scholarly journals Biliary Neuroendocrine Neoplasms: Analysis of Prognostic Factors and Development and Validation of a Nomogram

2021 ◽  
Vol 11 ◽  
Author(s):  
Shengnan Zhou ◽  
Shitao Jiang ◽  
Weijie Chen ◽  
Haixin Yin ◽  
Liangbo Dong ◽  
...  
Keyword(s):  
Prognostic Factors ◽  
Survival Time ◽  
Tumor Size ◽  
External Validation ◽  
Ampulla Of Vater ◽  
Validation Dataset ◽  
Neuroendocrine Neoplasms ◽  
Seer Database ◽  
Pathological Classification ◽  
Individual Survival

BackgroundFor this study, we explored the prognostic profiles of biliary neuroendocrine neoplasms (NENs) patients and identified factors related to prognosis. Further, we developed and validated an effective nomogram to predict the overall survival (OS) of individual patients with biliary NENs.MethodsWe included a total of 446 biliary NENs patients from the SEER database. We used Kaplan-Meier curves to determine survival time. We employed univariate and multivariate Cox analyses to estimate hazard ratios to identify prognostic factors. We constructed a predictive nomogram based on the results of the multivariate analyses. In addition, we included 28 biliary NENs cases from our center as an external validation cohort.ResultsThe median survival time of biliary NENs from the SEER database was 31 months, and the value of gallbladder NENs (23 months) was significantly shorter than that of the bile duct (45 months) and ampulla of Vater (33.5 months, p=0.023). Multivariate Cox analyses indicated that age, tumor size, pathological classification, SEER stage, and surgery were independent variables associated with survival. The constructed prognostic nomogram demonstrated good calibration and discrimination C-index values of 0.783 and 0.795 in the training and validation dataset, respectively.ConclusionAge, tumor size, pathological classification, SEER stage, and surgery were predictors for the survival of biliary NENs. We developed a nomogram that could determine the 3-year and 5-year OS rates. Through validation of our central database, the novel nomogram is a useful tool for clinicians in estimating individual survival among biliary NENs patients.

scholarly journals Clinicopathological Features and Prognostic Factors of Colorectal Neuroendocrine Neoplasms

2017 ◽  
Vol 2017 ◽  
pp. 1-9 ◽  
Author(s):  
Mengjie Jiang ◽  
Yinuo Tan ◽  
Xiaofen Li ◽  
Jianfei Fu ◽  
Hanguang Hu ◽  
...  
Keyword(s):  
Prognostic Factors ◽  
Tumor Size ◽  
Cox Regression ◽  
Survival Rates ◽  
Delayed Diagnosis ◽  
Tumor Location ◽  
Neuroendocrine Neoplasms ◽  
Predictive Capacity ◽  
Pathological Classification ◽  
Biological Differences

Background. Limited research is available regarding colorectal NENs and the prognostic factors remain controversial. Materials and Methods. A total of 68 patients with colorectal NENs were studied retrospectively. Clinical characteristics and prognosis between colonic and rectal NENs were compared. The Cox regression models were used to evaluate the predictive capacity. Results. Of the 68 colorectal NENs patients, 43 (63.2%) had rectal NENs, and 25 (36.8%) had colonic NENs. Compared with rectal NENs, colonic NENs more frequently exhibited larger tumor size (P<0.0001) and distant metastasis (P<0.0001). Colonic NENs had a worse prognosis (P=0.027), with 5-year overall survival rates of 66.7% versus 88.1%. NET, NEC, and MANEC were noted in 61.8%, 23.5%, and 14.7% of patients, respectively. Multivariate analyses revealed that tumor location was not an independent prognostic factor (P=0.081), but tumor size (P=0.037) and pathological classification (P=0.012) were independent prognostic factors. Conclusion. Significant differences exist between colonic and rectal NENs. Multivariate analysis indicated that tumor size and pathological classification were associated with prognosis. Tumor location was not an independent factor. The worse outcome of colonic NENs observed in clinical practice might be due not only to the biological differences, but also to larger tumor size in colonic NENs caused by the delayed diagnosis.

Clinicopathological features and prognostic factors of colorectal neuroendocrine neoplasms.

2017 ◽  
Vol 35 (4_suppl) ◽  
pp. 572-572
Author(s):  
Mengjie Jiang ◽  
Hanguang Hu ◽  
Ying Yuan
Keyword(s):  
Prognostic Factors ◽  
Tumor Size ◽  
Cox Regression ◽  
Survival Rates ◽  
Delayed Diagnosis ◽  
Tumor Location ◽  
Neuroendocrine Neoplasms ◽  
Clinicopathological Feature ◽  
Ki 67 ◽  
Pathological Classification

572 Background: Limited research is available regarding colorectal neuroendocrine neoplasms (NENs), especially in China. The prognostic factors of colorectal NENs remain controversial. Methods: A total of 68 patients with colorectal NENs were studied retrospectively. Clinical characteristics and prognosis between colonic and rectal NENs were compared. The Kaplan-Meier method and Cox regression models were used to evaluate the capacity of various factors to predict the outcome. Results: Of the 68 colorectal NENs patients, 43 (63.2%) had rectal NENs, and 25 (36.8%) had colonic NENs. Compared with rectal NENs, colonic NENs more frequently exhibited larger tumor size ( P < 0.0001) and distant metastasis ( P < 0.0001). Colonic NENs had a worse prognosis ( P= 0.027), with 5-year overall survival rates of 66.7% vs. 88.1% compared with rectal NENs. Neuroendocrine tumors, neuroendocrine carcinomas and mixed adenoendocrine carcinomaswere noted in 61.8%, 23.5% and 14.7% of patients, respectively. According to the available data (n = 49), Ki-67 index values were ≤ 2% in 27 (39.7%) patients, ranged from 3 to 20% in 6 patients (8.8%) and were > 20% in 16 patients (23.5%). Multivariate analyses revealed that tumor location was not an independent prognostic factor ( P= 0.081), but tumor size ( P= 0.037) and pathological classification ( P= 0.012) were independent prognostic factors. Conclusions: Significant differences in clinicopathological feature and outcome exist between colonic and rectal NENs. Multivariate analysis indicated that tumor size and pathological classification were associated with the prognosis. However, tumor location was not an independent factor. The worse outcome of colonic NENs observed in clinical practice might be due not only to the biological differences, but also to larger tumor size in colonic NENs caused by the delayed diagnosis.

scholarly journals Establishment of a Nomogram for Patients with Primary Mediastinal Large B-Cell Lymphoma Based on the SEER Database and Validation of Real-World Data

Blood ◽  
2021 ◽  
Vol 138 (Supplement 1) ◽  
pp. 1341-1341
Author(s):  
Hua Wang ◽  
Guanjun Chen ◽  
Bibo Fu
Keyword(s):  
Prognostic Factors ◽  
B Cell ◽  
Cell Lymphoma ◽  
External Validation ◽  
B Cell Lymphoma ◽  
Seer Database ◽  
Real World Data ◽  
Decision Curve Analysis ◽  
Large B Cell Lymphoma ◽  
Large B Cell

Abstract Background Primary mediastinal large B-cell lymphoma (PMBCL) is a rare disease with the majority of patients being rapidly progressive anterior mediastinal large tumors. Due to the rarity of PMBCL, information on the incidence, clinical features, prognostic factors and models of PMBCL is limited. The present study is one of the largest studies on the incidence and prognostic factors of PMBCL and is the first to establish a nomogram model of PMBCL and validate it with real-world data. We also compared the newly established Nomogram with the existing IPI prognostic model. We believe that our findings can help clinicians to quickly and accurately assess the predicted survival of patients and help them to perform individualized risk stratification of patients. Methods Based on data from the Surveillance, Epidemiology and End Results (SEER) database, 797 patients diagnosed with PMBCL were enrolled in this study. The 797 patients were randomly divided into training and internal validation groups in a 7:3 ratio, and 116 patients diagnosed with PMBCL were included in the external validation group based on data from the Sun Yat-sen University Cancer Center and the First Affiliated Hospital of Guangzhou Medical University. Independent prognostic factors were screened by Cox regression analysis. R-coding was used to construct nomograms predicting overall survival (OS). Discriminations and corrections of the new model were assessed using the consistency index (C-index), subject operating characteristic curves (ROC) and calibration curves, and compared with the conventional international prognostic index (IPI) using decision curve analysis (DCA) to assess its accuracy and benefit. Results From 2001 to 2016, the incidence of primary mediastinal large B-cell lymphoma showed a relatively stable increasing trend with an APC of 11.8% (95% confidence interval 8.8-14.0, P&lt;0.05), and this trend was more pronounced in the female population. Multivariate models showed that age and Ann arbor staging were significantly associated with OS, while the variable of extra-nodal invasion was included in the modeling based on clinical experience. In the training cohort, the C-index of the nomogram for OS was 0.712. the C-index for the internal and external validation cohorts was 0.667 and 0.690, respectively. The calibration curve also showed high predictive accuracy. The C-index and ROC curves of nomogram showed better results compared to IPI scores, and also yielded better net gains in decision curve analysis. Conclusion In summary, we successfully established a validated nomogram for predicting OS in patients with PMBCL, which can help clinicians to select appropriate individualized treatment for their patients. Figure 1 Figure 1. Disclosures No relevant conflicts of interest to declare.

Doubling time of preoperative serum alpha-fetoprotein level can predict recurrence and prognosis after hepatic resection of hepatocellular carcinoma

2007 ◽  
Vol 25 (18_suppl) ◽  
pp. 15118-15118 ◽  
Author(s):  
T. Masuda ◽  
T. Beppu ◽  
T. Ishiko ◽  
T. Mizumoto ◽  
H. Hayashi ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Prognostic Factors ◽  
Survival Time ◽  
Tumor Size ◽  
Odds Ratio ◽  
Doubling Time ◽  
Postoperative Recurrence ◽  
Tumor Type ◽  
Multiple Tumors ◽  
Preoperative Serum

15118 Background: It is quite important to predict postoperative recurrence or prognosis in the patients with hepatocellular carcinoma (HCC) before surgery. There have been few reports about the value of doubling time of preoperative serum a-fetoprotein (AFP) or protein induced by vitamin K absence (PIVKA-II) levels. Methods: Between January 2000 to December 2005, 160 consecutive HCC patients underwent hepatic resections in our institution. Serum AFP and PIVKA-II level was prospectively measured at least two points before surgery to calculate a doubling time. Clinical factors such as age, gender, BMI, etiology of hepatitis, degree of liver damage, gross tumor type, tumor size, tumor numbers, portal vein tumor thrombosis (PVTT), and AFP-L3 were concurrently investigated. Univariate and multivariate analyses were done to clarify predictive factors of postoperative recurrence and survival. Results: There were no relationship between preoperative levels and doubling time of both tumor markers. In univariate analysis, significant predictors of postoperative recurrence were AFP > 200 ng / ml, PIVKA-II > 200 mAU / ml, AFP-L3 > 10%, non-simple nodular type tumor, tumor size > 3 cm, multiple tumors, PVTT positive, and doubling time of AFP < 40 days. The significant prognostic factors were AFP > 200 ng / ml, HBs antigen positive, non-simple nodular type tumor, multiple tumors, PVTT positive, and doubling time of AFP < 40 days. In multivariate analysis, multiple tumors (odds ratio: 1.48), and doubling time of AFP < 40 days (odds ratio: 2.17) were significant predictors of recurrence. The significant prognostic factors were non-simple nodular type tumor (odds ratio: 6.41), multiple tumors (odds ratio: 7.62), and doubling time of AFP < 40 days (odds ratio: 6.49). Postoperative mean recurrence free survival time of HCC patients with doubling time of AFP < 40 days was only 2.8 months and mean survival time was 34 months. Conclusions: In HCC patients, doubling time of preoperative serum AFP level is useful to predict early recurrence and poor prognosis. Perioperative adjuvant therapy should be considered for such high risk patients. No significant financial relationships to disclose.

Conditional survival of patients with nonmetastatic bone osteosarcoma.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e23511-e23511
Author(s):  
Ruoyu Miao ◽  
Haotong Wang ◽  
Edwin Choy ◽  
Gregory Michael Cote ◽  
Kevin Raskin ◽  
...  
Keyword(s):  
Overall Survival ◽  
Prognostic Factors ◽  
Survival Time ◽  
Disease Progression ◽  
Tumor Size ◽  
Resection Margin ◽  
Progression Free Survival ◽  
Conditional Survival ◽  
Histologic Subtype ◽  
Free Survival

e23511 Background: Conditional survival provides a dynamic prediction of prognosis for patients surviving a defined period of time after diagnosis. This study aimed to determine the conditional survival and prognostic factors over time among patients with non-metastatic bone osteosarcoma. Methods: We reviewed 714 bone osteosarcoma patients treated from 1985 to 2016. Patients with metastatic disease at diagnosis or limited follow up were excluded, resulting in 587 cases for analysis. Clinical and pathological variables were recorded. Predictive variables included age at diagnosis, gender, previous radiation history, tumor site, tumor size, histologic subtype, histologic grade, resection margin, chemotherapy, and radiation therapy. The multivariate Cox proportional hazards regression was used to analyze prognostic factors of conditional overall survival and progression-free survival at baseline and 5 years after diagnosis. Results: The estimated 5-year conditional overall survival increased from 71.0% (95% CI: 67.5%-75.0%) at baseline to 86.9% (95% CI: 82.6%-90.5%) at 5 years, which means if a patient with non-metastatic bone osteosarcoma survived 5 years, the chance of surviving another 5 years was 86.9%. If the patient was progression-free for 5 years, the 5-year conditional overall survival was even higher, 93.2% (95% CI: 89.5%-96.4%), and the 5-year conditional progression-free survival improved from 57.1% (95% CI: 53.3%-61.0%) at baseline to 91.2% (95% CI: 87.5%-94.6%) at 5 years. Prognostic factors for mortality and disease progression change as survival time increases. At baseline, age (p < 0.001 and p = 0.003), histologic subtype (p < 0.001 and p = 0.001), grade (p < 0.001 and p < 0.001), tumor size (p = 0.002 and p = 0.002), resection margin (p < 0.001 and p < 0.001) and chemotherapy (p = 0.001 and p = 0.001) were predictive of both overall survival and progression-free survival. However, only age (p < 0.001) and histologic subtype (p = 0.015) remained significant for mortality and resection margin (p = 0.001) for disease progression at 5 years. Conclusions: The survival probability of osteosarcoma improves as survival time increases. Estimates of conditional survival can provide useful information for individualized surveillance strategies, risk evaluation, patient counseling, and making clinical decisions.

scholarly journals The Efficacy and Prognostic Factors of the Combination of TACE and Apatinib for the Treatment of BCLC Stage C Hepatocellular Carcinoma

2021 ◽  
Vol 8 ◽  
Author(s):  
Shun Liu ◽  
Kai-Cai Liu ◽  
Wei-Fu Lv ◽  
Dong Lu ◽  
Xian-Hai Zhu ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Prognostic Factors ◽  
Adverse Events ◽  
Portal Vein ◽  
Survival Time ◽  
Tumor Size ◽  
Tumor Thrombus ◽  
Portal Vein Tumor Thrombus ◽  
Cox Regression Analysis ◽  
Pugh Class

Objective: Apatinib is a inhibitor of vascular endothelial growth factor receptor-2. To explore the efficacy and prognostic factors of transarterial chemoembolization (TACE) combined with apatinib in the treatment of Barcelona Clinic Liver Cancer stage C (BCLC C) hepatocellular carcinoma (HCC).Methods: Clinical data of 146 HCC patients with BCLC stage C admitted to our hospital were collected and analyzed retrospectively, of which 76 cases were treated with TACE combined with apatinib (TACE-apatinib) and 70 with TACE alone. The tumor response, survival time, and adverse events were compared between the two groups, and the factors affecting the prognosis were analyzed.Results: The objective response rate (ORR) and disease control rate (DCR) in the TACE-apatinib group were higher than in the TACE-alone group (ORR: 42.10 vs. 25.71%, P = 0.03; DCR: 84.21 vs. 55.71%, P = 0.001). The median time to progression (TTP) and overall survival (OS) in the TACE-apatinib group were longer than in the TACE-alone group (TTP: 5.5 vs. 3.7 months, P = 0.02; OS: 10.0 vs. 6.2 months, P = 0.01). Univariate and multivariate Cox regression analysis showed that tumor size, Child-Pugh class, and the presence of the portal vein tumor thrombus affect the prognosis of patients. Subgroup analysis revealed that TACE-apatinib therapy resulted in a higher OS in patients with tumor size &lt;10 cm, without portal vein tumor thrombus, and with Child-Pugh class A (P &lt; 0.05). The likelihood of adverse events (hand-foot syndrome, hypertension, oral ulcer) was significantly higher in the increased in the TACE-apatinib group than in the TACE alone group (P &lt; 0.05).Conclusion: TACE-apatinib is an effective and safe method for the treatment of BCLC stage C HCC. Tumor size, Child-Pugh class, and portal vein tumor thrombus affect survival time in HCC patients with BCLC stage C.

scholarly journals Clinicopathological Characteristics and Treatment Strategies of Triple-Negative Breast Cancer Patients With a Survival Longer than 5 Years

2021 ◽  
Vol 10 ◽  
Author(s):  
Ning Xie ◽  
Ying Xu ◽  
Ying Zhong ◽  
Junwei Li ◽  
Herui Yao ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Prognostic Factors ◽  
Survival Time ◽  
Triple Negative Breast Cancer ◽  
Tumor Size ◽  
Triple Negative ◽  
Cox Regression ◽  
Propensity Score Analysis ◽  
Term Survival ◽  
Cox Regression Analysis

PurposeTriple-negative breast cancer (TNBC) is characterized by high malignancy and a poor prognosis. Patients with TNBC who survive longer than 5 years represent a unique portion of the population. This study aimed to analyze the clinicopathological features, explore prognostic factors, and evaluate treatment options for these patients.MethodsA total of 24,943 TNBC patients were enrolled from the national Surveillance, Epidemiology, and End Results (SEER) database between January 2010 and December 2016. The patients were divided into three groups: group 1, survival time &lt;3 years; group 2, 3–5 years; and group 3, survival time ≥5 years. The overall survival (OS) and breast cancer cause-specific survival (BCSS) were primarily assessed in this study. A propensity score analysis was used to avoid bias caused by the data selection criteria. We used a Cox hazard ratio analysis to determine prognostic factors, which were selected as nomogram parameters to develop a model for predicting patient survival.ResultsPatients who survived longer than 5 years were more likely to be younger than 55 years, Caucasian, and exhibit a lower AJCC stage, N stage, distant metastasis, lymph node (LN) involvement, and tumor size than those with a shorter survival time (p &lt; 0.05). The multivariable Cox regression analysis showed that age, race, tumor size, LN status, and chemotherapy were independent prognostic factors. Subgroup analyses for patients with tumors ≤20 mm displayed a superior OS and BCSS for breast-conserving surgery (BCS) not treated with a mastectomy. BCS provided at least an equivalent prognosis to a mastectomy in patients with tumors larger than 20 mm. A nomogram with a C-index of 0.776 (95% confidence interval: 0.767–0.785) was developed to predict the 3- and 5-year survival probability for the patients with TNBC.ConclusionA localized surgical approach may represent a superior choice for TNBC patients with a survival time longer than 5 years. Our study indicated that age, race, tumor size, LN status, and chemotherapy were independent prognostic factors. A prognostic nomogram directly quantified patient risk and was better able to predict long-term survival in TNBC patients.

scholarly journals Predicting Survival of Patients With Rectal Neuroendocrine Tumors Using Machine Learning: A SEER-Based Population Study

2021 ◽  
Vol 8 ◽  
Author(s):  
Xiaoyun Cheng ◽  
Jinzhang Li ◽  
Tianming Xu ◽  
Kemin Li ◽  
Jingnan Li
Keyword(s):  
Machine Learning ◽  
Predictive Model ◽  
Medical Center ◽  
External Validation ◽  
Staging System ◽  
Predictive Performance ◽  
Validation Dataset ◽  
Seer Database ◽  
Internal Validation ◽  
Survival Status

Background: The number of patients diagnosed with rectal neuroendocrine tumors (R-NETs) is increasing year by year. An integrated survival predictive model is required to predict the prognosis of R-NETs. The present study is aimed at exploring epidemiological characteristics of R-NETs based on a retrospective study from the Surveillance, Epidemiology, and End Results (SEER) database and predicting survival of R-NETs with machine learning.Methods: Data of patients with R-NETs were extracted from the SEER database (2000–2017), and data were also retrospectively collected from a single medical center in China. The main outcome measure was the 5-year survival status. Risk factors affecting survival were analyzed by Cox regression analysis, and six common machine learning algorithms were chosen to build the predictive models. Data from the SEER database were divided into a training set and an internal validation set according to the year 2010 as a time point. Data from China were chosen as an external validation set. The best machine learning predictive model was compared with the American Joint Committee on Cancer (AJCC) seventh staging system to evaluate its predictive performance in the internal validation dataset and external validation dataset.Results: A total of 10,580 patients from the SEER database and 68 patients from a single medical center were included in the analysis. Age, gender, race, histologic type, tumor size, tumor number, summary stage, and surgical treatment were risk factors affecting survival status. After the adjustment of parameters and algorithms comparison, the predictive model using the eXtreme Gradient Boosting (XGBoost) algorithm had the best predictive performance in the training set [area under the curve (AUC) = 0.87, 95%CI: 0.86–0.88]. In the internal validation, the predictive ability of XGBoost was better than that of the AJCC seventh staging system (AUC: 0.90 vs. 0.78). In the external validation, the XGBoost predictive model (AUC = 0.89) performed better than the AJCC seventh staging system (AUC = 0.83).Conclusions: The XGBoost algorithm had better predictive power than the AJCC seventh staging system, which had a potential value of the clinical application.

scholarly journals A Prognostic Nomogram of Colon Cancer With Liver Metastasis: A Study of the US SEER Database and a Chinese Cohort

2021 ◽  
Vol 11 ◽  
Author(s):  
Chuan Liu ◽  
Chuan Hu ◽  
Jiale Huang ◽  
Kanghui Xiang ◽  
Zhi Li ◽  
...  
Keyword(s):  
Colon Cancer ◽  
Liver Metastasis ◽  
Bone Metastasis ◽  
Lung Metastasis ◽  
Tumor Size ◽  
External Validation ◽  
Histological Type ◽  
Seer Database ◽  
Training Set ◽  
Internal Validation

BackgroundAmong colon cancer patients, liver metastasis is a commonly deadly phenomenon, but there are few prognostic models for these patients.MethodsThe clinicopathologic data of colon cancer with liver metastasis (CCLM) patients were downloaded from the Surveillance, Epidemiology and End Results (SEER) database. All patients were randomly divided into training and internal validation sets based on the ratio of 7:3. A prognostic nomogram was established with Cox analysis in the training set, which was validated by two independent validation sets.ResultsA total of 5,700 CCLM patients were included. Age, race, tumor size, tumor site, histological type, grade, AJCC N status, carcinoembryonic antigen (CEA), lung metastasis, bone metastasis, surgery, and chemotherapy were independently associated with the overall survival (OS) of CCLM in the training set, which were used to establish a nomogram. The AUCs of 1-, 2- and 3-year were higher than or equal to 0.700 in the training, internal validation, and external validation sets, indicating the favorable effects of our nomogram. Besides, whether in overall or subgroup analysis, the risk score calculated by this nomogram can divide CCLM patients into high-, middle- and low-risk groups, which suggested that the nomogram can significantly determine patients with different prognosis and is suitable for different patients.ConclusionHigher age, the race of black, larger tumor size, higher grade, histological type of mucinous adenocarcinoma and signet ring cell carcinoma, higher N stage, RCC, lung metastasis, bone metastasis, without surgery, without chemotherapy, and elevated CEA were independently associated with poor prognosis of CCLM patients. A nomogram incorporating the above variables could accurately predict the prognosis of CCLM.

scholarly journals Renal Cell Carcinoma in People with HIV- An Analysis of the Postoperative Factors Associated with the Long-Term Survival

2021 ◽  
Author(s):  
Liang Chen ◽  
Menghua Wu ◽  
Xin Zheng ◽  
Yu Zhang ◽  
Jimao Zhao
Keyword(s):  
Renal Cell Carcinoma ◽  
Overall Survival ◽  
Prognostic Factors ◽  
Cell Carcinoma ◽  
Survival Time ◽  
Tumor Size ◽  
Renal Cell ◽  
P Value ◽  
People Living With Hiv ◽  
Factors Associated

Abstract Aims: The purpose of the current study is to explore the prognostic factors of the renal cell carcinoma (RCC) in People living with HIV (PLWH), and to evaluate the postoperative factors associated with the survival in PLWH with RCC.Methods: PLWH with RCC who underwent surgical treatment were retrospectively studied. A single-center analysis was conducted from January 2012 to January 2021. General and postoperative clinical data, including age, gender, smoking and drink history, active antiretroviral therapy (ART), cancer histology, clinical and pathological stage, surgical result, Glasgow Prognostic Score (GPS), the Charlson comorbidity index(CCI), the Karnofsky performance status (KPS）, CD4+ T cell count, CD4/CD8 ratio and survival time were collected.Results: A total of 67 patients were included in our study. The Creatine (77.1±18.8 vs 85.7±12.9, P value=0.032), HGB(mg/dL) (113.6±12.6 vs 139.3±20.8, P value=0.694), the CD4/CD8 ratio (0.68±0.40 vs 0.86±0.33, P value=0.006) and overall survival time (months) (74.93±5.249 vs 96.47±3.28, P value=0.009), the progression free survival time (months) (66.47±6.56 vs 90.65±4.82，P value=0.011). The Cox regression analysis showed that the tumor size and the CD4/CD8 ratio were prognostic factors for survival time.Conclusion: In our retrospective analysis, the survival prognosis of negative group was better than that of PLWH with RCC. The risk factors for overall survival in PLWH with RCC was tumor size and CD4+/CD8+ ratio. The lower CD4/CD8 ratio was a significant predictive factor for shorter overall survival.

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