Prognostic model of survival for typical bronchial carcinoid tumours: analysis of 1109 patients on behalf of the European Association of Thoracic Surgeons (ESTS) Neuroendocrine Tumours Working Group

Filosso, Pier Luigi; Guerrera, Francesco; Evangelista, Andrea; Welter, Stefan; Thomas, Philippe; Moreno, Paula; Rendina, Erino Angelo; Venuta, Federico; Ampollini, Luca; Brunelli, Alessandro; Stella, Franco; Nosotti, Mario; Raveglia, Federico; Larocca, Valentina; Rena, Ottavio; Margaritora, Stefano; Ardissone, Francesco; Travis, William D.; Sarkaria, Inderpal S.; Sagan, Dariusz; Yuste, Mariano García; Lim, Eric; Papagiannopoulos, Kostas; Asamura, Hisao

doi:10.1093/ejcts/ezu495

Cited by 73 publications

(62 citation statements)

References 19 publications

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“…Tumour staging for PCs is recommended according to the UICC-TNM system; however, refinement of descriptive categories is needed. Nodal status (N) and its impact on prognosis has been the most studied and N1 or N2 disease is associated with poorer outcomes [31, 32]. The prognostic implications of tumour size (T), pleural invasion, and multicentricity remains to be better outlined [31].…”

Section: Classification and Diagnosticsmentioning

confidence: 99%

Unmet Medical Needs in Pulmonary Neuroendocrine (Carcinoid) Neoplasms

et al. 2018

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Pulmonary carcinoids (PCs) display the common features of all well-differentiated neuroendocrine neoplasms (NEN) and are classified as low- and intermediate-grade malignant tumours (i.e., typical and atypical carcinoid, respectively). There is a paucity of randomised studies dedicated to advanced PCs and management principles are drawn from the larger gastroenteropancreatic NEN experience. There is growing evidence that NEN anatomic subgroups have different biology and different responses to treatment and, therefore, should be investigated as separate entities in clinical trials. In this review, we discuss the existing evidence and limitations of tumour classification, diagnostics and staging, prognostication, and treatment in the setting of PC, with focus on unmet medical needs and directions for the future.

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Section: Classification and Diagnosticsmentioning

confidence: 99%

Unmet Medical Needs in Pulmonary Neuroendocrine (Carcinoid) Neoplasms

et al. 2018

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“…In that study, adenocarcinoma histology, female gender, N0 status, tumor size less than 3 cm and age less than 70 years were predictive of improved survival. A similar study developed a nomogram to predict survival following resection of typical carcinoid tumors, using data from a multi-center European registry 21 .…”

Section: Commentmentioning

confidence: 99%

A Nomogram to Predict Recurrence and Survival of High-Risk Patients Undergoing Sublobar Resection for Lung Cancer: An Analysis of a Multicenter Prospective Study (ACOSOG Z4032)

Kent

Mandrekar

Landreneau

et al. 2016

The Annals of Thoracic Surgery

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Background Individualized prediction of outcomes may help with therapy decisions for patients with non-small cell lung cancer (NSCLC). We developed a nomogram by analyzing 17 clinical factors and outcomes from a randomized study of sublobar resection for NSCLC in high-risk operable patients. The study compared sublobar resection alone, to sublobar resection with brachytherapy. There were no differences in primary and secondary outcomes between the study arms, and were thus combined for this analysis. Methods The clinical factors of interest (considered as continuous variables) were assessed in a univariate Cox Proportional Hazards model for significance at the 0.10 level for their impact on overall survival (OS), local recurrence free survival (LRFS) and any recurrence free survival (RFS). The final multivariable model was developed using a stepwise model selection. Results 173 of 212 patients had complete data on all 17 risk factors. Median (range) follow-up was 4.94 (0.04–6.22) years. The 5-year OS, LRFS and RFS were 58.4%, 53.2% and 47.4% respectively. Age, baseline DLCO % and maximum tumor diameter were significant predictors for OS, LRFS and RFS in the multivariable model. Nomograms were subsequently developed for predicting 5-year OS, LFRS and RFS. Conclusions Age, baseline DLCO% and maximum tumor diameter significantly predicted outcomes after sublobar resection. Such nomograms may be helpful for treatment planning in early stage NSCLC and to guide future studies.

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“…Accordingly, TC is deemed to be a low-grade malignant tumor with longer life expectation and time to recurrence, AC an intermediate-grade malignant tumor with more aggressive clinical course, somewhat unpredictable clinical behavior and shorter time to recurrence, and LCNEC and SCC high-grade malignant tumors with dismal prognosis, challenging therapy options and, often, difficulties in reliably distinguishing from each others, either pathologically, genetically or clinically 1,4,8,[14][15][16][17][18][19] .…”

Section: Approaching Lung Netmentioning

confidence: 99%

What clinicians are asking pathologists when dealing with lung neuroendocrine neoplasms?

Pelosi

Fabbri

Cossa

et al. 2015

Seminars in Diagnostic Pathology

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Prognostic model of survival for typical bronchial carcinoid tumours: analysis of 1109 patients on behalf of the European Association of Thoracic Surgeons (ESTS) Neuroendocrine Tumours Working Group

Abstract: We presented and validated a promising prognostic model for TC survival, showing good calibration and discrimination ability. Further analyses are needed and could be focused on an external validation of this model.

Cited by 73 publications

References 19 publications

Unmet Medical Needs in Pulmonary Neuroendocrine (Carcinoid) Neoplasms

Unmet Medical Needs in Pulmonary Neuroendocrine (Carcinoid) Neoplasms

A Nomogram to Predict Recurrence and Survival of High-Risk Patients Undergoing Sublobar Resection for Lung Cancer: An Analysis of a Multicenter Prospective Study (ACOSOG Z4032)

What clinicians are asking pathologists when dealing with lung neuroendocrine neoplasms?

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