Prognosis prediction model of metastatic castration-resistant prostate cancer patients in abiraterone treatment and establishment method and application of prognosis prediction model
A technology for castration resistance and prostate cancer, applied in computer-aided medical procedures, health index calculation, medical informatics, etc., can solve the problem of inability to effectively predict the prognosis model of mCRPC patients
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Embodiment 1
[0046] Example 1 Establishment of a nomogram model for predicting the prognosis of patients with metastatic castration-resistant prostate cancer in first-line abiraterone therapy
[0047] The nomogram for predicting the PSA-free progression time of patients with metastatic castration-resistant prostate cancer in the first-line abiraterone treatment of the present invention, its establishment method comprises the following steps:
[0048] (1) Collected 122 patients who were diagnosed with metastatic prostate cancer and progressed to metastatic castration-resistant prostate cancer (mCRPC) in West China Hospital of Sichuan University from 2014 to 2019. All patients received first-line abiraterone therapy (1000mg / day, combined with prednisone 10mg / day) after the diagnosis of mCRPC. After a median follow-up of 27.9 months, 100 (82.0%) patients eventually developed PSA progression;
[0049] (2) Collect the clinical and pathological data of the patients as follows: age, Gleason score ...
Embodiment 2
[0057] The prognostic model established in embodiment 2 verification
[0058] After the prognostic prediction model of PSA-free progression time in abiraterone treatment for mCRPC patients was established, 37 patients in the validation group were used to validate the model. The verification of the model was completed through C-index index and consistency curve analysis. The specific steps are as follows:
[0059] (1) The C-index index can reflect the prediction accuracy of the model in predicting the time of PSA-free progression or the ability to distinguish the prognosis. C-index was calculated by R software.
[0060] The C-index of the prognosis model for predicting PSA-free progression time of the present invention is 0.767, showing that the model has good prediction accuracy and discrimination.
[0061] (2) The consistency curve is used to reflect the consistency between the predicted probability of PSA progression and the actual proportion of PSA progression in the ver...
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