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MA09 - Lung Cancer Surgical and Molecular Pathology (ID 908)
- Event: WCLC 2018
- Type: Mini Oral Abstract Session
- Track: Pathology
- Presentations: 1
- Coordinates: 9/24/2018, 15:15 - 16:45, Room 202 BD
MA09.03 - Multiple Pathological Variables Predict Efficacy of Adjuvant Chemotherapy in Primary Lung Adenocarcinoma (ID 13761)
15:25 - 15:30 | Author(s): Grace Rake
Adjuvant chemotherapy has become established as a vital complement to surgery over the last decade, and improves survival by targeting micrometastatic disease which is clinically inaparrent at the time of surgery. However, in comparison to other common malignancies, the guidelines for the administration of adjuvant chemotherapy in lung cancer are rudimentary, being based solely upon clinical stage II and above at the time of surgery. We set out to discover pathological factors with the potential to better identify patients who are likely to benefit from this vital therapy.a9ded1e5ce5d75814730bb4caaf49419 Method
662 cases of primary lung adenocarcinoma treated with surgery with curative intent were identified from 2005-2014; 109 received adjuvant chemotherapy. Comprehensive survival/recurrence data, pathological data, and treatment history data were collected. Detailed histopathological data (growth pattern, vascular invasion, pleural stage) were collected by review of scanned histopathological images.
Multivariate Cox regression survival models were used to identify interactions between clinicopathological variables and adjuvant chemotherapy. A propensity score matching approasch was used to reduce selection biases in the data.4c3880bb027f159e801041b1021e88e8 Result
The existing stage criteria for the recommendation of adjuvant chemotherapy are stage pN1/2 and size>40mm; only nodal invasion interacts with chemotherapy in an OS model (interaction term HR=0.67 P=0.017). However, signficant interactions are seen with predominant growth pattern (HR=0.47 P=0.001 ), pleural stage (HR=0.62 P=0.002 ), and vascular invasion (HR=0.56 P=0.033).
We reduced selection bias by balancing treated and untreated groups by propensity matching for all prognostic variables. In the matched dataset, patients with predominantly in situ tumours experience no benefit of chemotherapy (HR=1.81 P=0.18), while higher-grade cases show substantial benefit (HR=0.53 P=0.01). Similar benefits were seen for patients with increasing pleural stage and vascular invasion.
In a multivariate model designed to identify which variable(s) had the most ability to predict treatment efficacy, only tumour growth pattern showed a significant interaction with chemotherapy treatment (HR=0.51 P=0.01 ).8eea62084ca7e541d918e823422bd82e Conclusion
We find that the existing stage-based criteria for adjuvant chemotherapy can be much improved. Low-grade cases experienced only negative effects of chemotherapy, while higher-grade cases showed a benefit. Pleural stage and vascular invasion were also significantly predictive. We suggest that the current criteria may be leading to substantial over- and under-treatment. A nuanced algorithm for the identification of patients likely to benefit from chemotherapy, which includes these additional pathoogical measures, may significantly improve patient outcomes. This would be especially impactful to the majority of surgical patients for whom no personalised therapy is as yet available.6f8b794f3246b0c1e1780bb4d4d5dc53
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