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Yago Garitaonaindía
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P09 - Health Services Research/Health Economics - Real World Outcomes (ID 121)
- Event: WCLC 2020
- Type: Posters
- Track: Health Services Research/Health Economics
- Presentations: 2
- Moderators:
- Coordinates: 1/28/2021, 00:00 - 00:00, ePoster Hall
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P09.12 - SARS- CoV2 Impact in a Spanish Lung Cancer Cohort? (ID 2995)
00:00 - 00:00 | Author(s): Yago Garitaonaindía
- Abstract
Introduction
Madrid has been the epicenter of the SARS-CoV2 pandemic in Spain. We analyzed our experience with SARS-CoV2 infection and cancer patients (p).
Methods
The analysis was carried out from March 1 to April 30 at the Puerta de Hierro University Hospital in Madrid. All patients with diagnosis of SARS-CoV2 infection by RT-PCR were included.
Results
During the study period, overall in-hospital mortality of cancer p with COVID-19 was 15.2% (95%CI, 6.3; 5.2), similar to 12.7% (95%CI,11.1;4.4) (p=0.615) of the global COVID-19 hospitalised population and greater than patients admitted without SARS-CoV-2 infection during the same period 4.3% (95%CI; 3.6;5.2) p<0.001.
Among the 653 patients receiving active cancer therapy, 24 (3.7%) developed COVID-19 and required admission, 4.2% of those were receiving chemotherapy, 9.5% immunotherapy and 2.1% targeted therapies. Lung and breast cancer were the most frequent (26.1%), followed by colorectal (19.6%) and breast cancer. Non-significant differences were found due to the cancer treatment received. Mortality in patients with lung cancer was the highest with 25%.
The univariate analysis comparing patients who developed a serious event to those who did not (Table2), showed that the higher Brescia, CURB-65 scale, the lactate dehydrogenase (LDH) or C-reactive protein (CRP) levels were at admission, the greater the risk of developing severe complications, with statistically significant results (table 2).
VARIABLE
OTHER CANCER PATIENTS, N=34 (%)
LUNG CANCER PATIENTS, N=12 (%)
Gender (male)
18 (52.9)
6 (50)
Age at hospitalization, mean (sd)
63.9 (10.2)
63.5 (15.5)
Active Smoking
0 (0.0)
2 (16.7)
Ex-smokers
12 (35.3)
6 (50)
COMORBIDITIES
Coronary heart disease
3 (8.8)
2 (16.7)
Hypertension
12 (35.3)
5 (41.7)
Hypothyroidism
3 (8.8)
0 (0.0)
COPD
3 (8.8)
2 (16.7)
Obesity
2 (5.9)
0 (0.0)
Diabetes
6 (17.7)
0 (0.0)
Dyslipidemia
8 (23.5)
3 (25.0)
LINES OF TREATMENT
First line
18 (52.9)
5 (41.7)
Other lines
8 (23.5)
5 (41.7)
Pending treatment
8 (23.5)
2 (16.7)
Recent cancer treatment <30d
11 (32.3
8 (66.7)
Active treatment
23 (67.6)
6 (50.0)
Others
10 (30.3)
0 (0.0)
SYMPTOMS
OTHER CANCER PATIENTS (N=34)
LUNG CANCER PATIENTS (N=12)
p-value
Neutropenia
2 (6.1)
0 (0.0)
1.000
Cough
23 (67.6)
5 (41.7)
0.170
Fever
26 (76.5)
9 (75.0)
0.918
Temperature
37.1 (1.0)
37.3 (1.1)
0.360
Dyspnoea
16 (47.0)
11 (91.7)
0.007
Diarrhoea
3(8.8)
1 (8.3)
1.000
Lymphopenia
22 (68.7)
4 (36.4)
0.080
PROGNOSTIC CRITERIA
IL6
0.416
<4,4
28 (82.3)
8 (66.7)
≥4,4
6 (17.7)
4 (33.3)
D-DIMER
0.9 (0.6; 2.2)
0.9 (0.5; 2.7)
0.574
<0,5
5 (17.9)
3 (27.3)
0.761
0,5-7
22 (78.6)
8 (72.7)
>7
1 (3.5)
0 (0.0)
PCR
107.7
0.449
<10
7 (21.9)
1 (9.1)
10-150
16 (50.0)
8 (72.7)
>150
9 (28.1)
2 (18.2)
LDH
266 (207; 326)
290 (238; 352)
0.195
<246
14 (46.7)
3 (27.3)
0.309
≥246
16 (53.3)
8 (72.7)
FERRITIN
562 (358; 933)
1111 (392; 2672)
0.158
CHARLSON INDEX
8 (6; 9)
8 (6; 9)
0.800
CURB65 SCALE
0.314
0-1
21 (61.8)
5 (41.7)
≥2
13 (38.2)
7 (58.3)
BRESCIA SCALE
0.178
0-1
30 (88.2)
8 (66.7)
≥2
4 (11.8)
4 (33.3)
Table 1. General characteristics, symptoms at diagnosis and prognostic data.COPD: chronic obstructive pulmonary disease,Charlson index (Comorbidities), Curb65 scale (includes age, confusion, urea, breathing frequency, blood pressure), Brescia Scale (depends on oxygen needs). P-values: comparison between lung cancer patients and the other.
VARIABLE
N VALID (N=46)
NON-SERIOUS EVENT (N=38)
SERIOUS EVENT (N=8)
P-VALUE
OR (95% CI)
Gender (male)
46
20 (52.6)
4 (50.0)
0.892
0.9 (0.19; 4.14)
Age at hospitalization
40
63.2 (11.6)
67 (11.4)
0.376
1.04 (0.96; 1.21)
Active Smoking
46
2 (5.3)
0 (0.0)
1
---
Ex-smokers
46
16 (42.1)
2 (25.0)
0.453
0.46 (0.08; 2.57)
Hypertension
46
14 (36.8)
3 (37.5)
0.972
1.02 (0.21; 4.97)
COPD
46
4 (10.5)
1 (12.5)
0.871
1.21 (0.12; 12.57)
Dyslipidaemia
46
10 (26.3)
1 (12.5)
0.418
0.40 (0.04; 3.67)
Higher ferritin
26
598 (382; 1111)
975 (903; 2403)
0.396
1.00 (0.99; 1.00)
Higher IL6 ≥4,4
46
8 (21.1)
3 (37.5)
0.330
2.2 (0.44; 11.48)
Higher D- Dimer
41
1.1 (0.7; 2.2)
2.6 (1.5; 5.6)
0.069
1.39 (0.97; 1.99)
First LDH
41
254 (195; 316)
354 (266; 441)
0.020
1.01 (1.00; 1.03)
Higher LDH
40
271 (227; 332)
619 (354; 812)
0.007
1.01 (1.00; 1.03)
First CRP
43
95 (11; 146)
169 (89; 228)
0.038
1.01 (1.00; 1.02)
Higher CRP
42
116 (43; 167)
202 (130; 249)
0.018
1.02 (1.00; 1.03)
Brescia
44
0.5 (0; 1)
2 (2; 5)
0.004
19.5 (2.54; 149.7)
CURB-65
42
1 (1; 2)
2 (1; 3)
0.060
2.41 (0.97; 6.03)
Table 2.
Cancer patients, especially lung ones, and SARS-CoV2 infection have a worse overall prognosis than the general population.
Objective parameters such as LDH, CRP at admission, Brescia index or CURB-65 should alert us to a more serious evolution and suggest early an early intensive care unit (ICU) admission.
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P09.50 - Lung Cancer Hospitalization Burden. Generating Knowledge from Administrative Data to Optimize Management. (ID 3565)
00:00 - 00:00 | Author(s): Yago Garitaonaindía
- Abstract
Introduction
Hospitalization secondary to lung cancer is a common event and causes significant resource consumption. From a basic set of administrative data of mandatory registration for all admissions, with demographic and clinical information recorded according to International Classification of Diseases (ICD), we aim to evaluate real-world health results and understand the hospitalization needs of lung cancer patients.
Methods
We conducted a retrospective observational study selecting all patients with lung cancer admitted to the Hospitalization Unit of the Medical Oncology Department at Puerta de Hierro University Hospital between 2009 and 2015. Administrative, epidemiological and diagnosis information encoded by ICD-9-MC version was analysed. A classification algorithm was coded to link morphological codes and diagnosis codes of ICD to identify subgroups of lung cancer. Our objective was to describe the lung cancer hospitalization burden and assess the quality of care.
Results
Between 2009 and 2015 there were 5440 admissions in the Medical Oncology Department, 1460 (26,8%) were lung cancer patients.
The main results of the study are summarized in the attached table.
Conclusion
Lung cancer is the neoplasm with the highest burden of hospitalization in our department (26,8%). NSCLC accounts for 87.1% of admissions (46.7% adenocarcinomas). ED admissions account for 71.4% and 97.3% for NSCLC and SCLC respectively. The average stay of 7.6 days, a hospital exitus rate of 16% and a readmission rate in 7 days of 5.2% allow to assess the quality of care.
A key issue addressed by our study is to develop a culture of evaluation of health results. The main limitation is that data entry is carried out by the admission department, so the applicability in clinical management must be taken with caution.
Automating the analysis of hospital activity through data science approaches will be essential for the development of learning health care systems.
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P25 - Mesothelioma, Thymoma and Other Thoracic Malignancies - Mesothelioma Preclinical, Prognostic and Predictive Factors (ID 139)
- Event: WCLC 2020
- Type: Posters
- Track: Mesothelioma, Thymoma and Other Thoracic Malignancies
- Presentations: 1
- Moderators:
- Coordinates: 1/28/2021, 00:00 - 00:00, ePoster Hall
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P25.06 - Malignant Pleural Mesothelioma: Patient Characteristics, Treatments and Outcomes from a Spanish Center (ID 3005)
00:00 - 00:00 | Presenting Author(s): Yago Garitaonaindía
- Abstract
Introduction
Malignant pleural mesothelioma (MPM) is a rare but aggressive tumour whose clinical and pathological diagnosis represents a challenge, due to delayed diagnosis and poor prognosis.
The aim of this study is to describe the demographic and clinical characteristics of patients with malignant pleural mesothelioma, as well as their subsequent treatments and outcomes in Hospital Universitario Puerta de Hierro Majadahonda, Madrid, Spain.
Methods
We conducted a retrospective study including 51 patients with confirmed diagnosis of malignant pleural mesothelioma between 2008 and 2020. We collected information regarding epidemiology, treatments and survival patterns of patients with MPM. The cohort was divided in 3 groups depending on stage (I-II, III and IV), excluding non-treated patients. Progression-free survival (PFS) was calculated from the initiation of first-line treatment until the date of progression or death and overall survival (OS) was calculated from the initiation of first-line treatment until the date of last follow-up or death.
Results
Demographic characteristics of patients are shown in Table-1.
70.6% of patients were male, and the mean age at diagnosis was 65.5 years. Asbestos exposure was reported in 13.7% of patients. Most patients were diagnosed by pleural biopsy (85%). The most frequent histological subtype was epithelioid (75%).
Treatments and outcomes are shown in Table-2.
Surgery was performed in 6 patients stage I-II (54.5%) and in 8 patients stage III (33.3%). The first-line of chemotherapy most used regardless of stage was a platinum-doublet with pemetrexed.
Median OS was 17.0 months (95% CI, 9.08-24.92) with a median PFS of 8.0 months (95% CI, 2.25-13.75).
Only 9.1% of patients were included in clinical trials and 6.8% received immunotherapy.
Table-1. Demographic characteristics Sex
Female = 15 (29.4%)
Male = 36 (70.6%)
Mean age (years, 95% CI)
Mean: 65.51 (63.11-67.91)
Range: 44 (35-79)
Smoking habits
Never smoker: 16 (33.3%)
Current smoker: 9 (18.8%)
Former smoker: 23 (47.9%)
Non-available/unknown: 3 (5.8%)
Packs-year (CI 95%)
Mean: 37.121 (26.086-48.156)
Comorbidities
HTN: 26 (51%)
DL: 21 (41.2%)
Cardiopathy: 10 (19.6%)
Charlson: 8.49 (8.15-8.83)
Previous pleural pathology
5 (9.8%)
Simplified profession
Industry/construction: 15 (29.4%)
Others: 8 (15.7%)
Painter: 3 (5.9%)
Unknown: 25 (49%)
Exposure to inhaled agents recorded
12 (23.5%)
Asbestos exposure identified
7 (13.7%)
ECOG
0: 19 (37.3%)
1: 17 (33.3%)
2: 3 (5.8%)
3: 1 (2.0%)
Unknown: 11 (21.6%)
Symptoms
Dyspnea: 31 (60.8%)
Cough: 16 (31.4%)
Constitutional syndrome: 13 (25.5%)
Costal pain: 7 (13.7%)
Hemoptysis: 1 (2%)
Diagnosis image tests
PET-CT: 1 (2.0%)
Chest CT: 42 (82.4%)
Unknown: 8 (15.7)
Test sensitivity
Pleural cytology: 15 (38.5%)
Pleural biopsy: 39 (84.8%)
Stage
I: 4 (7.8%)
II: 8 (15.7%)
III: 24 (47.1%)
IV: 10 (19.6%)
Unknown: 5 (9.8%)
Metastatic location
Lung: 6 (66.7%)
Bone: 2 (22.2%)
Hepatic: 1 (11.1%)
Histology
Epithelioid: 36 (75.0%)
Biphasic: 6 (12.5%)
Sarcomatoid: 2 (4.2%)
Desmoplastic: 2 (4.2%)
Non-available/unknown: 5 (9.8%)
Table-2. Treatment and outcomes Variables
Stages I-II (N = 11)
Stage III (N = 24)
Stage IV (N = 9)
Age (mean, 95% CI, range)
65.18 (57.14-73.22)
44 (35-79)
64.67 (61.68-67.65)
23 (55-78)
64.7 (57.32-72.01)
31 (44-75)
Sex
Female = 7 (63.6%)
Male = 4 (36.4%)
Female = 6 (25.0%)
Male = 18 (75.0%)
Female = 2 (22.2%)
Male = 7 (77.8%)
First line
Treatment
Chemotherapy: 5 (45.5%)
Neoadjuvant chemotherapy + surgery + adjuvant radiotherapy: 2 (18.2%)
Surgery + adjuvant chemotherapy: 4 (36.4%)
Chemotherapy: 12 (50%)
Surgery + adjuvant radiotherapy + adjuvant chemotherapy: 5 (20.8%)
Surgery + adjuvant chemotherapy: 2 (8.3%)
Radiotherapy + chemotherapy: 2 (8.3%)
Neoadjuvant chemotherapy + surgery + adjuvant radiotherapy: 1 (4.1%)
Chemotherapy: 8 (88.9%)
Chemotherapy + Radiotherapy: 1 (11.1%)
Types of surgery
Extended pneumonectomy: 3 (27.7%)
Pleurodesis: 2 (18.2%)
Not specified: 1 (9.1%)
Pleurectomy + amplified decortication: 4 (16.7%)
Extended pneumonectomy: 4 (16.7%)
None
Chemotherapy
Cisplatin + pemetrexed: 3 (27.3%)
Carboplatin + pemetrexed: 5 (45.5%)
Gemcitabine: 1 (9.1%)
Cisplatin + pemetrexed: 11 (45.8%)
Carboplatin + pemetrexed: 9 (37.5%)
Carboplatin + pemetrexed + bevacizumab + atezolizumab: 1 (4.2%)
Carboplatin + pemetrexed: 5 (55.6%)
Cisplatin + pemetrexed: 3 (33.3%)
Carboplatin + pemetrexed + bevacizumab: 1 (11.1%)
Cycles (95% CI)
5.5 (4.32-6.68)
4.9 (4.33-5.47)
4.11 (2.93-5.29)
Maintenance treatment
1 (9.1%)
7 (29.2%)
2 (22.2%)
Maintenance treatment
Pemetrexed: 1 (9.1%)
Pemetrexed: 6 (25%)
Bevacizumab + atezolizumab: 1 (4.2%)
Pemetrexed: 2 (22.2%)
Best response
Progressive disease: 5 (45.5%)
Stable disease: 2 (18.2%)
Partial response: 2 (18.2%)
Progressive disease: 5 (20.8%)
Stable disease: 6 (25%)
Partial response: 5 (20.8%)
Complete response: 4 (16.7%)
Progressive disease: 4 (44.4%)
Stable disease: 1 (11.1%)
Partial response: 2 (22.2%)
Progression-free survival (months, 95% CI)
Mean: 12.0 (8.48-15.26)
Median: 8.0 (2.25-13.75)
Overall survival (months, 95% CI)
Mean: 21.6 (14.83-28.37)
Median: 17.0 (9.08-24.92)
Second line
Relapse
4
15
4
Time to relapse/progression
Local: 4 (36.4%)
Distance: 2 (18.2%)
Local: 15 (62.5%)
Distance: 6 (25.0%)
Local: 3 (33.3%)
Distance: 4 (44.4%)
Treated patients
4 (36.4%)
11 (45.8%)
3 (33.3%)
Treatment (%)
Chemotherapy + radiotherapy: 2 (18.2%)
Chemotherapy: 2 (18.2%)
Chemotherapy: 7 (29.2%)
Radiotherapy: 4 (16.7%)
Chemotherapy: 3 (33.3%)
Chemotherapy
Vinorelbine: 1 (9.1%)
Pemetrexed: 1 (9.1%)
Not specified: 2 (18.2%)
Vinorelbine: 5 (20.8%)
Gemcitabine: 1 (4.2%)
Irinotecan + lurbinectedin: 1 (4.2%)
Vinorelbine: 1 (11.1%)
Nivolumab: 1 (11.1%)
Other immunotherapy: 1 (11.1%)
Cycles
Mean: 3.5
Mean: 2.86
Mean: 7.0
Best response
Progressive disease: 3 (27.3%)
Stable disease: 1 (9.1%)
Progressive disease: 7 (29.2%)
Progressive disease: 2 (22.2%)
Partial response: 1 (11.1%)
Overall survival (months, 95% CI)
Mean: 12.69 (5.34-20.03)
Median: 7.0 (0-16.47)
Third, fourth and fifth line
Chemotherapy
Cisplatin + pemetrexed (retreatment): 1 (9.1%)
Gemcitabine: 1 (9.1%)
Irinotecan: 1 (9.1%)
Gemcitabine: 1 (4.2%)
Carboplatin + pemetrexed (retreatment): 1 (4.2%)
Gemcitabine: 2 (22.2%)
Cisplatin + pemetrexed (retreatment): 1 (11.1%)
Additional data
Included in clinical trials
4 (9.1%)
Patients who received immunotherapy
3 (6.8%)
Survival rate
First year: 58%
Second year: 30 %
Third year: 10%
Fourth year: 3%
Our results confirm that overall survival in patients with new diagnosis of MPM remains poor. Cytology has a low sensitivity and most patients were diagnosed at advanced stage, limiting the possibility of radical approaches.
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P66 - Tumor Biology and Systems Biology - Basic and Translational Science - Outcomes (ID 205)
- Event: WCLC 2020
- Type: Posters
- Track: Tumor Biology and Systems Biology - Basic and Translational Science
- Presentations: 1
- Moderators:
- Coordinates: 1/28/2021, 00:00 - 00:00, ePoster Hall
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P66.04 - Real World Data: Immunotherapy in Lung Cancer Patients over 65 Years Old in Spain (ID 3641)
00:00 - 00:00 | Author(s): Yago Garitaonaindía
- Abstract
Introduction
In the last decade, immunotherapy (IT) has become a key therapeutic tool in lung cancer treatment. The number of elderly patients with this pathology in Spain has been progressively increased in recent years, becoming a representative subgroup nowadays. Studies carried out with IT in these patients are a minority and controversial, generating a need in clinical practice.
The aim of the study is to establish clinical and toxicity differences between patients older and younger than 65 years, treated with IT.
Methods
Retrospective study that includes all epidemiological, clinical and pathological data of patients > 65 and <65 years diagnosed with lung cancer at Puerta de Hierro Hospital from January 2014 to March 2020, and who received treatment with IT, either in the first line or successive.
A total of 155 patients were analyzed. Table 1 summarizes the main characteristics between both populations. The mean number of treatments received in both groups was similar (3.0 in <65 years vs 2.7 in> 65).
When both groups were compared, no statistically significant differences in the percentage of patients who needed to interrupt IT due to toxicity were observed, being 15.9% of those <65 years and 17.9% of those> 65 years (p = 0.576) who required this interruption.
There were also no differences in toxicity between grade 3 or 4 (10.2% vs 10.4%, p = 0.99) or in the number of admissions due to immune-related toxicity (IR) (9.0% vs 4.5%, p = 0.19).
Neither group required immunosuppressive treatment for severe toxicity, but they did require steroids at high doses. There were no deaths secondary to IT toxicity, being the majority due to disease progression.Table 1.
Characteristics
<65 years (88)
>65 years (67)
Gender
Male
Woman
54.5%
45.6%
74.6%
25.4%
Median age
58
72
ECOG
0-1
≥2
93.2%
4.5%
97.0%
3.0%
Charlson index
8
10
Stage
I – 3.4%
II – 6.8%
III - 33.0%
IV – 56.8%
I – 3.0%
II – 11.9%
III – 23.9%
IV – 61.2%
Histology
Adenocarcinoma
Squamous cell carcinoma
Small cell
Others
59.1%
27.3%
2.3%
11.4%
56.7%
25.4%
4.5%
13.4%
PDL-1
Positive
Negative
Unknown
29.5%
9.1%
13.6%
32.8%
16.4%
7.5%
Disease situation at the toxicity moment
Complete response
Partial response
Stable disease
Progression
8.2%
13.7%
20.5%
47.9%
1.6%
27.9%
23.0%
32.8%
Toxicity types
Asthenia
Anemia
Pneumonitis
Thyroid disorders
Cutaneous
Colitis
Nephritis
Hepatitis
Others
11.4%
1.1%
14.8%
10.2%
9.1%
6.8%
0%
3.4%
13.6%
13.4%
0%
11.9%
11.9%
9.0%
4.5%
4.5%
1.5%
9.0%
Toxicity grade
1
2
3
4
17.0%
6.8%
5.7%
3.4%
14.9%
13.4%
8.9%
1.5%
Patients > 65 years with lung cancer who received IT treatment in our center do not experience more serious adverse events, do not require more treatment interruptions or more admissions, compared to those <65 years. Consequently, IT should be a valid treatment option in this population and its management should be optimized, with the aim of offering the best possible quality of care to this subgroup of patients.
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P84 - Targeted Therapy - Clinically Focused - ALK (ID 261)
- Event: WCLC 2020
- Type: Posters
- Track: Targeted Therapy - Clinically Focused
- Presentations: 1
- Moderators:
- Coordinates: 1/28/2021, 00:00 - 00:00, ePoster Hall
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P84.16 - Treatment Options for Patients with Brain Metastases in Oncogene-Driven Non-Small Cell Lung Cancer (ID 3699)
00:00 - 00:00 | Presenting Author(s): Yago Garitaonaindía
- Abstract
Introduction
The brain is a frequent site of metastases in non-small cell lung cancer (NSCLC), specially in those with driver gene mutations. Treatment strategies include surgical resection, central nervous system (CNS) radiotherapy (RT), what includes: whole-brain radiation therapy (WBRT) and stereotactic radiotherapy, and drug therapy like tyrosine kinase inhibitors (TKIs).
Methods
We conducted a single centre retrospective review including 60 (25.3%) NSCLC patients with driver gene mutations (EGFR, ALK, ROS1) and brain metastases from a total of 237 patients treated with TKIs in Hospital Universitario Puerta de Hierro (Spain) between 2008 and 2020. We collected information regarding epidemiology, treatments, response and survival patterns. We analysed patients treated with TKIs alone and specifically patients who were treated with newly developed TKIs that can efficiently penetrate the blood-brain barrier (osimertinib, alectinib, ceritinib, brigatinib, lorlatinib). Radiotherapy-free survival was calculated from the initiation of first-line TKI until the date of CNS RT.
Results
Global characteristics regarding clinical characteristics, treatment and survival are shown in Table-1.
56.7% were female and mean age at diagnosis was 60.0 years. Driver gene mutations were EGFR (80.0%), ALK (20.0%) and ROS1 (0%). 56.7% received CNS RT and median OS was 31.0 months (95% CI, 21.4-46.6) with a median TKI time-treatment 27.0 months (95% CI, 22.0-31.9).
Specific data from patients treated with TKIs alone at the diagnosis of brain metastases and those treated with new generation TKIs are shown in Table-2.
CNS RT was performed in 24% with a RT-free survival mean of 45.15 months (95% CI, 28.85-61.51). Newly developed TKIs achieved a partial or complete CNS response in 42.9%.
Table-1. Global characteristics Clinical characteristics (n = 60)
Sex
Male: 26 (43.3) Female: 34 (56.7)
Age (years, range)
Mean: 60.0 (56.95-63.09)
Histology
Adenocarcinoma: 58 (96.7)
Neuroendocrine carcinoma: 1 (1.7)
Squamous cell carcinoma: 1 (1.7)
Driver gene mutations
EGFR: 48 (80.0)
ALK: 12 (20.0)
ROS1: 0
Mutations reported
Non-reported: 22 (36.7)
Exon 21 L858R: 13 (21.7)
Exon 21 L861Q: 1 (1.7)
Exon 21 (non-specified): 2 (3.3)
Exon 19 deletion: 18 (30.0)
Exon 18 (G719X): 2 (3.3)
Exon 18 (non-specified): 1 (1.7)
Exon 20 (insertion): 1 (1.7)
Smoking status
Smoker: 10 (16.7)
Former smoker: 15 (25.0)
Never smoker: 31 (51.7)
Non-reported: 4 (6.7)
Packs-year (95% CI)
Mean: 26.75 (20.76-32.73)
Comorbidities
Hypertension: 14 (23.3)
Dyslipidemia: 9 (15.0)
Diabetes: 5 (8.3)
Alcohol consumption: 9 (15.0)
First degree family history of cancer
29 (48.3)
ECOG:
0: 31 (51.7)
1: 22 (36.7)
2: 1 (1.7)
Non-reported: 6 (10)
CNS initial affection
43 (71.7%)
CNS type of affection
Unique: 11 (18.3)
Multiple: 47 (78.3)
Non-reported: 2 (3.3)
Radiological findings
Intracranial hypertension: 13 (21.7)
Meningeal carcinomatosis: 16 (26.7)
First TKI treatment (n = 60)
TKI
Erlotinib: 22 (36.7)
Afatinib: 10 (16.7)
Gefitinib: 12 (20.0)
Osimertinib: 5 (8.3)
Crizotinib: 8 (13.3)
Alectinib: 3 (5.0)
Best CNS response
Progressive disease: 3 (5.0)
Stable disease: 12 (20.0)
Partial response: 16 (26.7)
Complete response: 5 (8.3)
Unknown: 24 (40.0)
Best global response
Progressive disease: 5 (8.3)
Stable disease: 11 (18.3)
Partial response: 25 (41.7)
Complete response: 6 (10.0)
Unknown: 13 (21.7)
Reported toxicities
31 (51.7)
Grade of toxicity
1: 14 (23.3)
2: 5 (8.3)
3: 7 (11.7)
4: 1 (1.7)
Non-grade reported: 4 (6.7)
Treatment interruption due toxicity
11 (18.3)
Treatment dose-reduction
4 (6.7)
Second TKI treatment (n =28)
TKI
Erlotinib: 4 (16.0)
Afatinib: 6 (21.4)
Gefitinib: 2 (7.1)
Osimertinib: 6 (21.4)
Brigatinib: 1 (3.5)
Crizotinib: 1 (3.5)
Alectinib: 6 (21.4)
Ceritinib: 2 (7.1)
Non-TKI second line: 32
Best CNS response
Progressive disease: 6 (21.4)
Stable disease: 3 (10.7)
Partial response: 6 (21.4)
Complete response: 1 (3.5)
Unknown: 12 (42.9)
Best global response
Progressive disease: 6 (21.4)
Stable disease: 7 (25.0)
Partial response: 10 (35.7)
Complete response: 0
Unknown: 5 (17.8)
Reported toxicities
10 (35.7)
Grade of toxicity
1: 4 (16.0)
2: 2 (7.1)
3: 2 (7.1)
4: 1 (3.5)
Non-grade reported: 1 (3.5)
Treatment interruption due toxicity
3 (10.7)
Treatment dose-reduction
1 (3.5)
Third TKI treatment (n =9)
TKI
Erlotinib (retreatment): 2 (22.2)
Afatinib: 1 (11.1)
Gefitinib: 1 (11.1)
Osimertinib: 3 (33.3)
Brigatinib: 1 (11.1)
Lorlatinib: 1 (11.1)
Best CNS response in first line
Progressive disease: 3 (33.3)
Partial response: 2 (22.2)
Unknown: 4 (44.4)
Local CNS treatment (n = 60)
CNS Radiotherapy
34 (56.7)
CNS Radiotherapy type
Whole-brain radiotherapy (WBRT): 24 (40.0)
Stereotactic radiotherapy: 8 (13.3)
Both: 2 (3.3)
Reported toxicity
6 (10.0)
Best CNS response due to RT
Progressive disease: 11 (18.3)
Stable disease: 6 (10.0)
Partial response: 8 (13.3)
Complete response: 3 (5.0)
Unknown: 6 (10.0)
CNS surgery
2 (3.3)
Survival
Total TKI treatment time (months, 95% CI)
Mean: 33.3 (23.4-43.2)
Median: 27.0 (22.0-31.9)
Overall survival, (months, 95% CI)
Mean:
Global: 42.6 (28.6-56.6)
EGFR: 35.1 (24.7-45.5)
ALK: 64.3 (29.1-99.6)
Median:
Global: 31.0 (21.4-46.6)
EGFR: 29.0 (17.9-40.1)
ALK: 34.0 (21.4-46.6)
ConclusionTable-2. Patients treated with TKIs alone at the diagnosis of brain metastases and those treated with new generation TKIs Patients treated with TKI alone (n = 25)
Targetable driver mutation
EGFR: 22 (88.0)
ALK: 3 (12.0)
Radiotherapy at progression
6 (24.0)
Radiotherapy type
Whole-brain radiotherapy (WBRT): 5 (20.0)
Stereotactic radiotherapy: 1 (4.0)
Best CNS RT response
Progressive disease: 2 (8.0)
Partial response: 3 (12.0)
Unknown: 1 (4.0)
Radiotherapy-free survival (months, 95% CI)
Mean: 45.15 (28.85-61.51)
First TKI treatment (n = 25)
TKI
Erlotinib: 8 (32.0)
Afatinib: 4 (16.0)
Gefitinib: 5 (20.0)
Osimertinib: 5 (20.0)
Crizotinib: 1 (4.0)
Alectinib: 2 (8.0)
Best CNS response
Progressive disease: 6 (24.0)
Stable disease: 0
Partial response: 11 (44.4)
Complete response: 3 (12.0)
Unknown: 5 (20.0)
Best global response
Progressive disease: 3 (12.0)
Stable disease: 5 (20.0)
Partial response: 11 (44.0)
Complete response: 1 (4.0)
Unknown: 5 (20.0)
Second TKI treatment (n = 8)
TKI
Erlotinib: 1 (12.5)
Gefitinib: 1 (12.5)
Afatinib: 2 (25.0)
Osimertinib: 3 (37.4)
Alectinib: 1 (12.5)
Best CNS response
Progressive disease: 1 (12.5)
Stable disease: 1 (12.5)
Partial response: 1 (12.4)
Complete response: 0
Unknown: 5 (62.5)
Best global response
Progressive disease: 2 (25.0)
Stable disease: 0
Partial response: 5 (62.5)
Complete response: 0
Unknown: 1 (12.5)
Third TKI treatment (n = 4)
TKI
Erlotinib (retreatment): 1 (25.0)
Gefitinib: 1 (25.0)
Osimertinib: 1 (25.0)
Lorlatinib: 1 (25.0)
Best CNS response
Partial response: 1 (25.0)
Unknown: 3 (75.0)
Brain penetration TKI data (n = 28)
TKI included
Alectinib: 9 (32.1)
Brigatinib: 2 (7.1)
Ceritinib: 2 (7.1)
Lorlatinib: 1 (3.6)
Osimertinib: 14 (50.0)
Our study shows that deferring CNS RT in oncogene-driven NSCLC and CNS involvement is a valid option due to CNS metastases response to TKIs, especially to those that can penetrate the blood-brain barrier, in order to avoid side-effects derived from CNS radiation.