ABSTRACT
【Objective】 To explore the factors influencing the survival and prognosis of patients with bladder urothelial carcinoma (BUC) after surgical treatment, and to establish an artificial intelligence algorithm to predict the effects of different surgical regimens. 【Methods】 BUC patients treated with surgery during Jan.2007 and Jan.2019 in The Second Hospital of Dalian Medical University and Nanfang Hospital of Southern Medical University were enrolled. The complete clinical and follow-up data were collected. Deep neural network (DNN) was used to establish an artificial intelligence algorithm model. A prediction model of survival and prognosis was established, and the influencing factors of survival were explored and ranked by the artificial intelligence algorithm. 【Results】 A total of 832 patients were involved, including 438 (52.64%) treated in The Second Hospital of Dalian Medical University, and 394 (47.36%) treated in Nanfang Hospital of Southern Medical University. Of all cases, 579 (69.6%) were non-muscle invasive bladder cancer, and 253 (30.4%) were muscle invasive bladder cancer. Transurethral resection of bladder tumor was conducted in 539 (64.8%) cases, partial cystectomy in 66 (7.9%) cases, and total cystectomy in 227 (27.3%) cases. The data of patients treated in Second Hospital of Dalian Medical University were used for DNN modeling, and the data of patients treated in Nanfang Hospital of Southern Medical University were used for external verification after modeling. Finally, it was concluded that the factors affecting survival and prognosis were T stage, pathological grade, hypertension or cardiovascular and cerebrovascular disease, hemoglobin, blood calcium, smoking, albumin, lymphocytes, age, ratio of albumin/globulin, operation method, N stage, and creatinine clearance rate in descending order. The model could be used for preoperative prediction. 【Conclusion】 Through DNN modeling and external verification, the influencing factors of postoperative survival can be predicted for patients with bladder cancer, and the surgical effects can also be predicted before operation. The model can provide artificial intelligence algorithm support for the selection of surgical methods and postoperative follow-up plans.
ABSTRACT
Objective:To analyze the clinical features of absolute incidental prostate cancer (AIPCa) and pseudo-incidental prostate cancer (PIPCa).Methods:Between January 2013 and October 2019, 52 male patients who were diagnosed as incidental prostate cancer (IPCa) with their postoperative pathological examination in our center were included. None of them had any evidence of prostate cancer before. Their median age was 77.5(ranging 55-93) years old. 48 cases underwent PSA examination. The median tPSA was 6.7 (ranging 1-46) ng/ml, except 1 case tPAS>100ng/ml. The median IPSS score was 27.7(ranging 12-35). 48 cases accepted prostatic ultrasound examination. The median prostate volume was 38.6 (ranging 2.3-130.2)ml. Among them, 13 patients underwent transurethral resection of the prostate (TURP), 24 patients underwent transurethral enucleation and resection of the prostate(TUERP), 15 patients underwent radical cystoprostatectomy(RCP). According to the patients′ preoperative examination, AIPCa and PIPCa were redefined. Clinical characteristics, postoperative pathology and follow-up of the two groups were compared and analyzed.Results:There was no significant difference in age, IPSS score, tPSA, T stage and Gleason score between the operation methods groups except for prostate volume and resection ration of prostate ( P>0.05). Among those group, the sequence of prostatic resection ration was RCP>TUERP>TURP( P<0.001). There was no significant difference in age, IPSS score, prostate volume, proportion of T 1b and Gleason score between AIPCa and PIPCa groups. However, the analysis showed higher tPSA(14.68 ng/ml vs. 3.14 ng/ml) in PIPCa ( P<0.001). With a mean follow-up of 33 months(ranging 6-78 months), 23.8%(5/21) patients in AIPCa group and 45.2%(14/31) patients in PIPCa group were found to have increased PSA and underwent radical prostatectomy or androgen deprivation therapy in the follow-up. There was no metastasis or death in AIPCa group, while 2 patients had bone metastasis and 1 patient died of prostate cancer in PIPCa group. Conclusions:According to the indication of prostate biopsy, PIPCa and AIPCa were defined. PIPCa has a relatively poor prognosis, some of them may be missed diagnosis and clinical underestimation. In order to avoid missed diagnosis before operation, we should strictly define IPCa and follow the indications of biopsy, emphasize the reference value of PSA in tumor screening and biopsy, and careful handle the negative results of biopsy when PSA is abnormal.