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Applications and Case Studies

Accommodating Time-Varying Heterogeneity in Risk Estimation under the Cox Model: A Transfer Learning Approach

ORCID Icon, & ORCID Icon
Pages 2276-2287 | Received 10 Aug 2022, Accepted 26 Apr 2023, Published online: 26 Jun 2023

Figures & data

Fig. 1 Estimation biases for coefficients β1, β2, and β3 (Panel A), as well as cumulative baseline hazards at times 0.6 and 1.2 (Panel B) over 100 Monte Carlo simulations. H1=Ĥ0(0.6) and H2=Ĥ0(1.2). The dotted gray line shows the place where bias equals zero.

Fig. 1 Estimation biases for coefficients β1, β2, and β3 (Panel A), as well as cumulative baseline hazards at times 0.6 and 1.2 (Panel B) over 100 Monte Carlo simulations. H1=Ĥ0(0.6) and H2=Ĥ0(1.2). The dotted gray line shows the place where bias equals zero.

Fig. 2 Boxplots for absolute personalized prediction error of Trans-Cox and other existing methods in different simulation settings at time 0.6 (APPE1) and 1.2 (APPE2). The results are summarized over 100 Monte Carlo datasets.

Fig. 2 Boxplots for absolute personalized prediction error of Trans-Cox and other existing methods in different simulation settings at time 0.6 (APPE1) and 1.2 (APPE2). The results are summarized over 100 Monte Carlo datasets.

Fig. 3 The estimated cumulative baseline hazard (Panel A) and the survival curves (Panel B) for Trans-Cox (green) and Cox-Both (blue) in comparison to the true curves (red) over 100 Monte Carlo experiments. For survival curves, the covariates are fixed at X=(0.5,1,0.1,0.5,0.5).

Fig. 3 The estimated cumulative baseline hazard (Panel A) and the survival curves (Panel B) for Trans-Cox (green) and Cox-Both (blue) in comparison to the true curves (red) over 100 Monte Carlo experiments. For survival curves, the covariates are fixed at X=(0.5,1,0.1,0.5,0.5).

Fig. 4 Summary of the patients’ characteristics of the MDA and NCDB cohorts.

Fig. 4 Summary of the patients’ characteristics of the MDA and NCDB cohorts.

Table 1 Analysis results of the MDA and NCDB cohorts.

Fig. 5 The estimated survival curves using different methods for patients with (left panel) or without (right panel) receiving trimodality treatment. Other characteristics were specified as: age 50 years old, grade III, Black race, and stage IIIC.

Fig. 5 The estimated survival curves using different methods for patients with (left panel) or without (right panel) receiving trimodality treatment. Other characteristics were specified as: age 50 years old, grade III, Black race, and stage IIIC.

Fig. 6 Evaluation of the prediction performance of four methods using C-index (Panel A), Uno’s C-index (B), AUC (C), and personalized risk prediction error (D).

Fig. 6 Evaluation of the prediction performance of four methods using C-index (Panel A), Uno’s C-index (B), AUC (C), and personalized risk prediction error (D).
Supplemental material

Supplemental Material

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