...

neuro-oncologia nelle aree critiche gliomi a basso grado

by user

on
Category:

therapy

125

views

Report

Comments

Transcript

neuro-oncologia nelle aree critiche gliomi a basso grado
Le metastasi cerebrali
Nuove classi di rischio e sopravvivenza
Antonio Silvani
UOC Neurologia 2- Neuro-oncologia
Dipartimento di Neuro-oncologia
23 aprile 2015 Hotel Palace Como
Number of
metastases
Factors Used
to Assess
Therapy
Patient’s
input
Age / KPS
Therapy
Primary
tumor / stage
Extracranial
disease
Neurological
deficits
Size of
lesion(s)
• Location
Patients with brain metastases comprise a heterogeneous patient
population
In many patients with brain metastases, the primary therapeutic aim is
symptom palliation and maintenance of neurologic function, but in a
subgroup, long-term survival is possible
More accurate prognostic information may support the decision making
process and treatment recommendations for these patients
RPA: Recursive Partitioning Analysis
SIR: Score Index Radiosurgery
Five major
indices
BSBM: Basic score for brain metastases
GPA: Graded Prognostic Assessment
Modified RPA
Able to carry on normal activity and to work; no
special care needed.
Unable to work; able to live at home and care
for most personal needs; varying amount of
assistance needed.
Unable to care for self; requires equivalent of
institutional or hospital care; disease may be
progressing rapidly.
100
Normal no complaints; no evidence of disease.
90
Able to carry on normal activity; minor signs or
symptoms of disease.
80
Normal activity with effort; some signs or symptoms
of disease.
70
Cares for self; unable to carry on normal activity or
to do active work.
60
Requires occasional assistance, but is able to care for
most of his personal needs.
50
Requires considerable assistance and frequent
medical care.
40
Disabled; requires special care and assistance.
30
Severely disabled; hospital admission is indicated
although death not imminent.
20
Very sick; hospital admission necessary; active
supportive treatment necessary.
10
Moribund; fatal processes progressing rapidly.
0
Dead
KARNOFSKY PERFORMANCE STATUS SCALE : KPS
RTOG
85-28
RPA tree
1200
BM pts
RTOG
79-16
RTOG
89-05
Brain Metastases:
Recursive Partitioning
Analysis
Gaspar L et al.
Int J RadiatOncol Biol Phys.
1997
Class I
Class II
KPS ≥ 70
KPS ≥ 70
Primary
controlled
Primary
uncontrolled
Class III
KPS <70
Age < 65
Age ≥ 65
No extracranial
MTS
extracranial
MTS
Performance status and active extracranial disease as major indicators
of outcome following therapy
Brain Metastases:
Recursive Partitioning
Analysis
Gaspar L et al.
Int J RadiatOncol Biol Phys.
1997
Class I
Class II
KPS ≥ 70
KPS ≥ 70
Primary controlled
Primary uncontrolled
Class III
KPS <70
Age < 65
Age ≥ 65
No extracranial MTS
extracranial MTS
MST 7.1 mons
MST 4 .2
MST 2.3 mons
20%
65%
15 %
Recursive
Partitioning
Analysis (RPA)
Classification
Predicts Survival
in Patients with
Brain Metastases
from Sarcoma
Grossman G World Neurosurg. 2014
 Radiographically distinct on
MRI/CT
Favorable
Characteristics of Brain
Metastases for SRS
 Pseudospherical shape
 Displaces normal brain tissue
 Minimal invasion of normal brain
 Size at presentation ≤3 cm
SIR Index
RPA
SIR Index
0
1
2
Age
Age yrs
≥ 60
51-59
≤ 50
KPS
KPS
≤ 50
60-70
>70
Systemic disease st
Systemic disease status
PD
PR–SD
CR–NED
Largest lesion volume cm3
>13
5-13
<5
Number of lesions
≥3
2
1
Extracranial mts
Basic score for
brain
metastases
(BS-BM)
Score
Variable
0
1
50-70
80-100
Control of primary
tumor
No
Yes
Extracranial MTS
Yes
No
KPS
Graded Prognostic
Assessment (GPA) for
brain metastases
Sperduto P Int J Radiat Oncol Biol
Phys 70:510, 2008
To incorporate new data from
RTOG9508 that showed the
number of metastases to be
prognostic
To eliminate treatment factors
because the point of a prognostic
index is to guide treatment
choice, rather than reflect
treatment results
Rationale
To eliminate components that
are difficult to quantify and/or
subjective, such as control of
extracranial disease
GPA
Graded Prognostic
Assessment (GPA) for
brain metastases
Sperduto P Int J Radiat Oncol Biol
Phys 70:510, 2008
RPA
SCORE-GPA
Age
KPS
Extracranial
mts
0
0.5
1
Age
>60
50-69
<50
KPS
<70
70-80
90-100
Number of
CNS
metastases
>3
2-3
1
Extracranial
mts
Present
Systemic
Status disease
SCORE
Median Survival
3.5-4
11.0 mons
3
6.9
1.5-2.5
3.8
0-1
2.6
None
Age 67
KPS 70-80
Number of
CNS metastases: 3
Extracranial
metasteses None
GPA: 2.5
OS: 3.8 mts
‘Subtype’
Luminal A’
ER and/or PgR positive
HER2 negative
Ki-67 low (<14%)
Breast cancer:
Systemic
treatment
recommendations
for subtypes
‘Luminal B (HER2
positive)’
‘ER and/or PgR positive
Any Ki-67, HER2 overexpressed or amplified
HER2 positive (non
luminal)
HER2 over-expressed or
amplified
ER and PgR absent
Triple negative (basal)’
Type of therapy
Notes on therapy
Endocrine therapy alone
Few require cytotoxics
(e.g. high nodal status or
other indicator of risk:
No data are available to
Cytotoxics + anti-HER2 +
support the omission of
endocrine therapy
cytotoxics in this group
Cytotoxics + anti-HER2
Cytotoxics
Patients at very low risk
(e.g. pT1a and node
negative) may be
observed without
systemic adjuvant
treatment.
Lung
Are prognostic
factors the
same in
different
histologies ?
Age
x
KPS
x
ECM
x
NoBM
x
Subtype
Melanoma
Breast
Renal
GI
x
x
x
x
x
x
x
x
x
Graded
Prognostic
Assessment
(GPA) worksheet
to estimate
survival from
brain metastases
(BM) by
diagnosis
Paul W. Sperduto et al. JCO 2012;30:419-425
Breast
Kaplan-Meier
curves for
survival for six
diagnoses by
Graded
Prognostic
Assessment
(GPA) group,
SCLC
Renal ca
Paul W. Sperduto et al. JCO 2012;30:419-425
NSCLC
Melanoma
GI ca
Prognostic
factors
0
0.5
1.0
1.5
2.0
≤50
<60
70-80
90-100
na
Subtype
basal
na
LumA
Her2
LumbB
Age
≥60
≤60
na
na
na
KPS
GPA worksheet to
estimate survival
from brain
metastases
in breast cancer
Paul W. Sperduto JNO 2013
Total
Subtype
Basal
Triple Negative (ER/PR/HER2-neg)
LuminalA
ER/PR-pos, HER2-neg
Luminal B
Triple Positive, ER/PR/HER2-pos
Her-2
HER2-pos, ER/PR-neg
Score
60
50
The effect of tumor
subtype on the time
from primary diagnosis
to development of
brain metastases and
survival in patients
with breast cancer
PW Sperduto JNO2013
40
30
20
10
0
Basal
Her2
Median months from primary
DX to brain METS
Luminal B
Luminal A
MST in months from
brain MET treatment
http://brainmetgpa.com
NSCLC
Age 67
KPS 70-80
Number of
CNS metastases: 3
Extracranial
metasteses None
NSCLC
Age 67
KPS 70-80
Number of
CNS metastases: 3
Extracranial
metasteses None
NSCLC
Age 67
KPS 90-100
Number of
CNS metastases: 3
Extracranial
metasteses None
NSCLC
Age 67
KPS 70-80
Number of
CNS metastases: 3
Extracranial
metasteses None
NSCLC
Age 67
KPS 70-80
Number of
CNS metastases: 3
Extracranial
metasteses None
NSCLC
Age 67
KPS 70-80
Number of
CNS metastases: 3
Extracranial
metasteses None
http://brainme
tgpa.com
Exeresis
14 dec 2014
SRT
CHT
April 2
Adenocarcinoma
Large Cell
Squamous
P value
GPA 3.5–4.0
11.2
4.1
10.6
0.8597
GPA 3
12.1
10.2
6.9
0.0420
GPA 1.5-2.5
6.1
4.6
3.6
0.0052
GPA 0-1
3.2
2.2
3.2
0.0205
412 newly
diagnosed patients
treated outside of
clinical trials
1983-2011
“typical patient populations that many oncologists in Europe will face in
everyday practice are different from those included in the multi-institutional
database (11 institutions from the United States and Canada, time period 1985
to 2007”
More than 50% of patients in each diagnosis stratum had surgery or
radiosurgery (SRS) as a component of treatment, except for those with
small-cell lung cancer (whole-brain radiotherapy
Nieder
Sperduto 2012
412 (yrs 1983-2011)
3940 (yrs 1985-2007)
NSCLC+Melanoma
69%
67%
Surgery or SRS ± WBRT
19%
45%
Worst Group 0-1 points
36 %
16 %
Best Group 3-5 points
7%
14%
Median survival months
3.6
7.2
7
13.8
2.7
3.1
Pts
Median survival breast
Median survival 0–1 points
Primary tumour type
Nieder
Sperduto
Lung cancer
KPS, age
KPS, age, number of BM,
extracranial metastases
Breast cancer
KPS
KPS, age, histology
Renal cell cancer
Extracranial metastases,
number of BM
KPS, number of BM
Gastrointestinal primary
KPS, extracranial metastases, KPS
number of BM
Malignant melanoma
KPS, number of BM
KPS, number of BM
The real-world
utility of
predictions
Questions
1
How do the many clinical pieces of information result in a prediction,
and how accurate is that prediction?
2
Does the survival expectation differ among medical specialties?
3
How often is our expectation very wrong?
4
Are clinicians overly optimistic, fairly accurate, or nihilistic?
NSCLC
breast
Grazie per l’attenzione
Antonio Silvani
[email protected]
Fly UP