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Jose Carlos Benitez
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FP09 - Screening and Early Detection (ID 175)
- Event: WCLC 2020
- Type: Posters (Featured)
- Track: Screening and Early Detection
- Presentations: 1
- Moderators:
- Coordinates: 1/28/2021, 00:00 - 00:00, ePoster Hall
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FP09.05 - Driver Oncogenic Alterations and Indoor Radon in NSCLC Patients From the IFCT Biomarker Cohort: Bioradon France Study (ID 1176)
00:00 - 00:00 | Author(s): Jose Carlos Benitez
- Abstract
Introduction
Radon is a radioactive gas, considered as the leading cause of lung cancer in non-smokers. In a previous work, we studied the correlation between the estimation of radon concentration from the French Indoor Radon Map (Institut de Radioprotection et de Sûreté Nucléaire, IRSN) and the regional prevalence of driver alterations in a cohort of 116.424 NSCLC patients in France (Mezquita et al, WCLC 2018). The prevalence of driver oncogene alterations was significantly higher in high-radon areas but clinical data were not available. We aim to confirm this hypothesis in an annotated database of NSCLC patients with matched molecular data available for adjustment (Barlesi et al, Lancet 2016).
Methods
Retrospective assessment of patients with NSCLC tested for EGFR/BRAF/HER2/KRAS mutations (m) and ALK fusion from the 28 Platform led by the National Cancer Institute between Apr.2012 and Apr.2013, and included in the Biomarkers France dataset. We studied the association between the prevalence of driver oncogenic alterations (EGFR/ALK/BRAF/HER2/KRAS) and the radon mean concentration in the area where the patient was born according to the IRSN Map. Adjustment on age, gender and smoking was performed.
Results
Out of 17664 patients, we analyzed 3994 with birthplace available: 63% males, 82% smokers, with a median age of 64 years [18-94]. Lung cancer tumors were mostly adenocarcinoma (76%), followed by other histologies (18%) and squamous (6%). By molecular alterations: 468 tumors harbor EGFRm (12%), 129 ALK (3%), 89 BRAFm (2%), 32 HER2m (1%), 985 KRASm (25%); 2273 wildtype or harbor other non-driver alterations (control; 57%). Adenocarcinoma histology (83.7% vs. 80.2%, p=0.0034), and non-smoker habit (19.5% vs. 16.5%, p=0.0251) were more common in radon high-risk group (comparatively at the low risk group). The mean radon concentration by birthplace was 74.36 Bq/m3 ±53.28SD [range 16.6-622.3], and by molecular groups: EGFRm 72.49 Bq/m3 ± 47.98 SD [16.6-461.4], ALK 80.24 Bq/m3 ±55.22SD [19.3-384.7], BRAFm 73.22 Bq/m3 ±47.86SD [19.3-319.3], HER2m 72.74 Bq/m3 ±39.51SD Bq/m3 [27.8-231.3], KRASm 71.79 Bq/m3 ±53.32SD [16.6-576.8] and control group 75.67 Bq/m3 ± 54.5SD [16.6-622.3] (p=0.20). The prevalence of driver alterations was higher in high-radon areas (table 1; p=0.0472); but no significant difference was observed after adjustment on age, gender and smoking.
ConclusionLow radon
<50 Bq/m3High radon
≥50 Bq/m3P value
P value adjusted*
EGFR
Mutation
N (%)
155 (11.4%)
313 (13.2%)
0.1218
0.3024
Control (1)
N (%)
1199 (88.6)
2059 (86.8)
ALK
Fusion
N (%)
42 (3.4%)
87 (4.1%)
0.3272
0.4708
Control (1)
N (%)
1199 (96.6)
2059 (95.9)
BRAF
Mutation
N (%)
32 (2.6%)
57 (2.7%)
0.8708
0.9865
Control (1)
N (%)
1199 (97.4)
2059 (97.3)
HER2
Mutation
N (%)
7 (0.6%)
25 (1.2%)
0.0880
0.1781
Control (1)
N (%)
1199 (99.4)
2059 (98.8)
KRAS
Mutation
N (%)
375 (31.3%)
610 (29.6%)
0.3227
0.3478
Control (2)
N (%)
824 (68.7)
1449 (70.4)
DRIVER
Positive
N (%)
236 (16.4%)
482 (19%)
0.0472
0.2128
Control (1)
N (%)
1199 (83.6)
2059 (81)
(1) population no EGFRm, noBRAFm, no HER2m and no ALKr
(2) population no EGFRm, noBRAFm, no HER2m, no ALKr and no KRASm
*adjustment on age, gender and smoking
We observed a higher prevalence of driver oncogenic alterations in NSCLC patients born in high radon areas; but no significant difference was observed after adjustment on age, gender and smoker. This study warrants further research on radon gas and driver oncogenes.
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MA08 - Advances in Biomarkers for Immune Checkpoint Blockade and Targeted Therapy in Non Small Cell Lung Carcinoma (ID 166)
- Event: WCLC 2020
- Type: Mini Oral
- Track: Pathology, Molecular Pathology and Diagnostic Biomarkers
- Presentations: 1
- Moderators:
- Coordinates: 1/30/2021, 16:45 - 17:45, Scientific Program Auditorium
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MA08.04 - LIPI and Outcomes of Durvalumab as Consolidation Therapy after ChRT in Patients with Locally-Advanced NSCLC (ID 1969)
16:45 - 17:45 | Author(s): Jose Carlos Benitez
- Abstract
- Presentation
Introduction
The lung immune prognostic index (LIPI), which combines pretreatment derived neutrophils/[leukocytes minus neutrophils] ratio (dNLR) >3 and lactate dehydrogenase (LDH) > upper limit of normal (ULN), is associated with outcomes in advanced non-small cell lung cancer (NSCLC) patients treated with immune checkpoint inhibitors (ICI). We aimed to assess whether pretreatment LIPI correlates with durvalumab efficacy after concurrent chemoradiotherapy in the locally advanced setting.
Methods
Multicenter retrospective study of locally advanced NSCLC patients treated with durvalumab consolidation in 21 European/US centers from 12/2015 to 5/2020. Clinical and biological data were collected before durvalumab treatment. PD-L1 expression by immunohistochemistry was also collected at diagnosis. LIPI was calculated according to previous reports and three groups were characterized: good (dNLR≤3+LDH≤ULN), intermediate (dNLR>3 or LDH>ULN) and poor (dNLR>3+LDH>ULN). The primary endpoint was progression-free survival (PFS). Response was assessed according to the clinical routine of each center.
Results
A total of 267 patients were enrolled. One hundred eighty-five (69%) patients were male, 252 (94%) smokers, with median age of 67 [range 59-73] and 223 (98%) with Eastern Cooperative Oncology Group (ECOG) performance status (PS) ≤1. 260/266 (98%) were stage III, of which 96 were IIIA, 127 stage IIIB and 37 stage IIIC. 163 (63%) had non-squamous histology and 12/131 (27%) harbored driver alterations: 5 EGFR, 4 BRAF, 3 MET, 2 ALK; missing in 136 cases. PD-L1 was ≥1% in 191/233 (82%) patients both from Europe and US, missing in 34 cases. LIPI was evaluable in 143 patients: 90 were considered good (63%), 50 intermediate (35%) and 3 (2%) as poor LIPI group. dNLR >3 was found in 47/218 (22%) and LDH > ULN in 23/143 (16%) cases. Radiotherapy was delivered concurrent in 219 (82%) of cases. No differences in clinical characteristics were found between 3 LIPI groups, including the response to previous chemoradiotherapy.
With a median follow-up of 13.4 months [95% confidence interval (CI), 12-15], the median PFS was 20 months [95% CI, 12.7-not reached (NR)]. Median PFS was 7.5 months [95% CI, 3.1-NR] for poor group vs. 10.7 months [95% CI, 5.1-NR] for intermediate group vs. 19.1 months [95% CI, 11.6-NR] for good LIPI group (P=0.020). Median overall survival (OS) was NR [95% CI 47-NR] in the entire cohort and therefore considered not mature. The first objective response rate under durvalumab was 44% (111/251), being 36% (18/50) for the intermediate-poor group and 38% (33/87) for the good group with no significant differences (P=0.099). No differences in PFS and OS between groups were found regarding PD-L1 status (P=0.5 and P=0.4, respectively).
Conclusion
Pretreatment LIPI is associated with clinical outcomes in locally advanced patients treated with durvalumab as consolidation after chemoradiotherapy. This cohort is still ongoing to confirm our preliminary findings in a larger cohort.
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P33 - Pathology - Immunotherapy Biomarker (ID 101)
- Event: WCLC 2020
- Type: Posters
- Track: Pathology, Molecular Pathology and Diagnostic Biomarkers
- Presentations: 1
- Moderators:
- Coordinates: 1/28/2021, 00:00 - 00:00, ePoster Hall
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P33.10 - Identification of Long-Responders and Fast-Progressors under Immunotherapy Based on Early Monitoring of dNLR in Advanced NSCLC Patients (ID 2519)
00:00 - 00:00 | Author(s): Jose Carlos Benitez
- Abstract
Introduction
The dNLR score, based on [neutrophil/(leucocytes-neutrophils)] ratio (dNLR) at baseline (B) and before 2nd cycle (C2), has been correlated with immune checkpoint inhibitors (ICI) outcomes in NSCLC patients. We aimed to assess whether dNLR score can identify the different response phenotypes to ICI in NSCLC, particularly the fast-progressors (FP) and long-responders (LR) under ICI.
Methods
Advanced NSCLC patients receiving ICI between Nov.12 and Jan.19, were enrolled in Gustave Roussy. dNLR was retrospectively collected at B and C2. Patients were categorized as low vs. high-dNLR at each time-point (defined as ≤3 or >3), and the change between B and C2 (good = low at both time-points, poor = high at both time-points, mixed = different at each time-point). Response types were evaluated: a) “responder” (objective response (ORR) and progression-free survival (PFS) >6 months (mo.)), b) “LR” (ORR + PFS >12 mo. and median overall survival (OS) >24 mo.), c) “standard-progressor" (PD) (progressive disease as best response; not including FP) and d) “FP” (defined as early death within the 1st 12 weeks).
Results
469 patients were included: 65% males, 90% smokers, median age of 63, 75% performance status ≤1; adenocarcinoma histology in 66% and 12% harboring driver alterations. PD-L1 was ≥1% in 143/259 (55%), missing in 210 patients. The ORR was 19% (80/431); 15% were LR, 35% standard-PD and 13% FP. Overall, the median OS was 10.0 mo. [95% CI, 8.2-12.2]; 45.2 mo. [95% CI, 31.9-not reached] in LR, 4.2 mo. [95% CI, 3.2-5.7] in PD and 0.7 mo. [95% CI, 0.6-0.9] in FP population. dNLR (B) was high in 41% of FP vs. 44% of standard-PD vs. 27% of LR (P<0.001). dNLR (C2) was high in 81% of FP vs. 45% of PD vs. 14% of LR (P<0.001). Response phenotypes were strongly correlated with the dNLR score subgroups (table 1).
Overall
N=291
Long-responder
N=48
Responder
N=108
Standard progressor
N=116
Fast-progressor
N=16
P value Good 151 (52%) 32 (67%) 65 (60%) 52 (45%) 2 (13%) <0.001 Intermediate 71 (24%) 13 (27%) 24 (22%) 30 (26%) 3 (19%) <0.001 Poor 69 (24%) 3 (6%) 19 (18%) 34 (29%) 11 (69%) <0.001
Conclusion
The dNLR score, especially at C2, is an accessible and simple tool that can add information to radiological examination discriminating the different phenotypes of response under ICI, particularly aggressive patterns such as FP.
