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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 ….