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Fabio Franco
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EP1.14 - Targeted Therapy (ID 204)
- Event: WCLC 2019
- Type: E-Poster Viewing in the Exhibit Hall
- Track: Targeted Therapy
- Presentations: 1
- Now Available
- Moderators:
- Coordinates: 9/08/2019, 08:00 - 18:00, Exhibit Hall
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EP1.14-11 - Real-Life Data of Osimertinib in Pretreated Patients with Advanced Non-Small Cell Lung Cancer Harboring EGFR T790M Mutation (Now Available) (ID 697)
08:00 - 18:00 | Author(s): Fabio Franco
- Abstract
Background
Several clinical trials have demonstrated the efficacy and safety of osimertinib in pretreated patients with advanced non-small cell lung cancer (NSCLC) harbouring EGFR T790M resistance mutation. However, clinical real-world data on patient characteristics and efficacy of the drug is limited.
Method
We reviewed the medical records of T790M mutation-positive lung cancer patients treated with osimertinib between May 2016 and February 2019 in our institution. We calculated progression-free survival (PFS) and overall survival (OS) from osimertinib initiation.
Result
The study included 22 patients with a mean age of 59.6 years. 59% (13/22) were female and 100% had adenocarcinoma histology. We had an unusual high frequency of tobacco use in our series as 40.9% (9/22) of our patients were smokers (3/22) o former-smokers (6/22), with a mean of 35 pack-year (sd, 28.5). 45.5% (10/22) had exon 21 L858R mutations, whereas 54.5% (12/22) harboured exon 19 deletions (19del). One patient simultaneously had an exón 19 deletion and exon 20 S768I mutation. Osimertinib was used in second, third and fourth line in 50% (11/22), 27% (6/22) and 23% (5/22) of patients, respectively.
All patients had liquid biopsy blood samples obtained prior to the start of the treatment, and T790M mutation could be detected in 86.4% (19/22), with a mean mutant-allele fraction of 4,11% (standard deviation 8.65, min 0, max 37.7). T790M was detected only in tissue in 2 patients and exclusively in cerebrospinal fluid in 1 of them.
At the time of starting osimertinib, patients had a median of 3 metastatic sites (min 1, max 6), being the most frequent locations the lung (73%), the bone (64%), the pleura (59%), the central nervous system (23%) and the peritoneum (14%).
Median follow-up duration was 10 months (IQR, 4.7-22.67). To the date, 63% (14/22) have experienced progression of the disease. Median PFS in our series was 8.9 (95% CI, 4.9-17.9 ) months, whereas median OS since osimertinib initiation was 18.2 (95% CI, 8.8-NE) months.
Regarding to toxicity, 12 patients referred adverse events, 82.6% of which were mild (G1), being the most frequent toxicities neutropenia (9%), diarrhoea (9%), hypertransaminasemia (9%) and asthenia (9%). Only 1 G3 event was recorded (asymptomatic hyperamilasemia).
Conclusion
The efficacy of osimertinib in real-world practice was similar the observed in clinical trials, with a favourable adverse effect profile. Liquid biopsy is an effective non-invasive method to assess the presence of the T790M resistance mutation prior to the start of osimertinib.
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MA16 - Prioritizing Use of Technology to Improve Survival of Lung Cancer Subgroups and Outcomes with Chemotherapy and Surgery (ID 142)
- Event: WCLC 2019
- Type: Mini Oral Session
- Track: Treatment in the Real World - Support, Survivorship, Systems Research
- Presentations: 1
- Now Available
- Moderators:Jair Bar, Navneet Singh
- Coordinates: 9/09/2019, 15:45 - 17:15, Interlaken (1988)
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MA16.03 - Big Data Analysis for Personalized Medicine in Lung Cancer Patients (Now Available) (ID 2532)
15:45 - 17:15 | Author(s): Fabio Franco
- Abstract
- Presentation
Background
The use of Big Data in healthcare is in its early days, and most of the potential for value creation remains unclaimed.
Electronic Health Records (EHR) contain a large amount of information about the patient's condition, which can potentially revolutionize the clinical practice, such information is seldom considered due to the complexity of its extraction and analysis. We report on a first integration of an NLP framework for the analysis of clinical records of lung cancer in Puerta de Hierro University Hospital (HUPHM).
Method
A cohort of 1000 patients diagnosed of non-small cell lung cancer (NSCLC) from 2009 to 2018 at HUPHM were included in this observational study. Unstructured clinical data were obtained from the EHR. The semantic indexing and the information analysis was performed by the Politecnica University of Madrid, using Big Data and machine learning techniques. Clinical notes were converted into usable data, and combined with genomic data, images and bibliography, such as PubMed or Drugbank.
Result
A total of 251.730 documents were analyzed (240.851 notes and 10.879 reports). These heterogeneous sources of information were analyzed and integrated in an interactive user interface (Figure 1). As a result, all this large amounts of data turns into actionable and exploitable information for clinicians and authorities for planning public health policies and also create new clinical trials.
The interactive platform will allow the clinician obtain immediate and personalized information of each patient and will elaborate predictive models for long survivors, identify risk patients, reduce overtreatments, etc.
Conclusion
By using Big Data we will be able to exploit large amounts of clinical information and combine them with multiple databases developing interactive user interface, increasing lung cancer knowledge and directing medicine towards a more personalized one.
This work was supported by the EU H2020 programme, under grant agreement Nº 727658 ( Project iASiS).
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P2.03 - Biology (ID 162)
- Event: WCLC 2019
- Type: Poster Viewing in the Exhibit Hall
- Track: Biology
- Presentations: 1
- Moderators:
- Coordinates: 9/09/2019, 10:15 - 18:15, Exhibit Hall
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P2.03-33 - ctDNA Levels Significantly Predicts Survival in NSCLC Patients with an EGFR Activating Mutation (ID 2016)
10:15 - 18:15 | Author(s): Fabio Franco
- Abstract
Background
Circulating tumor DNA (ctDNA) have been shown to be useful for non-invasive biomarker testing in non-small cell lung cancer (NSCLC). In addition, there is growing evidence supporting that ctDNA levels can be useful for tumor response to treatment monitoring. Nevertheless, data from large prospective clinical longitudinal studies still limited.
Method
300 plasma samples from 100 advanced NSCLC patients, with tumors harboring an EGFR activating mutation and treated with a first line tyrosine Kinase inhibitor were analyzed. Samples were collected before the start of treatment, at first follow up evaluation, at 7 month and at disease progression. ctDNA was analyzed by dPCR.
Result
Median follow up was 11.3 months. There were not significant differences in progression free survival (PFS) or overall survival (OS) according to treatment (erlotinib, afatinib or gefitinib). Patients harboring a deletion in exon 19 or a mutation in exon 21 exhibited better survival than those with an insertion in exon 20 (P<0.001). dPCR detected EGFR sensitizing mutation in 77% of the pre-treatment samples. ctDNA levels before the start of the treatment did not significantly predict survival, although a tendency was observed, with patients with high levels of ctDNA showing poorer outcome. On the contrary, patients in which the EGFR sensitizing mutation was undetectable at first follow up had a markedly better PFS and OS (HR=2.7; 95IC= 1.4-5.5 and HR= 5.5 95IC: 1.8-17 respectively). In the same way, patients in which the EGFR sensitizing mutation remained negative at 7months had a significantly increased PFS (HR: 2.8; 95IC: 1.2-6.6). None of the patients with undetectable levels at 7 months has deceased.
Conclusion
ctDNA levels is of prognostic significance in EGFR positive NSCLC patients with advance disease and can be useful to monitor treatment outcome
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P2.05 - Interventional Diagnostic/Pulmonology (ID 168)
- Event: WCLC 2019
- Type: Poster Viewing in the Exhibit Hall
- Track: Interventional Diagnostics/Pulmonology
- Presentations: 1
- Moderators:
- Coordinates: 9/09/2019, 10:15 - 18:15, Exhibit Hall
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P2.05-10 - Liquid Biopsy: Association Between the Burden of Disease in Patients with EGFR-Mutated NSCLC and the Frequency of Its Detection in Blood (ID 2384)
10:15 - 18:15 | Author(s): Fabio Franco
- Abstract
Background
In the management of patient’s whit non small cell lung cancer (NSCLC) with EGFR mutations after progression to first and second generation tyrosine kinasa inhibitors (TKI), the mechanism of resistance is very important. Our objective is to analyse the appearance kinetics of the T790M by means of digital PCR techniques in liquid biopsy.
Method
We conducted a multicenter study with 100 patients with EGFR-mutated NSCLC, treated with first-line TKI therapy. We analyze the ctDNA by dPCR before the start of treatment, at first follow up evaluation, at 6 months and at disease progression.
Result
We included a total of 100 patients from July 2016 to December of 2017. Seven patients with Exon 20 insertion in EGFR were excluded (final sample 93). The median of follow-up was 12 months. There were not significant differences in progression free survival (PFS) or overall survival (OS) according to treatment (erlotinib, gefitinib or afatinib). dPCR detected EGFR sensitizing mutation in 77% of the pre-treatment samples. Of these cases, EGFR sensitizing mutation was detected in 75% of the patients with stage IVA and 85% in stage IVB respectively, p=0,075. The resistance mutation p.T790M was detected in 52% of the samples collected at disease progression. The probability to detect the resistance mutation p.T790M by liquid biopsy, is greater if the pre-treatment sample was positive for EGFR sensitizing mutation (11% vs 62%) p 0,009. In cases with progression of the disease the percent of detection of p.T790M was 52% and 54% in patients with Exon 19 deletion and L858R mutation respectively. The OS in patients with progression of the disease and p.T790M negative was 85% at 12 months (95%CI: 60%-94%) and 75% with p.T790M positive (95%CI: 49%-88%), p=0,01.
Conclusion
The burden of disease in patients with NSCLC mutated with EGFR is related to the appearance of sensitivity and resistance mutations in liquid biopsy. The probability to detect the resistance mutation p.T790M in blood, is greater if the pre-treatment sample was positive for EGFR sensitizing mutation.
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P2.10 - Prevention and Tobacco Control (ID 176)
- Event: WCLC 2019
- Type: Poster Viewing in the Exhibit Hall
- Track: Prevention and Tobacco Control
- Presentations: 1
- Moderators:
- Coordinates: 9/09/2019, 10:15 - 18:15, Exhibit Hall
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P2.10-02 - Smoking Habit in Lung Cancer in Spain (ID 732)
10:15 - 18:15 | Author(s): Fabio Franco
- Abstract
Background
Tobacco is the leading cause of lung cancer. The fight against the smoking habit is essential and should be continuous, to detect the national situation that makes it possible to design health care policies against this consumption. To do so, the Grupo Español de Cáncer de Pulmón (Spanish Lung Cancer Group) made this analysis within the context of the Thoracic Tumor Registry (TTR).
Method
The TTR is an observational cohort multicenter study in Spain. The study is conducted according to the Declaration of Helsinki and approved by the institutional review board of each participating site. The registry was approved by the Spanish Drug Agency, as a non-post-authorization, non-interventional study.
Result
We collected data from 6,600 patients diagnosed of lung cancer from 58 different Spanish hospital sites.
A total of 3,039 patients were former smokers (46%), 2,611 were active smokers (39%) and only 866 (12%) patients stated to be non-smokers; the status in 2% is unknown. If we make a comparison by gender regarding the presence of this habit, large differences (p-valor < 0.001) are observed, with a greater number of non-smokers in women (37 % vs. 4.5% in males), while the percentage of former smokers is much higher in the males (53.4% vs. 27.9% in women) and a minor difference in active smokers (42.1% vs. 34.4% in women).
Significant differences were observed in the study on the distribution of the smoking habit by gender and year of diagnosis. An increase is also observed in the last two years regarding the percentage of patients who were active smoked, both for the total population as well as for each one of the two genders separately. The increase is greater among the women and, also, the number of women who are active smokers is greater in recent years.
Mean age of onset of the smoking habit is 18.2 years. Significant differences are observed between both genders (p-valor < 0.001), with a mean age of initiation of 17.9 years in the men (95%CI 17.6-18.2 years) and 19.2 years in the women (95%CI 18.5-19.8 years). Significant differences between Regional Communities were also found in the mean age at onset of the habit, with much lower levels in the Valencian Community (16.6 years) or Navarra (16.9 years) regarding other communities, such as the Region of Murcia (22.9 years) or the Balearic Islands (21.6 years)
Conclusion
Lung cancer in Spain is associated to tobacco consumption in 85% of the cases diagnosed. Consumption has shown an increase in both genders in recent years and is especially rapid and worrisome in women. Anti-smoking campaigns should be reactivated and the causes of the regional differences analyzed in depth
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P2.16 - Treatment in the Real World - Support, Survivorship, Systems Research (ID 187)
- Event: WCLC 2019
- Type: Poster Viewing in the Exhibit Hall
- Track: Treatment in the Real World - Support, Survivorship, Systems Research
- Presentations: 1
- Moderators:
- Coordinates: 9/09/2019, 10:15 - 18:15, Exhibit Hall
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P2.16-20 - Big Data and Survival Predictors in Lung Cancer Patients (ID 1943)
10:15 - 18:15 | Author(s): Fabio Franco
- Abstract
Background
Lung cancer is the most common and fatal one (18% of all cancer deaths). Parameters which imply better survival are still unknown.
The objective of this project is to turn the large amount of data from each patient into exploitable information.
Method
Between 2008-2019, 935 non-small cell lung cancer patients from our hospital were enrolled in an observational study.
Unstructured data was obtained from the patient Electronic Health Records.
Politecnica University from Madrid made the information analysis using Big Data and machine learning techniques.
Result
A total of 251.730 documents have been analyzed from 935 patients, 54% in stage IV.
EGFR/ALK mutation was found in 9%, showing better OS than non-mutated (23.5 months vs 12 months, log-rank p=0.016). Survival curves are shown in figure 1.
In a multivariate analysis (table 1), independent predictors of mortality were male sex, squamous histology and PS status. Additionally, independent predictors of survival were receiving immunotherapy, surgery treatment or developing endocrine toxicities.
Conclusion
Big data is a very useful tool to exploit a large amount of lung cancer data, increasing knowledge about these disease and allowing the development of survival predictive models.
This work was supported by the EU H2020 programme, under grant agreement Nº 727658 (Project iASiS).
