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Objective: Surgical treatment of locally advanced non-small cell lung cancer including single or multilevel N2 remains a matter of debate. Several trials demonstrate that selected patients benefit from surgery if R0 resection is achieved. We aimed to assess resectability and outcome of patients with locally advanced clinical T3/T4 (American Joint Committee on Cancer 8 th edition) tumors after induction treatment followed by surgery in a pooled analysis of 3 prospective multicenter trials., Methods: A total of 197 patients with T3/T4 non-small cell lung cancer of 368 patients with stage III non-small cell lung cancer enrolled in the Swiss Group for Clinical Cancer Research 16/96, 16/00, 16/01 trials were treated with induction chemotherapy or chemoradiation therapy followed by surgery, including extended resections. Univariable and multivariable analyses were applied for analysis of outcome parameters., Results: Patients' median age was 60 years, and 67% were male. A total of 38 of 197 patients were not resected for technical (81%) or medical (19%) reasons. A total of 159 resections including 36 extended resections were performed with an 80% R0 and 13.2% pathological complete response rate. The 30- and 90-day mortality were 3% and 7%, respectively, without a difference for extended resections. Morbidity was 32% with the majority (70%) of minor grading complications. The 3-, 5-, and 10-year overall survivals for extended resections were 61% (95% confidence interval, 43-75), 44% (95% confidence interval, 27-59), and 29.5% (95% confidence interval, 13-48), respectively. R0 resection was associated with improved overall survival (hazard ratio, 0.41; P < .001), but pretreatment N2 extension (177/197) showed no impact on overall survival., Conclusions: Surgery after induction treatment for advanced T3/T4 stage including single and multiple pretreatment N2 disease resulted in 80% R0 resection rate and 7% 90-day mortality. Favorable overall survival for extended and not extended resection was demonstrated to be independent of pretreatment N status., (Copyright © 2022 The American Association for Thoracic Surgery. Published by Elsevier Inc. All rights reserved.)

Background: Chemoradiotherapy with durvalumab consolidation has yielded excellent results in stage III non-small-cell lung cancer (NSCLC). Therefore, it is essential to identify patients who might benefit from a surgical approach., Material and Methods: Data from 437 patients with operable stage III NSCLC enrolled in four consecutive Swiss Group for Clinical Cancer Research (SAKK) trials (16/96, 16/00, 16/01, 16/08) were pooled and outcomes were analyzed in 431 eligible patients. All patients were treated with three cycles of induction chemotherapy (cisplatin/docetaxel), followed in some patients by neoadjuvant radiotherapy (44 Gy, 22 fractions) (16/00, 16/01, 16/08) and cetuximab (16/08)., Results: With a median follow-up time of 9.3 years (range 8.5-10.3 years), 5- and 10-year overall survival (OS) rates were 37% and 25%, respectively. Overall, 342 patients (79%) underwent tumor resection, with a complete resection (R0) rate of 80%. Patients (n = 272, 63%) with R0 had significantly longer OS compared to patients who had surgery but incomplete resection (64.8 versus 19.2 months, P < 0.001). OS for patients who achieved pathological complete remission (pCR) (n = 66, 15%) was significantly better compared to resected patients without pCR (86.5 versus 37.0 months, P = 0.003). For patients with pCR, the 5- and 10-year event-free survival and OS rates were 45.7% [95% confidence interval (CI) 32.8% to 57.7%] and 28.1% (95% CI 15.2% to 42.6%), and 58.2% (95% CI 45.2% to 69.2%) and 45.0% (95% CI 31.5% to 57.6%), respectively., Conclusion: We report favorable long-term outcomes in patients with operable stage III NSCLC treated with neoadjuvant chemotherapy with cisplatin and docetaxel ± neoadjuvant sequential radiotherapy from four prospective SAKK trials. Almost two-third of the patients underwent complete resection after neoadjuvant therapy. We confirm R0 resection and pCR as important predictors of outcome., Competing Interests: Disclosure DK: consulting or advisory role: AstraZeneca (AZ) (fee to institution). IO: grants (all fees to institution): Roche, Medtronic; honoraria (all fees to speakers bureau): AZ, Roche; advisory role: AZ, Merck, Sharp, and Dohme (MSD). WW: honoraria, consulting or advisory role, travel/accommodations: AZ, Medtronic. SIR: honoraria, consulting or advisory role (all fees to institution): AbbVie, Amgen, AZ, Boehringer Ingelheim, Bristol-Myers Squibb (BMS), Eli Lilly, Eisai, Janssen, MSD, Merck Serono, Novartis, PharmaMar, Pfizer, Roche, Takeda; travel/accommodations: Boehringer Ingelheim, BMS, Roche; Research support: AZ, Roche. AA: consulting or advisory role: AZ, Astella, BMS, MSD, Novartis, Roche; honoraria: AZ, Eli Lilly, Novartis. MM: consulting or advisory role: AZ (institution), BMS, Janssen, MSD, Roche. SP (all fees to institution): consulting or advisory role: AbbVie, Amgen, AZ, Bayer, Beigene, Biocartis, Boehringer Ingelheim, BMS, Clovis, Daiichi Sankyo, Debiopharm, ecancer, Eli Lilly, Elsevier, Fishawack, Foundation Medicine, Illumina, Imedex, IQVIA, Incyte, Janssen, Medscape, MSD, Merck Serono, Merrimack, Novartis, OncologyEducation, PharmaMar, Phosplatin Therapeutics, PER, Pfizer, PRIME, Regeneron, RMEI, Roche/Genentech, RTP, Sanofi, Seattle Genetics, Takeda, Talk: AZ, Boehringer Ingelheim, BMS, ecancer, Eli Lilly, Illumina, Imedex, Medscape, MSD, Novartis, PER, Pfizer, Prime, Roche/Genentech, RTP, Sanofi, Takeda; Grants/research support: Amgen, AZ, Biodesix, Boehringer Ingelheim, BMS, Clovis, GSK, Illumina, Lilly, MSD, Merck Serono, Mirati, Novartis, and Pfizer, Phosplatin Therapeutics, Roche/Genentech. MP: honoraria: Bayer, Janssen, Nestle; consulting or advisory role: AbbVie, Amgen, AZ, Bayer, Boehringer Ingelheim, BMS, Eisei, Janssen, MSD, Merck Serono, Nestle, Novartis, Pfizer, Roche, Sanofi, Takeda; travel/accommodations: AZ, Boehringer Ingelheim, BMS, Roche, Takeda, Vifor. MF: grants (all to institution): AZ, BMS; consulting or advisory role: AZ, Boehringer Ingelheim, BMS, MSD, Pfizer, Roche, Takeda; travel/accommodations: Merck Serono. All other authors have declared no conflicts of interest., (Copyright © 2022 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

The anatomical location and extent of primary lung tumors have shown prognostic value for overall survival (OS). However, its manual assessment is prone to interobserver variability. This study aims to use data driven identification of image characteristics for OS in locally advanced non-small cell lung cancer (NSCLC) patients. Five stage IIIA/IIIB NSCLC patient cohorts were retrospectively collected. Patients were treated either with radiochemotherapy (RCT): RCT1* (n = 107), RCT2 (n = 95), RCT3 (n = 37) or with surgery combined with radiotherapy or chemotherapy: S1* (n = 135), S2 (n = 55). Based on a deformable image registration (MIM Vista, 6.9.2.), an in-house developed software transferred each primary tumor to the CT scan of a reference patient while maintaining the original tumor shape. A frequency-weighted cumulative status map was created for both exploratory cohorts (indicated with an asterisk), where the spatial extent of the tumor was uni-labeled with 2 years OS. For the exploratory cohorts, a permutation test with random assignment of patient status was performed to identify regions with statistically significant worse OS, referred to as decreased survival areas (DSA). The minimal Euclidean distance between primary tumor to DSA was extracted from the independent cohorts (negative distance in case of overlap). To account for the tumor volume, the distance was scaled with the radius of the volume-equivalent sphere. For the S1 cohort, DSA were located at the right main bronchus whereas for the RCT1 cohort they further extended in cranio-caudal direction. In the independent cohorts, the model based on distance to DSA achieved performance: AUC RCT2 [95% CI] = 0.67 [0.55-0.78] and AUC RCT3  = 0.59 [0.39-0.79] for RCT patients, but showed bad performance for surgery cohort (AUC S2  = 0.52 [0.30-0.74]). Shorter distance to DSA was associated with worse outcome (p = 0.0074). In conclusion, this explanatory analysis quantifies the value of primary tumor location for OS prediction based on cumulative status maps. Shorter distance of primary tumor to a high-risk region was associated with worse prognosis in the RCT cohort., (© 2021. The Author(s).)

Purpose: For patients with resectable stage IIIA(N2) non-small-cell lung cancer, neoadjuvant chemotherapy with cisplatin and docetaxel followed by surgery resulted in a 1-year event-free survival (EFS) rate of 48% in the SAKK 16/00 trial and is an accepted standard of care. We investigated the additional benefit of perioperative treatment with durvalumab., Methods: Neoadjuvant treatment consisted of three cycles of cisplatin 100 mg/m 2 and docetaxel 85 mg/m 2 once every 3 weeks followed by two doses of durvalumab 750 mg once every 2 weeks. Durvalumab was continued for 1 year after surgery. The primary end point was 1-year EFS. The hypothesis for statistical considerations was an improvement of 1-year EFS from 48% to 65%., Results: Sixty-eight patients were enrolled, 67 were included in the full analysis set. Radiographic response rate was 43% (95% CI, 31 to 56) after neoadjuvant chemotherapy and 58% (95% CI, 45 to 71) after sequential neoadjuvant immunotherapy. Fifty-five patients were resected, of which 34 (62%) achieved a major pathologic response (MPR; ≤ 10% viable tumor cells) and 10 (18%) among them a complete pathologic response. Postoperative nodal downstaging (ypN0-1) was observed in 37 patients (67%). Fifty-one (93%) resected patients had an R0 resection. There was no significant effect of pretreatment PD-L1 expression on MPR or nodal downstaging. The 1-year EFS rate was 73% (two-sided 90% CI, 63 to 82). Median EFS and overall survival were not reached after 28.6 months of median follow-up. Fifty-nine (88%) patients had an adverse event grade ≥ 3 including two fatal adverse events that were judged not to be treatment-related., Conclusion: The addition of perioperative durvalumab to neoadjuvant chemotherapy in patients with stage IIIA(N2) non-small-cell lung cancer is safe and exceeds historical data of chemotherapy alone with a high MPR and an encouraging 1-year EFS rate of 73%., Competing Interests: Sacha I. RothschildConsulting or Advisory Role: Bristol Myers Squibb, AstraZeneca, Boehringer Ingelheim, Eisai, Roche, Novartis, Merck Serono, MSD Oncology, Pfizer, Takeda, AbbVieResearch Funding: Boehringer Ingelheim, AstraZeneca, Bristol Myers Squibb, Eisai, Merck Serono, AbbVieExpert Testimony: Roche, AstraZeneca, Bristol Myers SquibbTravel, Accommodations, Expenses: Roche Pharma AG, Lilly, Bristol Myers Squibb, AstraZeneca, Merck Sharp & Dohme, Amgen Alfred ZippeliusHonoraria: BMSi, MSD, Roche, NBE Therapeutics, ACM Pharma, Hookipa Biotech, BeyondSpring PharmaceuticalsResearch Funding: Roche, NBE Therapeutics, Secarna, ACM Pharma, Hookipa Biotech, Beyondsprings Spasenija Savic PrinceHonoraria: NovartisConsulting or Advisory Role: Diaceutics Ireland Limited, Merck (Schweiz) AG, AstraZeneca AG Daniel BetticherTravel, Accommodations, Expenses: Bayer Adrienne BettiniHonoraria: MSD OncologyConsulting or Advisory Role: MSD Oncology, AstraZenecaTravel, Accommodations, Expenses: Janssen Oncology Martin FrühConsulting or Advisory Role: BMS, AstraZeneca, MSD, Takeda, Roche, LillySpeakers' Bureau: PfizerResearch Funding: BMS, AstraZeneca Markus JoergerConsulting or Advisory Role: Novartis, AstraZeneca, Basilea Pharmaceutical, Bayer, Bristol Myers Squibb, Debiopharm Group, Merck, Roche, SanofiResearch Funding: AstraZeneca, Basilea Pharmaceutical, Bayer, Bristol Myers Squibb, Daiichi Sankyo, Immunophotonics, InnoMedica, Janssen Oncology, Lilly, Merck, Novartis, Pfizer, PharmaMar, Roche, Sanofi, Takeda Laetitia A. MautiConsulting or Advisory Role: Takeda, Roche, AstraZeneca, Bristol Myers Squibb, Merck Sharp & Dohme, PfizerTravel, Accommodations, Expenses: Takeda, Bristol Myers Squibb, Merck, Roche, AstraZeneca Christian BritschgiConsulting or Advisory Role: AstraZeneca, Pfizer, Roche, Takeda, Janssen-Cilag, Boehringer IngelheimTravel, Accommodations, Expenses: AstraZeneca, Takeda Walter WederConsulting or Advisory Role: AstraZeneca, Covidien/MedtronicSpeakers' Bureau: AstraZeneca, Covidien/MedtronicTravel, Accommodations, Expenses: AstraZeneca, Covidien/Medtronic Solange PetersHonoraria: Roche, Bristol Myers Squibb, Novartis, Pfizer, MSD, AstraZeneca, Takeda, Illumina, MedscapeConsulting or Advisory Role: Roche/Genentech, Novartis, Bristol Myers Squibb, Pfizer, MSD, Amgen, AstraZeneca, Janssen, Regeneron, Merck Serono, Boehringer Ingelheim, Takeda, Lilly, AbbVie, Bayer, Biocartis, Debiopharm Group, Illumina, PharmaMar, Sanofi, Seattle Genetics, Blueprint Medicines, Daiichi Sankyo, Incyte, Bioinvent, Clovis Oncology, Vaccibody, Phosplatin TherapeuticsResearch Funding: Roche, BMS, MSD, Amgen, Lilly, AstraZeneca, Pfizer, Illumina, Merck Serono, Novartis, Biodesix, Boehringer Ingelheim, Iovance Biotherapeutics, Phosplatin TherapeuticsTravel, Accommodations, Expenses: Roche, Bristol Myers Squibb, MSD, Sanofi, IncyteUncompensated Relationships: Journal of Thoracic Oncology, ESMO, European Thoracic Oncology Platform (ETOP), Annals of Oncology Michael MarkConsulting or Advisory Role: Roche, AstraZeneca, Takeda, BMS, MSD OncologyTravel, Accommodations, Expenses: Pfizer, Roche, Takeda Richard CathomasHonoraria: Janssen-Cilag, Astellas Pharma, BMS, Debiopharm GroupConsulting or Advisory Role: Astellas Pharma, Bristol Myers Squibb, Pfizer, Roche, MSD Oncology, Janssen-Cilag, Bayer, Sanofi, IpsenTravel, Accommodations, Expenses: AstraZeneca Adrian F. OchsenbeinConsulting or Advisory Role: TolremoResearch Funding: argenxPatents, Royalties, Other Intellectual Property: Patent on the anti-CD70 antibody cusatuzumab Wolf-Dieter JanthurConsulting or Advisory Role: Roche, Takeda, MSD, Novartis Nicolas MachStock and Other Ownership Interests: MaxVAX SAResearch Funding: MaxiVaxPatents, Royalties, Other Intellectual Property: I am an inventor on patent owned by MaxiVAX SA and on patent co-owned by Geneva University Hospital and MaxiVAX SAUncompensated Relationships: MaxiVax Patrizia FroeschConsulting or Advisory Role: Pfizer, Takeda, Roche, Boehringer Ingelheim, AstraZeneca, Novartis, Bayer Pierre BohanesHonoraria: MSD, BayerTravel, Accommodations, Expenses: Janssen Corinne RusterholzEmployment: Roche Miklos PlessHonoraria: Janssen-CilagConsulting or Advisory Role: AbbVie, AstraZeneca, Boehringer Ingelheim, Bristol Myers Squibb, Eisai Europe, MSD Oncology, Novartis, Pfizer/EMD Serono, Roche, Takeda, Merck SeronoExpert Testimony: TakedaTravel, Accommodations, Expenses: Vifor Pharma, Bristol Myers Squibb, Boehringer Ingelheim, AstraZenecaNo other potential conflicts of interest were reported.

Background: Radiomics is a promising tool for identifying imaging-based biomarkers. Radiomics-based models are often trained on single-institution datasets; however, multi-centre imaging datasets are preferred for external generalizability owing to the influence of inter-institutional scanning differences and acquisition settings. The study aim was to determine the value of preselection of robust radiomic features in routine clinical positron emission tomography (PET) images to predict clinical outcomes in locally advanced non-small cell lung cancer (NSCLC)., Methods: A total of 1404 primary tumour radiomic features were extracted from pre-treatment [ 18 F]fluorodeoxyglucose (FDG)-PET scans of stage IIIA/N2 or IIIB NSCLC patients using a training cohort (n = 79; prospective Swiss multi-centre randomized phase III trial SAKK 16/00; 16 centres) and an internal validation cohort (n = 31; single centre). Robustness studies investigating delineation variation, attenuation correction and motion were performed (intraclass correlation coefficient threshold > 0.9). Two 12-/24-month event-free survival (EFS) and overall survival (OS) logistic regression models were trained using standardized imaging: (1) with robust features alone and (2) with all available features. Models were then validated using fivefold cross-validation, and validation on a separate single-centre dataset. Model performance was assessed using area under the receiver operating characteristic curve (AUC)., Results: Robustness studies identified 179 stable features (13%), with 25% stable features for 3D versus 4D acquisition, 31% for attenuation correction and 78% for delineation. Univariable analysis found no significant robust features predicting 12-/24-month EFS and 12-month OS (p value > 0.076). Prognostic models without robust preselection performed well for 12-month EFS in training (AUC = 0.73) and validation (AUC = 0.74). Patient stratification into two risk groups based on 12-month EFS was significant for training (p value = 0.02) and validation cohorts (p value = 0.03)., Conclusions: A PET-based radiomics model using a standardized, multi-centre dataset to predict EFS in locally advanced NSCLC was successfully established and validated with good performance. Prediction models with robust feature preselection were unsuccessful, indicating the need for a standardized imaging protocol., (© 2021. The Author(s).)

Introduction: The safety of first-line (1L) durvalumab in patients with advanced nonsmall-cell lung cancer (NSCLC) and an Eastern Cooperative Oncology Group (ECOG) performance status of 2 (PS2) is unknown. This is an interim unplanned safety analysis of the study SAKK 19/17 for patients with metastatic NSCLC with programmed death-ligand 1 (PD-L1) expression in ≥ 25% of tumor cells and an ECOG PS2 treated with 1L durvalumab. This safety analysis was triggered by the SAKK data and safety monitoring board due to a high mortality rate observed after the recruitment of the first 21 patients., Methods: This single-arm phase II study recruited patients with metastatic NSCLC with PD-L1 in ≥ 25% and ECOG PS2. Patients received durvalumab 1500 mg every four weeks. The trial aims to recruit 48 patients in total. This report includes safety analyses only. Adverse events (AEs) were assessed using National Cancer Institute Common Terminology Criteria for AEs (NCI CTCAE) Version 5.0. Efficacy data including the primary endpoint overall survival at 6 months and secondary endpoints (objective response rate, progression-free survival, and quality of life) will be reported at a later time point., Results: The data from 21 patients were available at this interim safety analysis. Among these, 13 deaths (13/21; 62%) were reported, including one treatment-related fatal colonic perforation at 9 months after treatment initiation (1/13; 8%). Twelve deaths were not treatment-related (12/13; 92%), and mostly attributed to tumor progression (10/13; 77%). Of note, seven deaths (7/13; 54%) occurred during the first 5 weeks (range 0.6-4.7 weeks) after treatment initiation. Four (4/7; 57%) were respiratory failures attributed to tumor progression. One of these patients (25%) had pre-existing COPD, and three (75%) had baseline dyspnea grade 2-3 related to the tumor. Grade ≥ 3 treatment-related AEs (TRAEs) included colonic perforation (grade 5), abdominal pain, and colitis (grade 3 each) in one patient, and fatigue (grade 3) in another. Other Grade ≥ 3 AEs unrelated to treatment were all of pulmonary origin: lung infections (19%), dyspnea (24%), cough (5%), and bronchial obstruction (5%)., Conclusions: 1L durvalumab in patients with ECOG PS2 and metastatic NSCLC with PD-L1 expression ≥ 25% resulted in an unexpectedly high number of fatal early events due to rapid tumor progression. We recommend to avoid treatment with 1 L durvalumab of patients who are highly symptomatic from the tumor, particularly those with respiratory symptoms. The study is continuing its accrual after an amendment excluding these patients.

Objectives: In this study, we aimed to assess the impact of different CT reconstruction kernels on the stability of radiomic features and the transferability between different diseases and tissue types. Three lung diseases were evaluated, i.e . non-small cell lung cancer (NSCLC), malignant pleural mesothelioma (MPM) and interstitial lung disease related to systemic sclerosis (SSc-ILD) as well as four different tissue types, i.e . primary tumor, largest involved lymph node ipsilateral and contralateral lung., Methods: Pre-treatment non-contrast enhanced CT scans from 23 NSCLC, 10 MPM and 12 SSc-ILD patients were collected retrospectively. For each patient, CT scans were reconstructed using smooth and sharp kernel in filtered back projection. The regions of interest (ROIs) were contoured on the smooth kernel-based CT and transferred to the sharp kernel-based CT. The voxels were resized to the largest voxel dimension of each cohort. In total, 1386 features were analyzed. Feature stability was assessed using the intraclass correlation coefficient. Features above the stability threshold >0.9 were considered stable., Results: We observed a strong impact of the reconstruction method on stability of the features (at maximum 26% of the 1386 features were stable). Intensity features were the most stable followed by texture and wavelet features. The wavelet features showed a positive correlation between percentage of stable features and size of the ROI (R2 = 0.79, p = 0.005). Lymph node radiomics showed poorest stability (<10%) and lung radiomics the largest stability (26%). Robustness analysis done on the contralateral lung could to a large extent be transferred to the ipsilateral lung, and the overlap of stable lung features between different lung diseases was more than 50%. However, results of robustness studies cannot be transferred between tissue types, which was investigated in NSCLC and MPM patients; the overlap of stable features for lymph node and lung, as well as for primary tumor and lymph node was very small in both disease types., Conclusion: The robustness of radiomic features is strongly affected by different reconstruction kernels. The effect is largely influenced by the tissue type and less by the disease type., Advances in Knowledge: The study presents to our knowledge the most complete analysis on the impact of convolution kernel on the robustness of CT-based radiomics for four relevant tissue types in three different lung diseases. .

Introduction: In the field of personalized medicine, radiomics has shown its potential to support treatment decisions. However, the limited feature interpretability hampers its introduction into the clinics. Here, we propose a new methodology to create radiomics feature activation maps, which allows to identify the spatial-anatomical locations responsible for signature activation based on local radiomics. The feasibility of this technique will be studied for histological subtype differentiation (adenocarcinoma versus squamous cell carcinoma) in non-small cell lung cancer (NSCLC) using computed tomography (CT) radiomics., Materials and Methods: Pre-treatment CT scans were collected from a multi-centric Swiss trial (training, n=73, IIIA/N2 NSCLC, SAKK 16/00) and an independent cohort (validation, n=32, IIIA/N2/IIIB NSCLC). Based on the gross tumor volume (GTV), four peritumoral region of interests (ROI) were defined: lung&#95;exterior (expansion into the lung), iso&#95;exterior (expansion into lung and soft tissue), gradient (GTV border region), GTV+Rim (GTV and iso&#95;exterior). For each ROI, 154 radiomic features were extracted using an in-house developed software implementation (Z-Rad, Python v2.7.14). Features robust against delineation variability served as an input for a multivariate logistic regression analysis. Model performance was quantified using the area under the receiver operating characteristic curve (AUC) and verified using five-fold cross validation and internal validation. Local radiomic features were extracted from the GTV+Rim ROI using non-overlapping 3x3x3 voxel patches previously marked as GTV or rim. A binary activation map was created for each patient using the median global feature value from the training. The ratios of activated/non-activated patches of GTV and rim regions were compared between histological subtypes (Wilcoxon test)., Results: Iso&#95;exterior, gradient, GTV+Rim showed good performances for histological subtype prediction (AUC training =0.68-0.72 and AUC validation =0.73-0.74) whereas GTV and lung&#95;exterior models failed validation. GTV+Rim model feature activation maps showed that local texture feature distribution differed significantly between histological subtypes in the rim (p=0.0481) but not in the GTV (p=0.461)., Conclusion: In this exploratory study, radiomics-based prediction of NSCLC histological subtypes was predominantly based on the peritumoral region indicating that radiomics activation maps can be useful for tracing back the spatial location of regions responsible for signature activation., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2020 Vuong, Tanadini-Lang, Wu, Marks, Unkelbach, Hillinger, Eboulet, Thierstein, Peters, Pless, Guckenberger and Bogowicz.)

Background: The coronavirus pandemic has provoked discussions among healthcare providers how to manage cancer patients when faced with the threat of severe acute respiratory syndrome related coronavirus 2 (SARS-CoV-2) infection. Immune checkpoint inhibitor (ICI) containing regimens are standard of care in the majority of metastatic clear cell renal cell carcinoma (mccRCC) patients. It remains unclear whether therapies should be modified in response to the COVID-19 pandemic., Methods: We performed an online survey among physicians involved in the treatment of mccRCC, and 41 experts responded. Questions focused on criteria relevant for treatment decision outside the pandemic and the modifications of systemic therapy during COVID-19., Findings: For the majority of experts (73%), the combination of International metastatic renal cell carcinoma Database Consortium (IMDC) risk category and patient fitness are two important factors for decision-making. The main treatment choice in fit, favourable risk patients outside the pandemic is pembrolizumab/axitinib for 53%, avelumab/axitinib, sunitinib or pazopanib for 13% of experts each. During the pandemic, ICI-containing regimens are chosen less often in favour of a tyrosine kinase inhibitors (TKI) monotherapy, mainly sunitinib or pazopanib (35%).In fit, intermediate/poor-risk patients outside the pandemic, over 80% of experts choose ipilimumab/nivolumab, in contrast to only 41% of physicians during COVID-19, instead more TKI monotherapies are given. In patients responding to established therapies with ICI/ICI or ICI/TKI combinations, most participants modify treatment regimen by extending cycle length, holding one ICI or even both., Conclusion: mccRCC treatment modifications in light of the coronavirus pandemic are variable, with a shift from ICI/ICI to ICI/TKI or TKI monotherapy., Competing Interests: Competing interests: SA: MSD (C/A), Sanofi-Genzyme (C/A) recipient: my institution. TE: Personal: AstraZeneca (RF, E, OI), Bayer (RF), Pfizer (RF), Roche (E, OI); Institution: AstraZeneca (RF), Roche (RF). BE: Pfizer (C/A), BMS (C/A), Ipsen (C/A), Roche (C/A), Oncorena (C/A), Aveo (C/A). SF: Bayer (TS), Astellas (RF, TS). VG: Astra Zeneca (C/A, H, OI, RF), Bristol-Myers Squibb (C/A, H, OI, RF), Roche Pharma AG (C/A, H), MSD Oncology (C/A, H, OI, RF), Ipsen (C/A, H, RF), Bayer (H, RF), Merck Serono (C/A, H), Janssen Cliag (C/A, H), Pfizer (C/A, H), Lilly (C/A, H), PharmaMar (H), EUSAPharm (C/A, H), Novartis (C/A, H, RF), EISAI (H), Onkowissen (C/A). JML: Achilles Therapeutics (C/A, grant support), Bristol-Myers Squibb (C/A, grant support), Merck Sharp & Dohme (C/A, grant support), Nektar (C/A, grant support), Novartis (C/A, grant support), Pfizer (C/A, grant support), Roche–Genentech (C/A, grant support), Immunocore (C/A, grant support), AstraZeneca (C/A), Boston Biomedical (C/A), Eisai (C/A), EUSA Pharma (C/A), GlaxoSmithKline (C/A), Ipsen (C/A), Imugen (C/A), Incyte (C/A), iOnctura (C/A), Kymab (C/A), Merck Serono (C/A), Pierre Fabre (C/A), Secama (C/A), Vitaccess (C/A), Covance (C/A), Aveo (C/A), Pharmacyclics (C/A). DM: BMS (H, C/A), Pfizer (H, C/A), Merck (H, C/A), Alkermes, Inc. (H, C/A). AO: Personal: Astellas (TS), Bayer (TS), Sanofi (TS), Janssen (TS). Instituional: Astellas (C/A, SB), Bayer (C/A, SB), Sanofi (C/A), Roche (C/A), Janssen (C/A, RF, SB), MSD (C/A), Molecular Partners (C/A), Teva (RF). CP: Bristol-Myers Squibb (personal fees), Merck Sharpe & Dohme (personal fees), Novartis (personal fees), Ipsen (personal fees), EUSA (personal fees), Eisai (personal fees), Janssen (personal fees), AstraZeneca (personal fees), General Electric (personal fees), Pfizer (grants and personal fees). BR: Merck (C/A), BMS (C/A), AVEO (C/A), Pfizer (C/A), Roche(C/A), Pfizer (RF), Merck (RF), BMS (RF), AVEO (RF), Astra-Zeneca (RF), Roche (RF). MS: Pfizer, BMS, Ipsen, MSD, Merck, Exelixis, EISAI, EUSA, Roche, Novartis, Alkermes. CS: Pfizer (C/A), MSD (C/A), Merck (C/A), AstraZeneca (C/A), Astellas (C/A), Sanofi-Genzyme (C/A), Roche-Genentech (C/A), Incyte (C/A). CR: Pfizer (C/A), Bristol-Myers Squibb (C/A), Roche Pharma AG (C/A), MSD Oncology (C/A), Merck (Schweiz) AG (C/A) recipient for all: my institution. Astellas Pharma (RF) recipient: my institution. Legend: (C/A) Consulting/advisory relationship; (RF) Research funding; (E) Employment; (ET) Expert testimony; (H) Honoraria received; (TS) Travel Support; (OI) Ownership interests; (IP) Intellectual property rights/inventor/patent holder; (SAB) Scientific advisory board, Speaker Bureau (SB)., (© Author (s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. Published by BMJ on behalf of the European Society for Medical Oncology.)

Purpose: Our purpose was to evaluate neurocognitive function (NCF) and clinical outcomes after early hippocampal avoidance (HA) prophylactic cranial irradiation (PCI) in limited disease (LD) small cell lung cancer (SCLC)., Methods and Materials: In a phase 2 trial, patients with LD SCLC received HA-PCI concomitant with the second cycle of chemotherapy and thoracic radiation therapy. All patients underwent objective NCF testing at baseline, 6 weeks, and 6 and 12 months after HA-PCI. NCF tests included Hopkins Verbal Learning Test Revised, Controlled Oral Word Association, and Trail Making Tests A and B. The primary endpoint was NCF decline at 6 months after HA-PCI. We assumed ≤30% of patients with no NCF decline to be unpromising. Secondary endpoints included brain metastases-free survival (BMFS), overall survival (OS), and safety of the concomitant treatment., Results: Among the 44 patients enrolled in the trial, 38 had evaluable NCF assessment at 6 months after HA-PCI. The proportion of evaluable patients showing no NCF decline at 6 and 12 months was 34.2% (90% confidence interval [CI], 21.6-48.8) and 48.5% (95% CI, 30.8-66.5), respectively. Median follow-up was 13.2 months (95% CI, 12.6-14.1). At 12 months, BMFS was 84.2% and OS was 87.7% (95% CI, 73.0-94.7). Four patients died of SCLC, 1 of respiratory failure, 1 of hemorrhage, and 1 for unknown reason. The most frequently reported grade ≥3 acute adverse events were anemia (21.4%), febrile neutropenia (19.1%), and fatigue (14.3%)., Conclusions: The proportion of patients showing no NCF decline 6 and 12 months after early HA-PCI does not appear to be better than, but rather similar to, that observed in patients receiving sequential PCI without HA. Early HA-PCI in LD SCLC is feasible, with observation of promising BMFS and OS in this selected population., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Background: Systemic second- and third-line therapies for malignant pleural mesothelioma (MPM) result in a median progression-free survival (mPFS) of <2 months and median overall survival (mOS) of 6-9 months. Lurbinectedin binds to the DNA of the regulatory region while inhibiting tumour-associated macrophage transcription. In early trials, encouraging outcomes occurred in patients (pts) with MPM treated with lurbinectedin. We aimed to generate lurbinectedin efficacy and safety data among pts with progressive MPM., Patients and Methods: Pts with progressing MPM treated with first-line platinum-pemetrexed chemotherapy with or without immunotherapy received lurbinectedin monotherapy. Treatment was given intravenously at 3.2 mg/m 2 dose every 3 weeks until progression or unacceptable toxicity. Using Simon's two-stage design, the primary endpoint, progression-free survival (PFS) at 12 weeks (PFS 12wks ), was met if achieved by ≥21 pts (p0 ≤35% versus p1 ≥55%)., Results: Forty-two pts from nine centres across Switzerland and Italy were recruited. Histology was epithelioid in 33 cases, sarcomatoid in 5, and biphasic in 4. Overall 10/42 (23.8%) underwent prior immunotherapy and 14/42 (33.3%) had progressed ≤6 months after first-line chemotherapy. At data cut-off PFS 12wks was met by 22/42 pts (52.4%; 90% confidence interval (CI): 38.7% to 63.5%; P = 0.015) with an mPFS of 4.1 months and mOS of 11.1 months. The best response was complete and partial remission observed in one patient each and stable disease in 20 pts. The duration of disease control was 6.6 months (95% CI: 5.2-7.4). No significant difference in PFS 12wks, mPFS, and mOS was recorded in epithelioid versus non-epithelioid cases and pts with prior immunotherapy versus those without. Similar mPFS but shorter mOS were observed among pts who progressed within ≤6 months after first-line chemotherapy. Lurbinectedin-related grade 3-4 toxicity was seen in 21 pts, mostly being neutropenia (23.8%) and fatigue (16.7%)., Conclusions: The primary efficacy endpoint was reached with acceptable toxicity. Lurbinectedin showed promising activity regardless of histology, prior immunotherapy, or outcome on prior treatment. CLINICALTRIALS., Gov Identifier: NCT03213301., Competing Interests: Disclosure YM declares travel grants as well as advisory fees from PharmaMar paid to his institution. RvM declares advisory fees from PharmaMar paid to his institution. All other authors have declared no conflicts of interest., (Copyright © 2020 European Society for Medical Oncology. Published by Elsevier Ltd. All rights reserved.)