondo K. Therapy for thymic epithelial tumors. Gen Thorac Cardiovasc Surg. 2014 Aug;62(8):468-74.

Multimodality therapies Adjuvant Therapy (AT)

Retrospective studies or clinical trials Heterogeneous samplesSurvival advantage controversial

Author Years Patients(Stage)

AT Survival Benefit

Kondo et al 1990-1994

1320 (all) RT No

Korst et al.* 1981-2008

592 (II-III) RT No

Omasa et al. 1991–2010

270 (III) RT No

Ruffini et al. 1990–2010

2030 (all) RT/CT Yes (OS)

Weksler et al. ? (SEER) 476 (III) RT Yes (RFS)* Meta-analysis

Multimodality therapies

Surgery alone Surgery + AT

IT + Surgery IT + Surgery + AT

AIM

To explore:

the factors affecting the outcome

the impact of multimodality treatments

in the subset of LATs (Masaoka-Koga stage III thymomas)

Our experience

European Society of Thoracic Surgeons (ESTS) thymic database

(38 Institutions)

2317 surgically-treated Thymic Tumors

(01/1990 – 01/2010)

370 Masaoka-Koga stage III Thymomas (WHO Histology A to

B3)

Stage I, II and IV excluded

Thymic carcinoma and NETT excluded

Our experience

370 Masaoka-Koga stage III Thymomas

(WHO Histology A to B3)

* according to the IASLC/ITMIG TNM staging proposal

EXAMINED FEATURES

Demographics Paraneoplastic syndromes WHO histology Tumor size Type and extension of surgery Completeness of resection T classification * Kind of IT and AT Cause of death Recurrence

OUTCOMES

Overall Survival (OS) Cancer-specific Survival (CSS) Recurrence-free Survival (RFS) Cumulative Incidence of

Recurrence (CIR)

Clinical, surgical and pathological features  Age (years) Median (range) 54(10-93)Gender

Female 195(52.7%)Male 175(47.3%)

Paraneoplastic syndromes Myasthenia Gravis 120(36.5%)

Others 10 (3.0%)WHO Histology

A 25 (6.8%) AB 37(10.1%)

B1 47(12.8%)B2 131(35.8%)B3 126(34.5%)

Surgical approach  Sternotomy 274(85.6%)

Thoracotomy 36(11.3%)VATS/Robotic 10 (3.1%)

Kind of thymectomy Radical 254(96.2%)Partial 10(3.8%)

Tumor Size (cm) Median (range)

5 (1-21)

Extent of resection  Pleura 62(25.6%)

Lung 130(53.7%)Pericardium 97(40.1%)Diaphragm 3(1.2%)

Phrenic nerve 29(12.0%)Vessel 33(13.6%)

Pathological resection status

 

R0 258(74.1%)R1 53(15.2%)R2 37(10.7%)

Pathologic invasion  Pleura 66(26.9%)

Lung 121(49.4%)Pericardium 116(47.3%)Diaphragm 3 (1.2%)

Phrenic nerve 26(10.6%)Vessel 37(15.1%)

pT  1 17(6.9%)2 63(25.6%)3 166(67.5%)

Induction therapy  IT group

 No IT group

p-value

Age (years)    < 54 56 (63.6%) 110 (45.3%) 0.004

Gender Female 41(46.6%) 115(47.3%) 0.91

Male 47(53.4%) 128(52.7%)Paraneoplastic syndrome 17(21.2%) 111(46.4%)

< 0.0001

WHO Histology A 1 (1.1%) 18(7.5%) 0.05

AB 4(4.6%) 27(11.2%)B1 10(11.5%) 33(13.7%)  B2 38(43.7%) 83(34.4%)  B3 34(39.1%) 34(39.1%)  

Radical thymectomy   64(91.4%) 180(97.8%) 0.03Pathological resection status      

R0 53(65.4%) 187(79.9%) 0.01R1 15(18.5%) 25(10.7%)  R2 13(16.1%) 22(9.4%)  

pT 1 1 (1.6%) 15(10.3%) 0.092 15(23.4%) 34(23.3%)3 48(75.0%) 97(66.4%)

Tumor size (cm) Median 5 (2-17) 5 (1-21) 0.27

353 pts *

88 pts(24.9%)

CT 76.1%CT-RT 19.4%RT 4.5%

*patients with available data on oncological therapies

Adjuvant therapy  AT group

 No AT group

p-value

Age (years)    

< 54137

(55.9%) 43 (40.6%) 0.008Gender

Female106

(43.3%) 57 (53.8%) 0.07

Male139

(56.7%) 49 (46.2%)  Paraneoplastic syndrome 94 (42.0%) 33 (35.5%) 0.28WHO Histology

A 10 (4.1%) 11(10.6%) 0.008 AB 23 (9.4%) 12(11.5%)  

B1 32(13.1%) 13(12.5%)  B2 85(34.8%) 42(40.4%)  B3 94(38.5%) 26(25.0%)  

Radical thymectomy   179(96.2%) 72(96.0%) 0.93Pathological resection status      

R0 182(76.8%) 71(71.7%) 0.61R1 32(13.5%) 16(16.2%)  R2 23(9.7%) 12(12.1%)  

pT 1 15 (9.4%) 2(2.9%) 0.0032 46(28.9%) 11(15.7%)  3 98(61.6%) 57(81.4%)  

Tumor size (cm) Median 5 (2-21) 6 (1-17) 0.001

353 pts *

245 pts(69.4%)

RT 64.1%CT-RT 31.0%CT 4.9%

*patients with available data on oncological therapies

Outcome

5-year 10-year

OS 82.8% 68.9%

CSS 88.4% 83.3%

RFS 80.0% 71.5%

5-year 10-year

CIR 20% 28.5%

Median Follow-up: 60 months (1-248)

Outcome analysis

Variables OS

HR [95%CI] p–value

CSS

HR [95%CI] p–value

RFS

HR [95%CI] p–value

 Age

 R0 resection

 Adjuvant therapy

 pT

1.80[1.11-2.90]

 2.38[1.44-3.92]

 2.02[1.23-3.31]

-

0.016

0.001

0.005

-

-

 2.15[1.16-4.00]

2.44[1.32-4.48]

-

-

0.015

0.004

-

-

 -

-

2.49[1.19-5.21]

-

-

-

0.016

Multivariate Cox Regression analysis

Outcome analysis

Variables OS

HR [95%CI] p–value

CSS

HR [95%CI] p–value

  

Adjuvant therapy

2.68[1.40-5.14] 0.003 3.60[1.54-8.81]

0.003

Propensity Score Match analysisConfounding variables

Age Gender

WHO Histology

Exact match (1:2) for

Pathological Resection Status

Outcome & Treatment Strategy

Treatment strategy (n=353)

Pts (%) 

Surgery alone66(18.7%

)IT + Surgery +

AT46(13.0%

)

IT + Surgery42(11.9%

)

Surgery + AT199(56.4

%)

CSS (months)

1209060300

Pro

bab

ilit

y o

f S

urv

ival

)

1.0

.9

.8

.7

.6

.5

.4

.3

.2

.10.0

Surgery aloneIT + Surgery + ATIT + SurgerySurgery + AT

p=0.006

CSS (months)

Pro

bab

ilit

y of

Su

rviv

al

IT Group

Primary Surgery Group

p-value

CSS 85.0% 88.3% 0.82

RFS 77.9% 84.0% 0.31

Outcome & Adjuvant Therapy

Pro

bab

ilit

y of

Su

rviv

al

p=0.0004

AT Group No AT Group p-value

CSS 91.1% 81.5% 0.0004

RFS 85.5% 79.3% 0.19

Outcome & Adjuvant Therapy

Type of AT:

}p=0.06

Stage III & Postop Therapy

Masaoka Stage III Thymomas

Different Tumor Size

Different p-Tumor invasion*

Adjuvant therapy

Surveillance

Tumor heterogeneity

* according to the IASLC/ITMIG TNM staging proposal

CSS (months)

1209060300

Pro

babi

lity

of

Sur

viva

l

1.0

.9

.8

.7

.6

.5

.4

.3

.2

.10.0

Pro

bab

ilit

y of

Su

rviv

al

p=0.08

pT2

pT & Adjuvant Therapy

Adjuvant therapy?Surveillance?

Adjuvant therapy

CSS (months)

1209060300P

robab

ilit

y o

f S

urv

ival

1.0

.9

.8

.7

.6

.5

.4

.3

.2

.10.0

p=0.04Pro

bab

ilit

y of

Su

rviv

al

pT3

T-size & Adjuvant Therapy

Adjuvant therapySurveillance ?

Adjuvant therapy?Tailored therapy ?

Limitations of the study

• Retrospective study

• Data collected from centers of different volume activity, expertise and geographic areas

• No central pathologic review

• IT and AT modalities not standardized

• Indications for IT and radiological response to IT not properly elucidated

• Pathological nodal status not available

Conclusions

The assessment of the optimal multimodality strategy in LATs is still controversial

Our analysis indicates that Induction Therapy is not associated with a survival advantage.

Administration of Adjuvant Therapy and Completeness of Resection represent the most significant outcome predictors.

Adjuvant Therapy should be administered whenever possible, especially in those patients with specific pathological features (pT2/3 or tumor size smaller than 5 cm) who may benefit the most from multimodality treatment. Further studies are needed to confirm these data and to define optimal postoperative therapeutic regimens according to different pathological cancer characteristics.

Thank you for your attention ….