15-year survival after radical prostatectomy (RP): Which prognostic factors are available for patient counseling?

2013 ◽  
Vol 31 (6_suppl) ◽  
pp. 181-181
Author(s):  
Sophie D. Fossa ◽  
Haakon Waehre ◽  
Milada Cvancarova ◽  
Haavard E Danielsen
Keyword(s):  
Prostate Cancer ◽  
Prognostic Factors ◽  
High Risk ◽  
Poor Prognosis ◽  
Risk Group ◽  
Rare Event ◽  
Observation Time ◽  
High Risk Group ◽  
Patient Counseling ◽  
Psa Relapse

181 Background: Studies on 15-year Post-RP survival including data on PSA relapse (PSA-Rel) are rare. We established the 15-year post-RP prostate cancer specific mortality (PCSM), to explore the time to PSA-Rel and PCSM thereafter, and to identify clinically available prognostic factors. Methods: In men prostatectomized from 1987-2004 slightly modified D`Amico risk groups were identified (T1: No palpable tumor ;”T2 unilateral”/”T2 bilateral” according to tumor palpability in one or both lobes). PSA –Rel was defined as PSA ≥4 µg/l before 2000, and thereafter as PSA >0.2 µg/l. Delay of RP was defined as RP performance 3-12 months after diagnosis. Competing risk modeling was performed with a significance level of <0.05. Results: After a median observation time of 12 years (range: 0-22), of 309 men (median age:62 years [range:40-74]) 40 have died from prostate cancer ( PCa) and 68 due to other causes (15-year PCSM: 15% [95%CI: 10-19%). No difference of PCSM was found between the low (N: 12) and the intermediate group (N: 121), the “conventional” high risk group ( N: 121) displaying a 24% PCSM rate (95% CI:16-32%) with particularly poor prognosis for men who presented with two high risk factors ( N. 32 ; PCSM: 33% [95% CI:20-46%]). The median time to PSA relapse (N: 152) was 5 years (range: 0-17), the median overall survival time after PSA- Rel being 7 years (range: 0-17). PCSM continued to increase after 10 years. Delay of RP had no impact on PCSM. Conclusions: After a median observation time of 12 years approximately 1 of 7 men with localized PCa, most of them diagnosed before the PSA- era, have died of prostate cancer. The “conventional” high-risk group is prognostically heterogeneous: Men with two high risk criteria have a particularly poor prognosis. PSA-Rel 10 years after RP is no rare event followed by survival times of >10 years. Delay of RP for up to one year had no impact on PCSM.

scholarly journals Clinical and Biological Prognostic Factors in Follicular Lymphoma Patients During Treatment

2021 ◽  
Author(s):  
Ádám Jóna ◽  
Anna Kenyeres ◽  
Sándor Barna ◽  
Árpád Illés ◽  
Zsófia Simon
Keyword(s):  
Prognostic Factors ◽  
High Risk ◽  
Follicular Lymphoma ◽  
Risk Group ◽  
Standardized Uptake Value ◽  
Progression Free Survival ◽  
High Risk Group ◽  
Pet Ct ◽  
Significant Difference ◽  
Biological Prognostic Factors

Abstract Introduction: Follicular lymphoma (FL) is an indolent yet heterogeneous B-cell lymphoproliferative disorder. Most people respond to treatment well. However, a particular group of patients has a poor prognosis, and these patients are difficult to define.Patients and methods: We retrospectively analyzed FL patients treated at the University of Debrecen in the past 20 years. We investigated prognostic factors that may influence the survival of FL patients.Results: We found a standardized uptake value (SUV)max cut-off value of 9.85 at the staging PET/CT to significantly separate FL patients’ progression-free survival (PFS) (p=0.0003, HR: 0.2560, 95%CI: 0.1232-0.5318). Lymphocyte/ monocyte (Ly/Mo) ratio of 3.45 drawn at diagnosis also significantly predicted PFS (p=0.0324, HR: 1.806, 95% CI: 1.051-3.104). Combining patients’ with staging SUVmax >9.85 and Ly/Mo < 3.45 a high-risk group of FL patients can be identified (p<0.0001, HR: 0.1033, 95%CI: 0.03719-0.2868). Similarly, a significant difference was shown with a SUVmax cut-off of 3.15 at the interim PET/CT (p<0.0001, HR: 0.1535, 95%CI: 0.06329-0.3720). Combining patients with staging SUVmax >9.85 and interim SUVmax >3.15, a high-risk group of FL patients can be identified (p<0.0001, HR: 0.1037, 95%CI: 0.03811-0.2824). The PFS difference is translated into overall survival advantage (p=0.0506, HR: 0.1187, 95%CI: 0.01401-1.005).Discussion: Biological prognostic factors, such as the Ly/ Mo ratio, may improve the prognostic assessment of staging PET/CT. Nevertheless, PFS difference is translated into OS when using a combination of staging and interim SUVmax. We consider investigating additional biological prognostic factors while currently highlighting PET/CT's role in FL.

Adjuvant Chemotherapy Guidance for pT1-3N0-1 Breast Cancer Patients with HR+, HER2- subtype: a study based on SEER database

2021 ◽  
Author(s):  
juanjuan Qiu ◽  
Li Xu ◽  
Yu Wang ◽  
Jia Zhang ◽  
Jiqiao Yang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Prognostic Factors ◽  
High Risk ◽  
Cancer Patients ◽  
Risk Group ◽  
High Risk Group ◽  
Low Risk ◽  
Rank Test ◽  
Breast Cancer Patients ◽  
Group Score

Abstract Background Although the results of gene testing can guide early breast cancer patients with HR+, HER2- to decide whether they need chemotherapy, there are still many patients worldwide whose problems cannot be solved well by genetic testing. Methods 144 735 patients with HR+, HER2-, pT1-3N0-1 breast cancer from the Surveillance, Epidemiology, and End Results database were included from 2010 to 2015. They were divided into chemotherapy (n = 38 392) and no chemotherapy (n = 106 343) group, and after propensity score matching, 23 297 pairs of patients were left. Overall survival (OS) and breast cancer-specific survival (BCSS) were tested by Kaplan–Meier plot and log-rank test and Cox proportional hazards regression model was used to identify independent prognostic factors. A nomogram was constructed and validated by C-index and calibrate curves. Patients were divided into high- or low-risk group according to their nomogram score using X-tile. Results Patients receiving chemotherapy had better OS before and after matching (p < 0.05) but BCSS was not significantly different between patients with and without chemotherapy after matching: hazard ratio (HR) 1.005 (95%CI 0.897, 1.126). Independent prognostic factors were included to construct the nomogram to predict BCSS of patients without chemotherapy. Patients in the high-risk group (score > 238) can get better OS HR 0.583 (0.507, 0.671) and BCSS HR 0.791 (0.663, 0.944) from chemotherapy but the low-risk group (score ≤ 238) cannot. Conclusion The well-validated nomogram and a risk stratification model was built. Patients in the high-risk group should receive chemotherapy while patients in low-risk group may be exempt from chemotherapy.

Molecular Load of Pathologically Occult Metastases in Pelvic Lymph Nodes Is an Independent Prognostic Marker of Biochemical Failure After Localized Prostate Cancer Treatment

2006 ◽  
Vol 24 (19) ◽  
pp. 3081-3088 ◽  
Author(s):  
Anna C. Ferrari ◽  
Nelson N. Stone ◽  
Ralf Kurek ◽  
Elizabeth Mulligan ◽  
Roy McGregor ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
High Risk ◽  
Lymph Nodes ◽  
Prognostic Marker ◽  
Risk Group ◽  
High Risk Group ◽  
Biochemical Failure ◽  
Localized Prostate Cancer ◽  
Pelvic Lymph Nodes ◽  
Independent Prognostic Marker

Purpose Thirty percent of patients treated with curative intent for localized prostate cancer (PC) experience biochemical recurrence (BCR) with rising serum prostate-specific antigen (sPSA), and of these, approximately 50% succumb to progressive disease. More discriminatory staging procedures are needed to identify occult micrometastases that spawn BCR. Patients and Methods PSA mRNA copies in pathologically normal pelvic lymph nodes (N0-PLN) from 341 localized PC patients were quantified by real-time reverse-transcriptase polymerase chain reaction. Based on comparisons with normal lymph nodes and PLN with metastases and on normalization to 5 × 106 glyceraldehyde-3′-phosphate dehydrogenase mRNA copies, normalized PSA copies (PSA-N) and a threshold of PSA-N 100 or more were selected for continuous and categorical multivariate analyses of biochemical failure-free survival (BFFS) compared with established risk factors. Results At median follow-up of 4 years, the BFFS of patients with PSA-N 100 or more versus PSA-N less than 100 was 55% and 77% (P = .0002), respectively. The effect was greatest for sPSA greater than 20 ng/mL, 25% versus 60% (P = .014), Gleason score 8 or higher, 21% versus 66% (P = .0002), stage T3c, 18% versus 64% (P = .001), and high-risk group (50% v 72%; P = .05). By continuous analysis PSA-N was an independent prognostic marker for BCR (P = .049) with a hazard ratio of 1.25 (95% CI, 1.001 to 1.57). By categorical analysis, PSA-N 100 or more was an independent variable (P = .021) with a relative risk of 1.98 (95% CI, 1.11 to 3.55) for BCR compared with PSA-N less than 100. Conclusion PSA-N 100 or more is a new, independent molecular staging criterion for localized PC that identifies high-risk group patients with clinically relevant occult micrometastases in N0-PLN, who may benefit from additional therapy to prevent BCR.

Validation of a genomic-clinical classifier model for predicting clinical recurrence of patients with localized prostate cancer in a high-risk population.

2012 ◽  
Vol 30 (5_suppl) ◽  
pp. 175-175 ◽  
Author(s):  
Robert B. Jenkins ◽  
Eric J Bergstralh ◽  
Elai Davicioni ◽  
R. Jeffrey Karnes ◽  
Karla V. Ballman ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
High Risk ◽  
Radical Prostatectomy ◽  
Gleason Score ◽  
Risk Group ◽  
High Risk Group ◽  
High Risk Population ◽  
Clinical Recurrence ◽  
Clinical Variables ◽  
Subset Analysis

175 Background: The efficient delivery of adjuvant and salvage therapy after radical prostatectomy in patients with prostate cancer is hampered by a lack of biomarkers to assess the risk of clinically significant recurrence and progression. Methods: Mayo Clinic Radical Prostatectomy Registry (RP) patient specimens were selected from a case-control cohort with 14 years median follow-up for training and initial validation of an expression biomarker genomic classifier (GC). An independent, blinded case-cohort study of high-risk RP subjects was used to validate GC, comparing the performance of GC to a multivariate logistic regression clinical model (CM) and GC combined with clinical variables (genomic-clinical classifier, GCC) for predicting clinical recurrence (defined as positive bone or CT scan within 5 years after biochemical recurrence). The concordance index (c-index) and Cox model were used to evaluate discrimination and estimate the risk of clinical recurrence. Results: In the training subset (n=359), both GC and GCC had a c-index of 0.90 whereas CM had a c-index of 0.76. In the internal validation set (n=186), GC and GCC had a c-index of 0.76 and 0.75, while CM had a c-index of 0.69. In an independent high-risk study (n=219), GC and GCC had a c-index of 0.77 and 0.76, while CM had a c-index of 0.68. In subset analysis of Gleason score 7 patients within the high-risk group, GC and GCC showed improved discrimination with c-index of 0.78 and 0.76, respectively compared to 0.70 for CM. In the high-risk group, the risk of recurrence by GC model score quartiles at 5 years after RP was estimated at 1%, 5%, 5% and 18%. Conclusions: The GC model shows improved performance over CM in the prediction of clinical recurrence in a high-risk cohort and in subset analysis of Gleason score 7 patients. The addition of clinical variables to the GC model did not significantly contribute to classifier performance in patients with high-risk features. We are further testing the performance of the GC and GCC models and their usefulness in guiding decision-making (e.g., for the adjuvant therapy setting) in additional studies of prostate cancer clinical risk groups.

scholarly journals A Circulating MicroRNA Signature as a Biomarker for Prostate Cancer in a High Risk Group

2015 ◽  
Vol 4 (7) ◽  
pp. 1369-1379 ◽  
Author(s):  
Brian Kelly ◽  
Nicola Miller ◽  
Karl Sweeney ◽  
Garrett Durkan ◽  
Eamon Rogers ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
High Risk ◽  
Risk Group ◽  
High Risk Group ◽  
Circulating Microrna

scholarly journals Retrospective analysis of pediatric hepatoblastoma with tumor rupture: experience from a single center

2021 ◽  
Author(s):  
Yu-Tong Zhang ◽  
Yu-fei Zhao ◽  
Dian-fei Yang ◽  
Jian Chang
Keyword(s):  
High Risk ◽  
Poor Prognosis ◽  
Risk Group ◽  
Interleukin 2 ◽  
Complete Response ◽  
High Risk Group ◽  
Free Fluid ◽  
Tumor Rupture ◽  
High Risk Factor ◽  
Peritoneal Perfusion

Abstract Background Hepatoblastoma (HB) tumor rupture is currently considered as a high-risk factor in some risk-stratification systems. This study aimed to investigate the value of HB tumor rupture in predicting the poor prognosis of child patients. Methods The clinical data from children with high-risk HB or HB tumor rupture at our institution from October 2008 to October 2017 were retrospectively reviewed and analyzed. Results Altogether 34 children with high-risk HB or HB tumor rupture were retrospected, including 25 in the high-risk group and 9 in tumor rupture group. The 3-year overall survival (OS) rate in tumor rupture group was significantly higher than that in high-risk group (100% vs 60%, p=0.035). In tumor rupture group, 7 (77.8%) out of 9 patients had the hemoglobin level ≤ 8 g/L and 3 (33.3%) had that ≤ 6 g/L at the time of diagnosis. Peritoneal perfusion with normal saline and interleukin-2 was implemented for each patient until the free fluid was under normal level. At the end of the treatment, 7 (77.8%) of 9 patients achieved complete response (CR). No patient died at the last follow-up. Conclusions Tumor rupture is not predictive of poor prognosis with the risk of peritoneal dissemination/relapse.

scholarly journals Investigation of Information Acquisition Channel for Prostate Cancer High-Risk Group

2021 ◽  
Vol 19 (3) ◽  
pp. 174-182
Author(s):  
Yun-Sok Ha ◽  
Kwang Taek Kim ◽  
Wook Nam ◽  
Hongzoo Park ◽  
Sangjun Yoo ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Cancer Screening ◽  
High Risk ◽  
Information Acquisition ◽  
Risk Group ◽  
Prostate Cancer Screening ◽  
High Risk Group ◽  
Cancer Information ◽  
Urological Oncology ◽  
Initial Symptoms

Purpose: The survey was conducted on Korean men to examine information acquisition channel for prostate cancer high risk group as part of the “Blue Ribbon Campaign” of the Korean Urological Oncology Society.Materials and Methods: An online survey of 500 men aged 50 years old or older was completed to query investigation of the status of prostate cancer awareness and information acquisition from February 4 to February 9, 2021.Results: Most men in their 50s and older are well aware that prostate cancer can also occur in young men in their 40s, so the rate of misunderstanding of the timing of prostate cancer screening after their 60s is very low. Two-thirds of all respondents (67.2%) were also confirmed that prostate cancer had no initial symptoms and was not included in the national cancer screening. Seventy-five percent of people look up information on their own in case of suspected prostate cancer, and 51.6% seek out knowledge on their own to prevent prostate cancer. Of the respondents, 27.4% of men contacted prostate cancer-related information within the past year, and the percentage of people contacted through ‘Internet/Phone,’ ‘People Around’ and ‘Television’ was high. The most trusted channel among prostate cancer information channels was ‘medical professionals,’ but the experience rate was not high, and the channel with high experience rate and reliability was shown as ‘television.’Conclusions: Much effort is still needed to understand the information acquisition behavior of Korean men and to improve awareness of early screening for prostate cancer.

Varying Importance of Prognostic Factors in Subgroups of Myelodysplastic Syndromes Defined by Blast Count, Cytogenetic Risk Group, or WHO Classification.

Blood ◽  
2009 ◽  
Vol 114 (22) ◽  
pp. 2776-2776
Author(s):  
Andrea Kuendgen ◽  
Corinna Strupp ◽  
Kathrin Nachtkamp ◽  
Barbara Hildebrandt ◽  
Rainer Haas ◽  
...  
Keyword(s):  
Multivariate Analysis ◽  
Prognostic Factors ◽  
High Risk ◽  
Research Funding ◽  
Risk Group ◽  
Univariate Analysis ◽  
Risk Groups ◽  
High Risk Group ◽  
Intermediate Risk ◽  
Blast Count

Abstract Abstract 2776 Poster Board II-752 Introduction: We wondered whether prognostic factors have similar relevance in different subpopulations of MDS patients. Methods: Our analysis was based on patients with primary, untreated MDS, including 181 RA, 169 RARS, 649 RCMD, 322 RSCMD, 79 5q-syndromes, 290 RAEB I, 324 RAEB II, 266 CMML I, 64 CMML II, and 209 RAEB-T. The impact of prognostic variables in univariate analysis was compared in subpopulations of patients defined by medullary blast count, namely <5%, ≥5% (table), ≥10%, and ≥20% (not shown), as well as 3 subpopulations defined by the cytogenetic risk groups according to IPSS (table). Multivariate analysis of prognostic factors was performed for cytogenetically defined subgroups and WHO-subtypes. Results: Strong prognostic factors in all blast-defined subgroups were hemoglobin, transfusion dependency, increased WBC, age, and LDH. However, all variables became less important in patients with ≥20% blasts (RAEB-T) and increased WBC was rare. Platelet count and cytogenetic risk groups were relevant in patients with <5%, ≥5%, and ≥10% marrow blasts, but not in RAEB-T. Marrow fibrosis was important in patients with <5% or ≥5% blasts, but not ≥10%. Gender and ANC <1000/μl were significant only in patients with a normal blast count. Furthermore, we looked for the effect of the karyotypes, relevant for IPSS scoring (-Y, del5q, del20q, others, del7q/-7, complex), and found a comparable influence on survival, irrespective whether patients had < or ≥5% marrow blasts. In subpopulations defined by cytogenetic risk groups, several prognostic factors were highly significant in univariate analysis, if patients had a good risk karyotype. These included hemoglobin, sex, age, LDH, increased WBC, transfusion need, and blast count (cut-offs 5%, 10%, and 20%). In the intermediate risk group only LDH, platelets, WBC, and blasts were significant prognostic factors, while in the high risk group only platelets and blast count remained significant. Multivariate analysis was performed for the cytogenetic risk groups and for subgroups defined by WHO subtypes. The analysis considered blast count (</≥5%), hemoglobin, platelets, ANC, cytogenetic risk group, transfusion need, sex, and age. In the subgroup including RA, RARS, and 5q-syndrome, LDH, transfusion, and age in descending order were independent prognostic parameters. In the RCMD+RSCMD group, karyotype, age, transfusion, and platelets were relevant factors. In the RAEB I+II subgroup, the order was hemoglobin, karyotype, age, and platelets, while in CMML I+II only hemoglobin had independent influence. In RAEB-T none of the factors examined was of independent significance. Looking at cytogenetic risk groups, in the favorable group, several variables independently influenced survival, namely transfusion, blasts, age, sex, and LDH (in this order). Interestingly, in the intermediate and high risk group, only blast count and platelets retained a significant impact. Conclusion: Univariate analysis showed prognostic factors (except ANC) included in IPSS and WPSS are relevant in most subgroups defined by marrow blast percentage. However, they all lose their impact if the blast count exceeds 20%. Regarding cytogenetic risk groups, several prognostic factors lose their influence already in the intermediate risk group. This underscores the prognostic importance of MDS cytogenetics. Multivariate analysis showed MDS subpopulations defined by WHO types also differ with regard to prognostic factors. In particular, CMML and RAEB-T stand out against the other MDS types. Disclosures: Kuendgen: Celgene: Honoraria. Hildebrandt:Celgene: Research Funding. Gattermann:Novartis: Honoraria, Participation in Advisory Boards on deferasirox clinical trials. Germing:Novartis, Celgene: Honoraria, Research Funding.

scholarly journals Establish a predictive model for high-risk de novo metastatic prostate cancer patients by machine learning.

2019 ◽  
Vol 5 (suppl) ◽  
pp. 13-13
Author(s):  
Po-Jung SU ◽  
Yu-Ann Fang ◽  
Yung-Chun Chang ◽  
Yung-Chia Kuo ◽  
Yung-Chang Lin
Keyword(s):  
Prostate Cancer ◽  
Machine Learning ◽  
High Risk ◽  
Cancer Patients ◽  
Metastatic Prostate Cancer ◽  
De Novo ◽  
Risk Group ◽  
High Risk Group ◽  
Recursive Feature Elimination ◽  
Risk Patients

13 Background: For de novo metastatic prostate cancer (mPC)) patients, their prognosis may be really different. Some of these patients response very well to hormone therapy with durable survival, but others may be not. For those poor prognosis patients, if we could predict them as high risk patients when diagnosed, and provide aggressive upfront chemotherapy or novel hormonal therapy, they might get better treatment outcomes. Methods: We used data of prostate cancer patients from 2000 to 2016 in Chang Gung Research Database. There are 799 de novo mPC patients with castration. We predicted the possibility for these patients progressed to metastatic castration-resistant prostate cancer (mCRPC) in 1 year and find the high risk group patients. Then we figured out the best features for prediction from the best classifier with Recursive Feature Elimination. Results: The de nove mPC patients who pregressed to mCRPC in 1 year, whose mOS is 21.9 months is worse than who progressed to mCRPC beyond 1 year significantly, whose mOS is 80.7 months. (adjusted hazard ratio[aHR]: 6.43, P<0.001). The overall performance of machine learning by XGBoost is the best in all predictive models for high risk patients. (AUC=0.7000, Accuracy=0.7143). We excluded the features with missing data over 50%, then put all other features in the model. (AUC=0.7042, Accuracy=0.7239). But we got the best performance with only 11 features, including age, time from diagnosis to castration, nadir PSA, hemoglobin, eosinophil/white blood cell ratio, alkaline phosphatase, alanine transaminase, blood urea nitrogen, creatinine, prothrombin time, and secondary primary cancer, by Recursive Feature Elimination. (AUC=0.7131, Accuracy=0.7267). Conclusions: We found the predictive model has better predictive accuracy and shorter manuscript time with less features selected by Recursive Feature Elimination.We can predict high risk group in de novo mPC patients and make better clinical decision for treatment with this XGBoost model.

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