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T. Edwards
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MA10 - Facing the Real World: New Staging System and Response Evaluation in Immunotherapy (ID 393)
- Event: WCLC 2016
- Type: Mini Oral Session
- Track: Radiology/Staging/Screening
- Presentations: 1
- Moderators:P. Kosmidis
- Coordinates: 12/06/2016, 14:20 - 15:50, Stolz 2
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MA10.03 - Investigating the Potential Utility of the Alternative 9th Edition IASLC Nodal Staging Classification in NSCLC (ID 4491)
14:32 - 14:38 | Author(s): T. Edwards
- Abstract
- Presentation
Background:
The IASLC lung cancer staging project recently published recommendations for the 8th edition of the TNM classification of lung cancer. This recommends the same N descriptors be used, however, further analysis of an alternative system (proposed 9[th] Edition) was recommended. The aim of this retrospective study was to assess the utility of this proposed nodal staging system at a large UK tertiary lung cancer centre.
Methods:
Patients who underwent surgical resection for non-small cell lung cancer between 2011-2014 (allowing minimum of 2 years follow-up) were identified from a prospective database (n=1308). Stratification of pathological N-stage as per the IASCLC proposal was performed: N0, single station N1 (N1a), multi-statin N1 (N1b), single station N2 without N1 involvement – skip metastases - (N2a1), single station N2 with N1 involvement (N2a2), multi-station N2 (N2b) and N3. Survival data was obtained from national death registries.
Results:
There a significant effect of N-stage on mortality using Cox proportional hazards regression analysis, using pN0 (n=848) as the reference group and adjusting for sex, age and histology (table 1). There appears to be similar survival outcomes between multi-station N1 (pN1b) and single station N2 skip metastases (pN2a1), and single station N2 with N1 involvement (pN2a2) and multi-station N2 (pN2b).Table 1.
N-stage Hazard Ratio 95% CI p-value pN1a (n=146) 1.68 (1.26, 2.26) 0.001 pN1b (n=55) 2.25 (1.49, 3.39) <0.001 pN2a1 (n=50) 2.24 (1.46, 3.45) <0.001 pN2a2 (n=81) 2.94 (2.15, 4.03) <0.001 pN2b (n=67) 2.99 (2.09, 4.27) <0.001
Conclusion:
The proposed 9[th] edition N-staging classifications appear to add additional insight into prognosis. However, interpretation is limited by the small numbers of patients within the pN1/pN2 sub-groups. 65% of this large cohort were pN0 and acted as the reference group and a further 5% were pNx as no nodes were submitted. Furthermore, the accuracy of pN-staging is reliant on the quality of intra-operative lymph node sampling. Although significant improvements have been made in this timeframe at our centre (published previously), any sub-optimal performance has the potential to affect the validity of the results, particularly if multi-station N2 disease is missed.
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P1.05 - Poster Session with Presenters Present (ID 457)
- Event: WCLC 2016
- Type: Poster Presenters Present
- Track: Early Stage NSCLC
- Presentations: 1
- Moderators:
- Coordinates: 12/05/2016, 14:30 - 15:45, Hall B (Poster Area)
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P1.05-043 - Survival Following Surgical Resection of Lung Adenocarcinoma Stratified According to Morphological Sub-Type (ID 4494)
14:30 - 14:30 | Author(s): T. Edwards
- Abstract
Background:
Lung adenocarcinoma is the commonest histological sub-type of Non-small cell lung cancer (NSCLC) and a leading cause of death worldwide. Identifying factors that may influence survival or the risk of recurrence following resection of lung adenocarcinoma may inform adjuvant strategies and the intensity of surveillance programs. The aim of this study was to assess the effect of morphological sub-type on survival following surgical resection.
Methods:
Patients who underwent surgical resection for non-small cell lung cancer between 2011 and 2014 at a tertiary thoracic surgical and lung cancer centre were identified from pathological records (n=1387). Patients with adenocarcinoma (n=705) were selected and the predominant morphological subtyping was recorded. Survival data was obtained from national death registries.
Results:
Of the 705 adenocarcinomas, Acinar (n=325), Lepidic (n=133) and Solid (n=131) were the most frequent histological subtypes identified. Numbers for other subtypes were small and therefor 3 year survival was not always possible to calculate.Survival by histological subtypes
Histology No. of Deaths during follow-up 1 year survival 2 year survival 3 year survival Acinar (N=325) 93 90.5% 79.2% 68.3% Glandular (N=17) 5 94.1% - - Lepidic (N=133) 32 92.5% 84.4% 76.6% Micropapillary (N=3) 1 - - - Mixed (N=26) 9 84.6% 71.3% - Papillary (N=38) 11 78.9% 76.3% - Solid (N=131) 50 81.7% 67.1% 59.7% Unknown (N=31) 10 93.5% 71.5% -
Conclusion:
A difference in survival can be seen between the three commonest adenocarcinoma subtypes (Acinar, Lepidic and Solid) at 1, 2 and 3 years following surgical resection. Interpreting results on other sub-types is limited by small numbers. Lepidic and Solid have the best and worst survival rates respectively. Limitations include a lack of adjustment for pathological stage or co-morbidities and a lack of cancer-specific mortality data. Future studies may evaluate if the morphology of lung adenocarcinomas could have a role in defining adjuvant and surveillance strategies.
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P1.08 - Poster Session with Presenters Present (ID 460)
- Event: WCLC 2016
- Type: Poster Presenters Present
- Track: Surgery
- Presentations: 1
- Moderators:
- Coordinates: 12/05/2016, 14:30 - 15:45, Hall B (Poster Area)
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P1.08-022 - Risk Stratification Model to Predict Survival Following Surgical Resection for Lung Cancer Using Pathological Variables (ID 4495)
14:30 - 14:30 | Author(s): T. Edwards
- Abstract
Background:
The risk of lung cancer recurrence remains a significant problem following curative-intent treatment. Novel methods of calculating this risk may have potential benefits in defining adjuvant strategies and stratifying the intensity of surveillance programs. The aim of this study was to identify factors at surgical resection of NSCLC that influenced survival in attempt to develop a probability model to predict mortality.
Methods:
Pathological variables were recorded from 1311 patients undergoing surgical resection for NSCLC from 2011 to 2014 at a tertiary UK lung cancer centre. Pathological variables analysed included T-stage, N-stage, adequacy of intra-operative lymph node sampling, pleural invasion, lymphovascular invasion, extracapsular spread, histological sub-typing, extent of surgery, grade of differentiation and R status (residual disease). Survival data was obtained from national death registries and logistic regression was used to develop a probability model to predict mortality.
Results:
Table 1. Pathological predictors of survival 1 year post surgery for NSCLC Figure 1 Using the probabilities from the logistic regression model to predict one year mortality gives an AUC of 0.741. If a probability of 0.144 is used to predict whether a patient will die within one year of surgery, sensitivity is 70.0% (119/170), specificity is 67.3% (625/929), PPV is 28.1% (119/423) and NPV is 92.5% (625/676).
Conclusion:
Survival post-curative intent surgery for NSCLC is based on multiple pathological factors as described above. Further analysis of these factors will be performed in the future to determine a risk stratification model to predict patients with low versus high risk mortality post surgery. Whilst indications for adjuvant therapy are well documented, the optimal surveillance regime is not as clear. Given the heterogenous group of patients receiving surgery for NSCLC, a predictive model may be useful in determining optimal surveillance strategies.
