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Table 1.

Demographics of the final dataset.

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Table 1 Expand

Fig 1.

LCA model output.

A: Probabilistic distribution of patients by latent class. Note that this represents the probability of a patient being classified in each subgroup, and is not equivalent to the distribution of cases in this study (Table 3). B: Outcome probabilities for each class. Each bar represents the probability of a parameter being positive in a particular class. Bars are colour coded based on the following groupings: HR/HER2 subtype (blue), distant organ metastases (orange), and lymph node metastases (green).

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Fig 1 Expand

Table 2.

LCA model optimization.

Note that BIC is minimized with 4 classes.

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Table 2 Expand

Table 3.

Latent class compositions.

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Table 3 Expand

Fig 2.

DAG plots for each latent class.

Arrow thickness represents the strength of association, which is inversely proportional to BIC. Dotted lines represent associations which are ≤5% of the strength of the strongest association. Node colours are grouped as follows: host features (blue), tumour biology (orange), disease burden (green), and overall survival (grey). Red boxes indicate interactions which were not validated by the SEM regression (p > 0.001). RMSEA = root mean square error of approximation; SRMR = standardized root mean square residual; “surv” = survival; “insur” = insurance.

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Fig 2 Expand