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Davide Franceschini
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P1.04 - Immuno-oncology (ID 164)
- Event: WCLC 2019
- Type: Poster Viewing in the Exhibit Hall
- Track: Immuno-oncology
- Presentations: 1
- Now Available
- Moderators:
- Coordinates: 9/08/2019, 09:45 - 18:00, Exhibit Hall
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P1.04-41 - Immunotherapy Concomitant to Radiotherapy: A Multicentric Retrospective Study on 179 Patients with Advanced Non-Small Cell Lung Cancer (Now Available) (ID 647)
09:45 - 18:00 | Author(s): Davide Franceschini
- Abstract
Background
Immunotherapy (IT) has enhanced the treatment armamentarium for aNSCLC. Radiobiological studies and initial clinical reports suggest a potential synergistic effect of radiotherapy (RT) and IT. Aim of the study is to investigate the safety of cytoreductive RT (palliative or ablative) delivered in association with Nivolumab (NIVO), Pembrolizumab (PEM) or Atezolizumab (ATE) in aNSCLC setting.
Method
We analyzed 179 consecutive pts affected by aNSCLC treated with a combination of RT and IT with NIVO/PEM or ATE from January 2015 to February 2019. One hundred eighteen patients were male and 61 female. Mean age was 65 (range 38-81). Adenocarcinoma was diagnosed in 101 of patients, while squamous cell carcinoma constituted 43.6% of our population. Eleven patients received IT as first line therapy, while the other 168 pts received at least a first line of systemic therapy before IT. One hundred thirty patients received NIVO, 42 PEM and 7 ATE. Concerning RT, 109 patients were treated before first cycle of IT (within 40 days), 49 pts during IT and the remaining 21 received RT immediately after the last IT session (within 40 days) due to disease progression (DP).
Result
After a mean follow up (FUP) of 24.1 months (range 3-142), 63/179 patients were still alive. During FUP 115 patients (62.4%) experienced DP after RT-IT. One and 3-year Overall Survival were 60.3%±3.8%SE and 26,7%±4,5%SE, respectively. RT was delivered in 96 cases to bone metastasis, in 49 to brain mts, in 11 to lung nodules, in 12 to lymph nodes, in 6 to surrenalic gland and in 5 pts to other sites. RT was delivered to 109 patients as a pure palliative treatment (8-36 Gy in 1-12 fractions), to 49 pts using stereotactic ablative doses (18-54 Gy in 1-5 fractions) and to 21 with high dose moderately-hypofractionated schedules(24-51 Gy in 3-17 fractions) . In 107 patients, RT was planned using a 3D conformal approach, while in 72 an inverse planning system was used (IMRT/VMAT/Tomotherapy). Mean number of IT administrations was 11 (2-58). No patient had an interrumption of systemic therapies during or after RT. Severe acute toxicities (Grade 3 by 4.0 CTCAE scale) were reported only in three cases because of the RT treatment: 1 case of radiodermitis and two lung toxicities. Known systemic side effects from IT were observed in 44 pts, 12 of whom with ≥G3 : 6 pneumonitis, 3 colitis, 2 thyroid toxicities, 1 oesophageal toxicity, 1 pt asthenia.
Conclusion
RT and IT with checkpoint inhibitor NIVO/PEM/ATE represent a safe, well tolerated and efficient multimodal treatment in aNSCLC, with the available data suggesting also potential, synergistic effects on local and systemic disease in aNSCLC pts even when non-radical RT doses are prescribed. Ongoing studies set out to understand the optimal timing, RT doses and ideal combination between RT and IT in aNSCLC.
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P2.17 - Treatment of Early Stage/Localized Disease (ID 189)
- Event: WCLC 2019
- Type: Poster Viewing in the Exhibit Hall
- Track: Treatment of Early Stage/Localized Disease
- Presentations: 1
- Now Available
- Moderators:
- Coordinates: 9/09/2019, 10:15 - 18:15, Exhibit Hall
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P2.17-20 - A Radiomic Approach to Predict Nodal and Distant Relapse in Patients Treated with Stereotactic Body Radiation Therapy for Early Stage NSCLC (Now Available) (ID 2178)
10:15 - 18:15 | Presenting Author(s): Davide Franceschini
- Abstract
Background
Regional and distant relapse remain a significant issue in the treatment of early stage non small cell lung cancer with Stereotactic Body Radiation Therapy (SBRT). There is a need for predictive biomarkers able to identify patients that are at higher risk of relapse. In this work we present a radiomic approach using features extracted by routine planning CT, to predict the risk of nodal and distant recurrence.
Method
A cohort of 102 patients was retrospectively investigated. All patients were affected by early stage (T1-T2) lung cancer and received the same radiation treatment with 48Gy delivered in 4 fractions. For all patients, a set of 45 radiomics textural features was computed for the tumor volumes segmented on the treatment planning CT images. Patients were split into two independent cohorts used for training (70% of cases) and validation (30% of cases). A stepwise backward linear discriminant analysis (LDA) was applied as a classifier to identify patients at risk of lymph-nodal progression. The performance of the model was assessed by means of standard metrics derived from the confusion matrix. Furthermore, all textural features were correlated to survival data to build predictive models: the features/predictors found significant at univariate analysis and to elastic net regularization, were included in a multivariate model to predict disease specific progression free survival (PFS) and disease specific survival (DS OS). Low and high risk groups were identified by maximizing the separation by means of the Youden method.
Result
In the total cohort (77 (75.5%) males and 25 (24.5%) females, median age 76.6 years), 15 patients presented nodal progression at the time of analysis (11 in the training and 4 in the validation sets); 19 patients (18.6%) died because of disease specific causes, 25 (24.5%) died for other reasons, 28 (27.5%) were alive without disease and 30 (29.4%) with either local or distant progression. The mean tumor volume was 5.6±6.4cm3. Figure 1 illustrates the actuarial curves for PFS and DS OS over the entire training and test cohorts (in both cases the difference was not significant) and the same data stratified in low and high risk groups identified. In all case highly significant differences were identified.
Conclusion
Radiomics features extracted from treatment planning CT images can distinguish patients with low and high risk of tumor progression and disease specific death in early stage lung cancer treated with SBRT.
