How to adjust kaplan-meier curves for confounding factors and get p value?

Question

[Manuel]

Following the tutorial from stanford uni , if kaplan meyer curves do not contain significant p value but the coxph for the same variable contains, the curves should adjusted for possible confounding factors. C1, C2, C3 and C4 correspond to other classification of the disease by gene expression.

cox <- coxph(Surv(TIME_TO_DEATH_FROM_SURGERY, Morte.S.N) ~ Histologia +  Transcriptomic + 
Genomic + Sexo +Tratamento.adjuvante , data = clinical_data_clean)
ggadjustedcurves(cox, variable = 'Transcriptomic', data = clinical_data_clean)

Is is possible to add a p value for the second graph with the curves adjusted for confounding factors? And could you provide some feedback about the correctness of this analysis?

Thank you and best regards.