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Abstract:
There are many important changes in the 2015 WHO classification of lung tumours, reflecting the numerous advances in tumour genetics and therapy over the past decade.[1] Many have been in the field of adenocarcinoma, with discontinuation of the term bronchioloalveolar carcinoma and the concept of stepwise progression accepted for adenocarcinoma.[1] Adenocarcinoma in situ (AIS) is a small (less than 3 cm in diameter), pure lepidic adenocarcinoma; minimally invasive adenocarcinoma (MIA) is also a small lepidic adenocarcinoma but has small invasive areas less than 5 mm across. As both entities have a very favorable outcome, with an expected 5-year survival rate of 100%, AIS and MIA are targets for reduction surgery, and are frequently detected by low-dose CT screening. High-resolution (HR)-CT demonstrates these tumours as a pure ground glass nodule (GGN) or a part-solid nodule (PSN), being closely correlated with their pathological features.[2] Therefore, AIS and MIA can be assessed by HR-CT. However, the size of the solid component in HR-CT images does not necessarily correspond to the extent of histological invasion, since features such as alveolar collapse and fibrosis are also included in the solid part demonstrated by HR-CT.[1] Although the new WHO classification defines the histological criteria for MIA invasion, the degree of inter-observer agreement regarding the histological definition of invasion in MIA has still not been fully studied, and a consensus trial will be needed in the near future. More advanced adenocarcinoma is subdivided into five categories: lepidic, papillary, acinar, solid and micropapillary. These subtypes are diagnosed according to the predominant component and the group comprising lepidic, papillary and acinar adenocarcinomas shows a better prognosis than those with solid and micropapillary patterns. Therefore the presence of solid and/or micropapillary adenocarcinoma should be reported, even if the predominant component is lepidic, papillary or acinar adenocarcinoma. These patterns also predict response to adjuvant chemotherapy,[3] and the above changes overall have also led new proposals for both clinical and pathologic staging in the 8[th] TNM revision in terms of multiple primary tumours and measurement of tumour invasive size.[4,5] For the other three major tumour types (large cell carcinoma (LCC), squamous cell carcinoma (SQCC) and neuroendocrine (NE) tumours), the classification has evolved from mainly morphological to a more biologically based system, which allows more appropriate decisions in relation to adjuvant therapy and better defined subgroups for studies into molecular characterisation and the search for potentially treatable targets. LCC is now restricted to resected tumours that lack clear morphologic and immunohistochemical differentiation, with reclassification of those that do to solid adenocarcinoma (TTF-1 positive) and non-keratinising SQCC (P40 and/or CK5/6 positive). This has already been shown to correlate with molecular data.[6] For SQCC, classification is simplified to keratinizing, nonkeratinizing and basaloid subtypes, with the non-keratinizing tumours ideally requiring immunohistochemical confirmation. Criteria for diagnosing NE tumours remain essentially unchanged but these tumours are now grouped in one category, with further subdivision into carcinoids, and large cell neuroendocrine carcinoma and small cell carcinoma. Molecular studies based on these definitions are already identifying interesting subgroups.[7] In relation to rarer entities, the definition of pleomorphic carcinomas is also being shown to have clinical relevance in terms of correlating with potential therapies, both in relation to specific molecular abnormalities (exon 14 skipping mutations)[8] and immunoodulatory therapy with high levels of PD-L1 expression.[9] Molecular characterisation is also increasingly important in the accurate diagnosis and potential treatment of other rare tumours, such as NUT-carcinoma and inflammatory myofibroblastic tumours (ALK and ROS1/RET gene rearrangements).[10] A classification system for small biopsies and cytology is provided for the first time, with emphasis on integration of molecular testing and usage of a limited panel of immunohistochemistry when needed (table 1). The presence of such a system for the first time provides a system for consistent classification of the majority (unresectable) of lung cancer cases, both in terms of clinical management, assignment to pathways for molecular and immunomodulatory characterisations, and for assessment of the results of clinical trials that have sometimes been confounded by inaccurate subgrouping. The book also emphasises how to obtain the greatest value from small sample via efficient usage and avoidance of inappropriate testing.[1] Table 1: Classification of non-small cell lung carcinoma in small biopsies and cytology specimens when there is no morphologic evidence of differentiation

2015 WHO Small Biopsy/Cytology Terminology	Morphology/Stains	2015 WHO Classification in resection specimens
Non-small cell carcinoma, favour adenocarcinoma using IHC	Morphologic adenocarcinoma patterns (lepidic, acinar, papillary, micropapillary) not present, but supported by special stains (+TTF-1)	Adenocarcinoma, solid pattern (may only be a component)
Non-small cell carcinoma, favour squamous cell carcinoma using IHC	Morphologic squamoid features (keratinization and/or clear intercellular bridging) not present, but supported by stains ( +p40)	Squamous cell carcinoma, (non-keratinizing pattern may be just one component)
Non-small cell carcinoma, not otherwise specified NSCLC-NOS using IHC	No clear adenocarcinoma, squamous or neuroendocrine morphology or staining pattern (IHC or mucin stains).	Large cell carcinoma

REFERENCES 1. WHO Classification of Tumours of the Lung, Pleura, Thymus and Heart. Lyons, France.: International Agency for Research on Cancer (IARC); 2015. 2. Kakinuma R, Noguchi M, Ashizawa K, et al. Natural History of Pulmonary Subsolid Nodules: A Prospective Multicenter Study. J Thorac Oncol. Jul 2016;11(7):1012-1028. 3. Tsao MS, Marguet S, Le Teuff G, et al. Subtype Classification of Lung Adenocarcinoma Predicts Benefit From Adjuvant Chemotherapy in Patients Undergoing Complete Resection. J Clin Oncol. Oct 20 2015;33(30):3439-3446. 4. Detterbeck FC, Nicholson AG, Franklin WA, et al. The IASLC Lung Cancer Staging Project: Summary of Proposals for Revisions of the Classification of Lung Cancers with Multiple Pulmonary Sites of Involvement in the Forthcoming Eighth Edition of the TNM Classification. J Thorac Oncol. Feb 29 2016. 5. Travis WD, Asamura H, Bankier AA, et al. The IASLC Lung Cancer Staging Project: Proposals for Coding T Categories for Subsolid Nodules and Assessment of Tumor Size in Part-Solid Tumors in the Forthcoming Eighth Edition of the TNM Classification of Lung Cancer. J Thorac Oncol. Aug 2016;11(8):1204-1223. 6. Clinical Lung Cancer Genome P, Network Genomic M. A genomics-based classification of human lung tumors. Sci Transl Med. Oct 30 2013;5(209):209ra153. 7. Rekhtman N, Pietanza MC, Hellmann MD, et al. Next-Generation Sequencing of Pulmonary Large Cell Neuroendocrine Carcinoma Reveals Small Cell Carcinoma-like and Non-Small Cell Carcinoma-like Subsets. Clin Cancer Res. Jul 15 2016;22(14):3618-3629. 8. Schrock AB, Frampton GM, Suh J, et al. Characterization of 298 Patients with Lung Cancer Harboring MET Exon 14 Skipping Alterations. J Thorac Oncol. Sep 2016;11(9):1493-1502. 9. Chang YL, Yang CY, Lin MW, Wu CT, Yang PC. High co-expression of PD-L1 and HIF-1alpha correlates with tumour necrosis in pulmonary pleomorphic carcinoma. Eur J Cancer. Jun 2016;60:125-135. 10. Antonescu CR, Suurmeijer AJ, Zhang L, et al. Molecular characterization of inflammatory myofibroblastic tumors with frequent ALK and ROS1 gene fusions and rare novel RET rearrangement. Am J Surg Pathol. Jul 2015;39(7):957-967.

Abstract not provided

Abstract:
Lung cancer is still the leading cause of cancer-related death in both men and women with 80% to 85% of cases being non-small-cell lung cancer (NSCLC).[1]Over the past years, the IASLC Staging and Prognostic Factors Committee has collected a new database of 94,708 cases of lung cancer as the backbone for the upcoming 8[th] edition of the TNM classification for lung cancer due to be published late 2016 [2,3]. The 8[th] edition will significantly impact lung cancer staging with CT and/or PET-CT due to the subclassification of T1 and T2 into a,b and c categories, the reclassification of tumors more than 5 cm but not more than 7 cm in greatest dimension as T3, the reclassification of tumors more than 7 cm in greatest dimension as T4, the grouping of the involvement of the main bronchus as a T2 descriptor, regardless of distance from the carina, but without invasion of the carina, the grouping of partial and total atelectasis or pneumonitis as a T2 descriptor, the reclassification of diaphragm invasion as T4 and the elimination of mediastinal pleura invasion as a T descriptor [2,3]. Moreover, the upcoming 8[th] edition will also lead to a novel classification of distant metastasis, in which single extrathoracic metastasis will be classified as M1b whereas multiple extrathoracic metastasis are classified as M1c. The changes made within the proposal of the 8[th] edition of the TNM will be discussed within the presentation using clinical examples. Beside the accurate staging of patients with lung cancer early detection using CT screening with novel low radiation dose CT technologies will also be discussed. Within this context, a special focus will be given on novel methods that may improve a more accurate characterization of detected lung nodules using deep machine learning and Radiomics. Radiomics refers to the comprehensive quantification of lung nodule and tumour phenotypes by applying a large number of quantitative image features that are standardized collected with specific software algorithms. Radiomics features have the capability to further enhance imaging data regarding prognostic tumour signatures, detection of tumour heterogeneity as well as the detection of underlying gene expression patterns which is of special interest in patients with metastatic disease. The third part of the presentation will focus on novel techniques in lung cancer imaging. The past fifteen years have brought significant breakthroughs in the understanding of the molecular biology of lung cancer. Signalling pathways and genetic driver mutations that are vital for tumour growth have been identified and can be effectively targeted by novel pharmacologic agents, resulting in significantly improved survival of patients with lung cancer[4]. Parallel to the progress in lung cancer treatment, imaging techniques aiming at improving diagnosis, staging, response evaluation, and detection of tumour recurrence have also considerably advanced in recent years[5]. However, standard morphologic computed tomography (CT) and magnetic resonance imaging (MRI) as well as fluor-18-fluorodeoxyglucose ([18]F-FDG) positron emission tomography CT (PET-CT) are still the currently most frequently utilized imaging modalities in clinical practice and most clinical trials [6,7]. Novel state-of-the-art functional imaging techniques such as dual-energy CT (DECT), dynamic contrast enhanced CT (DCE-CT), diffusion weighted MRI (DW-MRI), perfusion MRI, and PET-CT with more specific tracers that visualize angiogenesis, tumour oxygenation or tumour cell proliferation have not yet been broadly implemented, neither in clinical practice nor in phase I–III clinical trials. In this context, Nishino et al.[4] published an article on personalized tumour response assessment in the era of molecular treatment in oncology. The authors showed that the concept of personalized medicine with regard to cancer treatment has been well applied in therapeutic decision-making and patient management in clinical oncology. With regard to imaging techniques, however, it was criticized that the developments in tumour response assessment that should parallel the advances in cancer treatment are not sufficient to produce state-of-the-art functional information that directly reflect treatment targets. Functional information on tumour response is highly required because there is growing evidence that the current objective criteria for treatment response assessment may not reliably indicate treatment failure and do not adequately capture disease biology. Molecular-targeted therapies and novel immunotherapies induce effects that differ from those induced by classic cytotoxic treatment including intratumorale haemorrhage, changes in vascularity, and tumour cavitation. Thus, conventional approaches for therapy response assessment such as RECIST or WHO criteria that exclusively focus on the change in tumour size are of decreasing value for drug response assessment in clinical trials[8,9]. In summary, the aim of of this presentation is to provide an overview on the changes made within the upcoming 8[th] of the TNM classification as well as to provide an overview on state-of-the-art imaging techniques for lung cancer screening, staging, response evaluation as well as surveillance in patients with lung cancer. The various techniques will be discussed regarding their pros and cons to further provide functional information that best reflects specific targeted therapies including anti-angiogenetic treatment, immunotherapies and stereotactic body radiation therapy. Literature: 1. Rami-Porta R, Crowley JJ, Goldstraw P. The revised TNM staging system for lung cancer. Ann Thorac Cardiovasc Surg 2009;15:4-9. 2. Asamura H, Chansky K, Crowley J, et al. The International Association for the Study of Lung Cancer Lung Cancer Staging Project: Proposals for the Revision of the N Descriptors in the Forthcoming 8th Edition of the TNM Classification for Lung Cancer. Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer 2015;10:1675-84. 3. Rami-Porta R, Bolejack V, Crowley J, et al. The IASLC Lung Cancer Staging Project: Proposals for the Revisions of the T Descriptors in the Forthcoming Eighth Edition of the TNM Classification for Lung Cancer. Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer 2015;10:990-1003. 4. Rengan R, Maity AM, Stevenson JP, Hahn SM. New strategies in non-small cell lung cancer: improving outcomes in chemoradiotherapy for locally advanced disease. Clin Cancer Res 2011;17:4192-9. 5. Miles K. Can imaging help improve the survival of cancer patients? Cancer Imaging 2011;11 Spec No A:S86-92. 6. Nishino M, Jackman DM, Hatabu H, Janne PA, Johnson BE, Van den Abbeele AD. Imaging of lung cancer in the era of molecular medicine. Acad Radiol 2011;18:424-36. 7. Nishino M, Jagannathan JP, Ramaiya NH, Van den Abbeele AD. Revised RECIST guideline version 1.1: What oncologists want to know and what radiologists need to know. AJR Am J Roentgenol 2010;195:281-9. 8. Oxnard GR, Morris MJ, Hodi FS, et al. When progressive disease does not mean treatment failure: reconsidering the criteria for progression. J Natl Cancer Inst 2012;104:1534-41. 9. Stacchiotti S, Collini P, Messina A, et al. High-grade soft-tissue sarcomas: tumor response assessment--pilot study to assess the correlation between radiologic and pathologic response by using RECIST and Choi criteria. Radiology 2009;251:447-56.

Background:
Institutional-level differences in NSCLC survival are associated with differences in the quality of oncologic care. We examined stage-stratified and overall survival of patients in different categories of US Commission-on-Cancer (CoC)-accredited institutions, to quantify inter-institutional differences in survival-impactful quality measures and estimate their relative survival impact, in order to identify the most impactful targets for improvement efforts.

Methods:
National Cancer Data Base (NCDB) institutions were grouped according to CoC category into: Community Cancer Program (CCP), Comprehensive Community Cancer Program (CCCP), Teaching Research Program (TRP), and NCI Program/Network (NCIP). Resections for stage I-IIIA NSCLC in the National Cancer Data Base from 2004-2013 performed within each category of institution were examined for specific quality parameters. Survival was estimated by the Kaplan-Meier method and compared with the log-rank test.

Results:
Of 125,408 NSCLC eligible patients, 8% received surgery at CCP, 52% at CCCP, 28% at TRP, and 12% at NCIP. The pNX rate was 8%, 5.7%, 5.5%, and 3.2% respectively (p<.0001); the median (IQR) nodal count for pN0/1 patients was 6 (7), 7 (7), 8 (9), and 10 (10) respectively, and the CoC quality criterion attainment rate (examination of >10 nodes for stage I/II patents) was 25.5%, 30.2%, 38.7%, and 51.4% (p<.0001). The nodal upstaging rate from clinical (c) N0 to pathologic N-positive was 10.4%, 10.8%, 10.7% and 13.1% (p<.0001); for cN1, nodal upstaging rate was 9.4%, 10.5%, 10.4% and 15.5% (p<.0001). There was no significant inter-institutional difference in 5-year OS for stage I/II patients with pNX resections: 0.47 v 0.50 v 0.51 v 0.54 (log-rank p=.27), whereas stage I/II patients with resections meeting or failing the CoC quality standard had persistent inter-institutional survival differences. For those with <10 nodes, 5-year survival was 0.59 v 0.63 v 0.65 v 0.69 (log-rank p<.0001) and for those with >10 nodes, it was 0.62 v 0.64 v 0.67 v 0.69 (log-rank p<.0001).

Conclusion:
Striking differences in the quality and accuracy of NSCLC pathologic nodal staging exist between the different categories of CoC-accredited facilities. Institutions with higher quality staging have significantly better stage-stratified OS. This inter-institutional survival difference disappears in the patients without examination of any lymph nodes, who arguably have similarly bad quality pathologic nodal staging. However, adjustment for other measures of pathologic nodal staging quality failed to eliminate the inter-institutional survival disparity. Further investigation of inter-institutional practice differences is needed to understand the institutional-level difference in survival after lung cancer surgery.

Background:
Low-dose computed tomography lung cancer screening has been demonstrated to increase detection of cases at an early-stage and reduce lung cancer mortality (vs. x-ray or no screening). However, screening benefits are greatly reduced in persons who are poor candidates for curative intent surgery in the event of screen-detected early-stage disease. To date, no practical tools have been developed to assess potential suitability for surgical treatment at the time of screening shared decision-making. The objective of this study was to use readily available socio-demographic and medical history variables to develop a prediction model that estimates the risk of 30-day mortality following surgical treatment for early-stage non-small cell lung cancer (NSCLC).

Methods:
We used logistic regression to develop a risk-prediction model for 30-day mortality following surgical treatment for Stage I/II NSCLC in patients age 65 to 79 using SEER-Medicare linked databases (2007-2012). Additionally, all patients had at least 1 year of Medicare enrollment prior to NSCLC diagnosis and received initial surgical treatment within 6 months of diagnosis. We developed the model with a training sample of 1,571 surgical cases and conducted internal validation exercises with a sample 4,632 independent surgical cases. Models included age, sex, race, country of birth, urban-rural status, and comorbidities in the year prior to NSCLC diagnosis. The Hosmer-Lemeshow test (by decile) and area under the receiver-operating characteristic curve (AUC) were assessed as measures of model calibration and discrimination, respectively.

Results:
Within the full sample of 6,203 cases, 201 deaths were identified within 30 days of surgical treatment (3.2% of sample). In the training and internal validation sets, the AUC was 0.831 and 0.734, respectively. The observed risk of 30-day mortality was 9.3-fold greater in the highest decile of predicted risk (8.3%) vs. the lowest decile (0.7%), and the Hosmer-Lemeshow test indicated satisfactory model fit (p=0.92). The model had similar performance in women, men, whites, and non-whites; and also had similar calibration and discrimination for 60- and 90-day mortality.

Conclusion:
Our risk-prediction model has good ability to identify patients at increased risk of mortality following surgical treatment for early-stage NSCLC, and pending additional development and validation, can potentially be applied in clinic to inform lung cancer screening shared decision-making with minimal time or resource impacts.

Background:
At the time of diagnosis, two-thirds of patients with lung cancer are ≥65 years of age with significant comorbidities. We sought to determine the short- and long-term cancer- and noncancer-specific mortality and morbidity in patients who underwent resection for stage I non-small cell lung cancer (NSCLC).

Methods:
Of 5371 consecutive patients who had undergone curative-intent resection of primary lung cancer (2000–2011), 2186 patients with pStage I NSCLC were included in the analysis. All preoperative clinical variables known to affect outcomes were considered, including, Charlson comorbidity index, predicted postoperative (ppo) diffusion capacity of the lung for carbon monoxide (DLCO), and ppo–forced expiratory volume in 1 second (FEV1). Association between factors and cause-specific mortality was performed using competing risks approach.

Results:
Of 2186 patients, 1532 patients (70.1%) were ≥65 years of age, including 638 patients (29.2%) ≥75 years of age. In patients ≥65 years of age, for up to 2.5 years after resection, noncancer-specific CID was higher than lung cancer–specific CID, the higher noncancer-specific early-phase mortality was enhanced in patients ≥75 years of age compared with 65-74 years of age (Figure 1a). Multivariable analyses adjusted by age, sex, smoking status, comorbidities, tumor size, and surgical procedures showed that low ppoDLCO was an independent predictor for severe morbidity (p<0.001), 1-year mortality (p<0.001), and noncancer-specific mortality (p<0.001), whereas low ppoFEV1 for lung cancer–specific mortality (p=0.002). PpoDLCO can be used for estimation of 5-year cumulative incidence of noncancer death (Figure 1b, right, red curve) because of its linear relation, whereas ppoFEV1 for lung cancer-specific death (Figure 1b, left, black curve).

Conclusion:
In patients undergoing curative-intent resection of stage I NSCLC, noncancer-specific mortality is a significant competing event, with increasing impact as patient age increases. Figure 1

Abstract not provided

Background:
Postoperative complications after pulmonary resection may cause morbidities such as prolonged hospitalization. Recently, combined pulmonary fibrosis and emphysema (CPFE) have reportedly been linked to a high risk for postoperative complications following lung cancer surgery. Moreover, some studies have claimed that lung age (LA) is associated with postoperative complications. Here we clarify the relationship between LA and postoperative complications in lung cancer patients with CPFE.

Methods:
Among a total of 1166 consecutive patients who underwent curative resection for lung cancer from January 2004 to April 2016 at the Kitasato University Hospital, Japan, a dataset of 36 patients with CPFE was retrospectively analyzed. Lungs with CPFE were defined based on preoperative chest computed tomography (CT) findings. LA was determined using the methods advocated by the Japanese Respiratory Society. The difference between “real age” (RA) and LA was calculated as “RA−LA,” and patients were classified into three groups: group A, RA−LA > 0 (n = 10); group B, −15 ≤ RA−LA ≤ 0 (n = 13); group C, RA−LA < −15 (n = 13).

Results:
The average age was 70 (males, 69.1; females, 73.2) years. Thirty two patients were male and four were female. Almost all patients were ex- or current smokers. The average postoperative hospital stay was 16 (range, 7–56) days. There were no significant differences in age, gender, smoking history, and postoperative　hospital stay among the three groups. The surgical procedures were lobectomy (n = 29), segmentectomy (n = 2), and wedge resection (n = 5). Histologically, the tumors were squamous cell carcinoma (n = 22), adenocarcinoma (n = 9), and other types (n = 4). Postoperative complications were arrhythmia (4 cases), hypertension (4 cases), air leakage (3 cases), pneumonia (5 cases), hypoxemia (3 cases), and others (5 cases). There were no significant differences in postoperative complications among the groups (p = 0.69). However, cardiovascular complications in group C were significantly higher than those in the other groups (p = 0.008). There were 26 patients with postoperative acute exacerbation, but there were no significant differences among the groups.

Conclusion:
LA accurately predicted postoperative cardiovascular complications in lung cancer patients with CPFE.

Background:
The occurrence of minimally invasive thoracic surgery interventions has grown steadily since the early 1990s, yet practice patterns for peri-operative management of these patients has lagged behind technical progress. Our thoracic program has created WAVE (Walking After VATS Experiment) which focuses on a multidisciplinary approach to early ambulation after thoracic surgery. A report from our first 3 years of data (July 2010 - July 2013) was presented at the 2013 IASLC meeting in Sydney, Australia. In response to the positive comments, we have continued our endeavor and in addition, investigated 30 day outcomes and length of stay for the homogeneous subset of anatomic lobectomy.

Methods:
Data was collected from a single surgeon at a single center and includes all consecutive thoracic surgical patients recovered through the WAVE program from July 2010 - July 2016. We excluded patients undergoing tracheostomy, endoscopic only procedures, and mediastinoscopy. Data was collected prospectively and analyzed retrospectively.

Results:
From July 2010 - July 2016, 1152 patients were included for analysis. Within the 6 year period, 798/1152 patients (69%) walked any distance within one hour of extubation, 945/1152 patients (82%) walked 250 feet at any time while in the PACU, 721/1152 patients (63%) successfully walked the targeted distance of 250 feet within one hour of extubation and only 37/1152 patients (3%) were unable to ambulate at all in the PACU. There were no adverse events. The subset of anatomic lobectomies included 290 patients of which 197/290 patients (68%) walked any distance within one hour of extubation, 239/290 patients (82%) successfully walked 250 feet at any time while in the PACU, 175/290 patients (60%) achieved the target distance of 250 feet within one hour of extubation and only 5/290 patients (1.7%) were unable to ambulate at all in the PACU. The rate of 30 day post-operative complications compares favorably with the literature and are as follows: 4.1% atrial arrhythmia, 1.0% pneumonia, 6.6% air leak > 5 days, 0.7% DVT, 0.3% acute renal failure, 0.3% pulmonary embolism, 0% stroke, 0% myocardial infarction, 4.8% readmission and 0% mortality. Mean length of hospital stay was 1.6 days with a median of 1 day.

Conclusion:
Our “WAVE” experience reveals that aggressive early ambulation is effective in reducing post-operative complications and shortening length of stay. The platform is simple, reproducible and feasible for any thoracic surgical program. Key features for successful implementation include patient and family engagement, a multi-disciplinary team and administrative support.

Background:
There is no consensus for the appropriate follow-up of patients after complete resection of non-small cell lung cancer (NSCLC). Our study was designed to visually represent postoperative recurrence patterns for NSCLC with the use of event dynamics and to optimize postoperative follow-up schedule based on risk factors for recurrence.

Methods:
A total of 829 patients with NSCLC who underwent complete pulmonary resection were studied. There were 538 men and 291 women with a mean age of 69.2 at the time of operation. The majority of the patients had adenocarcinoma (62.5%), underwent lobectomy (85.9%) and pathological stage IA (47.3%). Event dynamics, based on the hazard rate, were evaluated and only first events (distant metastases or local recurrence) were considered. The effects of sex, histological type and pathological stage were studied.

Results:
On non-parametric kernel smoothing, the resulting hazard rate curves indicated that the recurrence risk pattern was definitely correlated to sex, with a sharp peak in the first year for men and broad peak during the 2 to 3 years for women. This finding was also confirmed by the analysis of histological type. Although pathological stage IA patients lacked such a large peak in both sexes during the follow-up period, gender difference was shown in pathological stage IB and stage IIA to IIIB patients. Figure 1



Conclusion:
The use of recurrence dynamics allows the times of peak recurrence to be visualized. The hazard rate and the peak times of recurrence differed considerably between genders in pathological stage IB or higher. Postoperative follow-up methods should be based on currently recommended follow-up guidelines, give adequate consideration to the recurrence patterns, and be modified individually.

Abstract not provided

Background:
Thymic Epithelial Tumors (TET) are rare intrathoracic malignancies, for which surgery represents the mainstay of the treatment strategy. Current practice for postoperative mediastinal radiotherapy is highly variable, and there is paucity of prospective, multicentre evidence. RYTHMIC is the nationwide network for TET in France, established in 2012. Whether postoperative radiotherapy (PORT) should be delivered was the most frequent question raised at the RYTHMIC multi-disciplinary tumor board (MTB) over the past 3 years, accounting for 494 (35%) of a total of 1401 questions.

Methods:
All consecutive patients for whom postoperative adjuvant radiotherapy was discussed at the RYTHMIC MTB from 2012 to 2015 were identified from the RYTHMIC prospective database.

Results:
285 patients were identified, 274 (52% men, 48% women) of whom fulfilled inclusion criteria. Average age at time of TET diagnostic was 60 years. TET histology was thymoma in 243 (89%) cases - including type A in 11% of cases, type AB in 28%, type B1 in 17%, type B2 in 29%, and type B3 in 14% -, and thymic carcinoma in 31 (11%) of cases. Complete resection was achieved in 81% of patients. Masaoka-Koga stage was stage I in 29% of cases, IIA in 21%, IIB in 21%, III in 18%, and IVA/B in 11%. Decision of the MTB was consistent with guidelines in 221 (92%) assessable cases. Clinical situations for which PORT was indicated in accordance with guidelines (84 cases) were thymoma/R1 resection (30 patients), thymoma/R0 resection/stage III (22 patients), thymoma/R0 resection/stage IIB/type B2/B3 histology (11 patients), thymic carcinoma/R1 resection (6 patients), thymic carcinoma/R0 resection (13 patients), thymoma/R0 resection/stage IIA/type B3 histology (2 patients). Inconsistencies between decision of the MTB and guidelines – 20 (8%) cases - consisted of abstention related to poor general condition (10 patients), carcinoid histology (2 patients), and discordance in staging (1 patient), and of delivery of radiotherapy related to peroperative tumor fragmentation (2 patients); for 5 patients who received PORT, a clear explanation for inconsistency with guidelines was not found, but those cases actually corresponded to those in a “grey zone” of guidelines. MTB decision for PORT was actually implemented for 99 (85%) of patients; most frequent reason for not delivering radiotherapy was prolonged delay since surgery.

Conclusion:
Our data provide with a unique insight into the decision-making process for PORT in thymic epithelial tumors, highlighting the need for a systematic discussion at an expert MTB, while stressing the value of current available guidelines.

Background:
Sunitinib is active in patients with recurrent thymic carcinoma (TC). We have previously reported an objective response rate of 26% and disease control rate (partial response and stable disease) of 91% in patients with TC when sunitinib is administered at a dose of 50 mg once daily for 4 weeks followed by 2 weeks off (4/2 dosing schedule). Grade 3 or 4 treatment-related adverse events (TEAEs) occurring in more than 10% of patients included fatigue, oral mucositis and lymphocytopenia (20% each), and hypertension (13%). Grade 3 decrease in left ventricular ejection fraction (LVEF) was observed in 8% of patients. Alternative dosing schedules have been evaluated in solid tumors to improve tolerability. As part of an ongoing phase II study (NCT01621568), we evaluated the clinical activity and tolerability of sunitinib in patients with TC using a 2-weeks-on/1-week-off (2/1) dosing regimen.

Methods:
Patients with progressive TC after at least one prior platinum-containing chemotherapy regimen, measurable disease, and adequate end organ function were enrolled and received sunitinib at a dose of 50 mg orally once daily using a 2/1 schedule until disease progression or development of intolerable adverse events. The primary objective was evaluation of response rate. Tumor assessments were performed every 6 weeks using RECIST version 1.1 and toxicity was assessed every 3 weeks using CTCAE version 4.0. Exploratory correlative studies including evaluation of immune cell subsets will be reported separately.

Results:
Between July 8, 2014 and January 14, 2016, 15 patients were enrolled. Median age was 62 years (range, 41-76), and 33% were male. A median of 4 (range, 1 – 33+) cycles of sunitinib was administered. Among 13 evaluable patients, there was 1 (8%) partial response, 11 (85%) stable disease and 1 (8%) progressive disease. After a median follow-up of 16 months, the median progression-free survival was 5 months and median overall survival was 16 months. Grade 3 or 4 TEAEs occurring in more than 10% of patients included lymphocytopenia (40%), neutropenia and leucopenia (20% each), thrombocytopenia and oral mucositis (13% each). Grade 3 decrease in LVEF was observed in 1 (7%) patient.

Conclusion:
Sunitinib, administered using a 2/1 dosing schedule, has clinical activity in patients with TC, and the frequency of clinically significant TEAEs (fatigue, mucositis, hypertension) is acceptable. Studies are ongoing to identify novel immunological biomarkers of activity.

Background:
Avelumab (MSB0010718C) is a fully human, IgG1 anti-PD-L1 antibody under clinical development. We report safety and clinical activity in patients with relapsed TETs enrolled in a phase I trial (NCT01772004).

Methods:
Patients previously treated with one or more standard therapies, no prior immune checkpoint inhibitors, and with no history of autoimmune disease were eligible. Treatment consisted of avelumab at doses of 10-20 mg/kg iv q2 weeks until disease progression or toxicity. Responses were assessed q6 weeks by RECIST 1.1. Correlative studies included evaluation of tumor cell PD-L1 expression and peripheral blood immune subset analysis.

Results:
7 patients with thymoma and 1 with thymic carcinoma (TC) were treated with avelumab; 3 patients with thymoma (2 B3, 1 B2/B3) received avelumab 20 mg/kg; 4 patients with thymoma (1 B1, 3 B2) and 1 TC received 10 mg/kg. Two (29%) patients with thymoma had a confirmed partial response (PR;1 at 20 mg/kg, and 1 at 10 mg/kg), 2 (29%) had unconfirmed PRs, 2 (29%) stable disease (SD) and 1 (14%) progressive disease; the TC patient had SD. Most adverse events (AEs) were mild (grade 1 or 2). Grade 3 and 4 AEs were observed in 3 (38%) patients each, and included potential immune-related AEs (irAEs) in 5 cases. irAEs resolved completely with oral steroids in 3 patients, and incompletely in 1 patient. One patient required cyclosporine A for treatment of irAEs. All 4 responders experienced irAEs (myositis in 3 patients, all after 1 dose of avelumab, and enteritis in 1 patient). Pre- and post-treatment tumor biopsies were available for analysis of PD-L1 expression and intratumoral immune infiltrates from three patients treated at 20 mg/kg. In one case the post-treatment biopsy showed necrotic tissue with no viable tumor. In the other two cases diffuse, membranous PD-L1 staining of epithelial cells was seen in both pre- and post-treatment biopsies. The immune infiltrate consisted of immature T cells in pre-treatment tumor samples in both cases. The post-treatment biopsy showed continued presence of immature T cells in one case and a mature CD8+ T cell phenotype in the other case. Decreased CTLA4+ regulatory T cells and decreased ratio of granulocytic vs. monocytic myeloid-derived suppressor cells was seen post-treatment at the 20mg/kg dose.

Conclusion:
Avelumab is active in patients with recurrent thymoma. Strategies need to be developed to reduce the risk of development of irAEs in response to immune checkpoint inhibitor therapy in patients with thymoma.

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Background:
[18]F-Fluorodeoxy glucose positron emission tomography (FDG- PET) is thought to be useful for predicting the histologic grade in thymic epithelial tumors (TETs). Although there have been many reports on the use of FDG-PET for evaluating TETs, no previous studies have included only resected cases. Therefore, we investigated the relationship between the degree of FDG-uptake in the tumor and either the WHO histologic subtype or the tumor stage in patients with resected TETs.

Methods:
We retrospectively reviewed FDG-PET findings in 112 patients with TETs (92 with thymomas and 20 with thymic carcinomas) resected at 2 institutes in Japan. The Spearman rank correlation coefficient was used to assess the association between the maximum standardized uptake value (SUV max) in the tumor and both the histologic subtype and tumor stage. The cut-off value of SUV max for differentiating thymoma from thymic carcinoma was calculated using a receiver operating characteristic (ROC) curve analysis.

Results:
The Table shows the relationship between SUV max in the tumor and the WHO histologic subtype. SUV max according to each tumor stage was 3.9 ± 1.7 (mean ± SD) in stage I (n = 89), 4.7 ± 1.7 in stage II (n = 3), 7.4 ± 5.3 in stage III (n =11), and 7.6 ± 3.9 in stage IV (n = 9). SUV max was strongly related to both the WHO histologic subtype and tumor stage (Spearman rank correlation coefficient = 0.485 and 0.432; p = 0.000 and 0.000, respectively). The optimal cut-off value of SUV max for differentiating thymoma from thymic carcinoma was 4.6, with a sensitivity of 80% and a　specificity of 70%.

		SUV max
~Histologic subtype~	No. of patients	~Mean ± SD~	Range
A	12	~3.5 ± 1.3~	~1.3 – 6.3~
AB	45	~3.5 ± 1.3~	[1.2 – 6.9]
B1	19	~4.1 ± 0.9~	[2.5 – 6.5]
B2	10	[4.2 ± 1.0]	[2.7 – 5.9]
B3	6	[4.8 ± 2.6]	[2.4 – 8.6]
Thymic carcinoma	20	[8.0 ± 4.7]	[3.0 – 21.8]
Total	112	[4.5 ± 2.8]	[1.2 – 21.8]

Conclusion:
Our results suggest that FDG-PET is useful for differentiating thymoma from thymic carcinoma. Further studies will be needed to assess other potential clinical applications of FDG-PET for the evaluation of TETs.

Background:
The treatment of patients with recurrent thymic tumors remains uncertain due to limited data because of the rare nature of this disease. This retrospective analysis was conducted to investigate clinical characteristics, outcomes and possible prognostic factors of patients presenting with a first recurrence of thymic tumors.

Methods:
107 patients with thymic neoplasms registered as C37 by ICD10 coding at Guy’s Hospital during the 2007-2016 period with first recurrence following primary treatment were selected and retrospectively reviewed via descriptive analysis. Differences in survival were assessed using Kaplan-Meier analysis and uni & multivariate Cox proportional hazards regression analyses.

Results:
25 patients (14 male & 11 female) with a median age of 51 years (range 36-80 years) experienced a first recurrence of thymoma (20 patients – 80%) or thymic carcinoma (5 patients – 20%) with a median time from diagnosis of 36 months (range, 7-270). At diagnosis, modified Masaoka disease stage was IIA/IIB/IIIA/IIIB/IVA/IVB in 4/0/8/2/6/5 patients; 18 patients’ (72%) primary resection was R0/R1/R2 in 11/3/4 patients; 9 patients (36%) received radiotherapy; 19 received chemotherapy (76%); CAP (n=10) and platinum-etoposide (n=6) regimens. At first relapse, 19 patients (76%) had thoracic recurrence and 6 patients (24%) extrathoracic recurrence. Nine patients (26%) underwent redo surgery, 3 of which recieved chemotherapy prior to resection. Overall resection status was 2/5/1 (1 patient’s data is not yet assessable) R0/R1/R2. Chemotherapy was administered in 17 patients (68%) with a median cycle of 4 (range, 1-6): 16 patients received combination chemotherapy consisting of platinum etoposide (n=10) or cisplatin-anthracycline based (CAP/CAV/AC n=5). Dose reduction and withdrawal were reported in 3 (18%) and 7 (41%) patients, respectively. In 4 out of these 7 patients withdrawal was due to PD; disease control rate (=CR+PR+SD) was 67% (in 10 out of 15 assessable patients). Three patients (12%) received radiotherapy of which one was treated exclusively with radiotherapy. Time to progression since the first recurrence was 12 months (range 2-52 months); in 16 patients extrathoracic recurrence was seen in 4 patients (25%) and thoracic in 12 patients (75%). Eight recurring patients (50%) received further chemotherapy. With a median follow-up of 32.5 months, 19 patients (75%) are alive and 2 (8%) disease-free; median OS has not been reached, median PFS was 29.5 months (range, 26.3-33.2). Analysis of possible prognostic factors will be presented.

Conclusion:
Patients with first recurrence of thymic tumors may benefit from combination chemotherapy and surgery when feasible.

Background:
Stage III TET represents a heterogeneous population and their optimal approach remains unclear; most of the available literature is composed of small series spanned over extended periods of time. RYTHMIC (Réseau tumeurs THYMiques et Cancer) is a French nationwide network for TET with the objective of territorial coverage by regional expert centers and systematic discussion of patients management at national tumor board. We reviewed our experience in stage III thymic tumors in order to evaluate the value of tumor board recommendations and multidisciplinary approach.

Methods:
We conducted a retrospective analysis of patients (pts) with stage III TET discussed at the RYTHMIC tumor board from January 2012 to December 2015. Clinical, pathologic and surgical data were prospectively collected in a central database. Survival rates were based on Kaplan-Meier estimation. Cox proportional hazard models were used to evaluate prognostic factors for disease free survival (DFS) and overall survival (OS).

Results:
150 pts were included in the analysis. Median age was 64 years [18 – 91], 56% males, thymoma A-B2/ B3-thymic carcinoma in 52% and 47% respectively; 12% presented with autoimmune disorder (76% myasthenia). Local treatment was surgery in 134 pts (90%) followed by radiotherapy (RT) in 90 pts; 26 pts received preoperative chemotherapy (CT). Complete resection rate (R0) was 53%. Among 38 pts considered non-surgical candidates at diagnosis, 26 pts became resectable after induction CT with a R0 rate of 58%; 12 pts received CT-RT and/or CT as primary treatment. Recurrence rate was 38% (n=57), first sites were pleural (n=32) and lung (n=12). The 5-year OS and DFS were 88% and 32% respectively. Gender (HR: 0.2 [95%CI 0.04 - 0.97] p=0.04), histology (HR: 0.19 [95%CI 0.05 - 0.70] p=0.02) and surgery (HR: 0.4 [95%CI 0.01 - 0.20] p<0.001) as primary treatment modality were significant prognostic factors for OS in multivariate analysis. Histology (HR: 0.5 [95%CI 0.30 - 0.90] p=0.02) and adjuvant RT (HR: 0.4 [95%CI 0.20 – 1.00] p=0.05) were significantly associated with DFS. Completeness of resection was not associated with survival in our cohort.

Conclusion:
Surgery followed by radiotherapy improves outcome irrespectively of R0. Stage III TET not candidate to surgery should be reassessed for resection after induction chemotherapy.

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