Phenotypic Heterogeneity of Potentially Curable Non–Small-Cell Lung Cancer: Cohort Study with Cluster Analysis Lama Sakr, MD, MSc, FRCPC, David Small,

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Phenotypic Heterogeneity of Potentially Curable Non–Small-Cell Lung Cancer: Cohort Study with Cluster Analysis Lama Sakr, MD, MSc, FRCPC, David Small, MD, FRCPC, Goulnar Kasymjanova, MD, PhD, Samy Suissa, PhD, Pierre Ernst, MD, MSc, FRCPC Journal of Thoracic Oncology Volume 10, Issue 5, Pages 754-761 (May 2015) DOI: 10.1097/JTO.0000000000000505 Copyright © 2015 International Association for the Study of Lung Cancer Terms and Conditions

FIGURE 1 Dendrogram indicating the four-cluster model. The cutoff line for the cluster selection process is the red line shown above. Cutting the dendrogram at this level (for the three-dimensional solution)—thereby yielding a four-cluster model—was attempted. According to the selected partitions, cluster 1 includes the groups G1–G7 (170 subjects), cluster 2 comprises G8 and G9 (48 subjects), cluster 3 includes G10–G14 (108 subjects), and cluster 4 corresponds to individuals in the group G15 (41 subjects). Journal of Thoracic Oncology 2015 10, 754-761DOI: (10.1097/JTO.0000000000000505) Copyright © 2015 International Association for the Study of Lung Cancer Terms and Conditions

FIGURE 2 Three-dimension, four-cluster model. This vertical box-plot shows the disposition of each of the four clusters, according to the three depicted dimensions. The two best dimensions that describe a particular cluster consist of those, which best discriminate between that cluster and the remaining clusters. Such dimensions should ideally have coordinate values far from 0, in either direction. Cluster 1 can be differentiated from cluster 2, using dimensions 2 and 3. Although cluster 1 has a predominantly positive axis with regard to dimension 2 and a negative axis with regard to dimension 3, cluster 2 is described by these two dimensions in opposite directions. Journal of Thoracic Oncology 2015 10, 754-761DOI: (10.1097/JTO.0000000000000505) Copyright © 2015 International Association for the Study of Lung Cancer Terms and Conditions

FIGURE 3 Multiple correspondence analysis plots for cluster 4, according to dimensions 1 and 3. This plot depicts each variable, according to the coordinate values associated with each of its categories. Dimensions 1 and 3 were selected to describe cluster 4. Taking into account the axes of dimensions 1 and 3 for this cluster, we can provide an overall description of the characteristics of individuals that constitute each cluster. With a positive axis for both dimensions 1 (vertical axis) and 3 (horizontal axis), cluster 4 includes individuals with the following characteristics: patients with stage 1A disease, presenting no weight loss, having a good performance status (0), a well-differentiated ADK and ADK in situ, with positive TTF-1 staining, low SUV uptake, and who are mainly nonsmokers, young and of female gender. Journal of Thoracic Oncology 2015 10, 754-761DOI: (10.1097/JTO.0000000000000505) Copyright © 2015 International Association for the Study of Lung Cancer Terms and Conditions

FIGURE 4 Five-year overall survival by disease stage. Journal of Thoracic Oncology 2015 10, 754-761DOI: (10.1097/JTO.0000000000000505) Copyright © 2015 International Association for the Study of Lung Cancer Terms and Conditions

FIGURE 5 Three-year overall survival rates in the four-cluster model. Journal of Thoracic Oncology 2015 10, 754-761DOI: (10.1097/JTO.0000000000000505) Copyright © 2015 International Association for the Study of Lung Cancer Terms and Conditions

FIGURE 6 Five-year overall survival rates in the four-cluster model. Journal of Thoracic Oncology 2015 10, 754-761DOI: (10.1097/JTO.0000000000000505) Copyright © 2015 International Association for the Study of Lung Cancer Terms and Conditions

FIGURE 7 Five-year disease-free survival rates in the four-cluster model. Journal of Thoracic Oncology 2015 10, 754-761DOI: (10.1097/JTO.0000000000000505) Copyright © 2015 International Association for the Study of Lung Cancer Terms and Conditions