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Fig 1.

The schematics of the decision tree and the Markov state transition model.

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Fig 1 Expand

Fig 2.

The exploration and fitting of PFS and OS curves for cCRT population in comparison with external data.

Model simulation visual PFS curve (A), OS curve (B) of sugemalimab arm and PFS curve (C), OS curve (D) of placebo arm.

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Fig 2 Expand

Fig 3.

The exploration and fitting of PFS and OS curves for sCRT population in comparison with external data.

Model simulation visual PFS curve (A), OS curve (B) of sugemalimab arm and PFS curve (C), OS curve (D) of placebo arm.

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Fig 3 Expand

Table 1.

Best fit and the values of the parameters.

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Table 1 Expand

Fig 4.

The proportion of subsequent immunotherapy and detailed treatment strategies varied with tumor histology type at progression for patients with stage III NSCLC.

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Fig 4 Expand

Table 2.

Model inputs: Base case values, ranges, and distributions for sensitivity analysis.

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Table 2 Expand

Table 3.

Base-case analysis results without or with PAP.

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Table 3 Expand

Fig 5.

Tornado diagram of one-way deterministic sensitivity analysis (DSA) of sugemalimab vs. placebo.

DSA for cCRT population without PAP. cCRT, concurrent chemoradiotherapy; PAP: Patient assistance program.

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Fig 5 Expand

Fig 6.

Tornado diagram of one-way deterministic sensitivity analysis (DSA) of sugemalimab vs. placebo.

DSA for sCRT population without PAP. sCRT, sequential chemoradiotherapy; PAP: Patient assistance program.

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Fig 6 Expand

Fig 7.

Cost-effectiveness acceptability curves of sugemalimab vs. placebo with and without PAP.

PAP: Patient assistance program.

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Fig 7 Expand

Table 4.

Results of scenario analyses for cCRT population.

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Table 4 Expand

Table 5.

Results of scenario analyses for sCRT population.

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Table 5 Expand

Table 6.

Validation of modeled PFS and OS data using updated GEMSTONE-301 and external data.

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Table 6 Expand