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Efstathiou JA, Morgans AK, Bland CS, Shore ND. Novel hormone therapy and coordination of care in high-risk biochemically recurrent prostate cancer. Cancer Treat Rev 2024; 122:102630. [PMID: 38035646 DOI: 10.1016/j.ctrv.2023.102630] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Accepted: 09/25/2023] [Indexed: 12/02/2023]
Abstract
Biochemical recurrence (BCR) occurs in 20-50% of patients with prostate cancer (PCa) undergoing primary definitive treatment. Patients with high-risk BCR have an increased risk of metastatic progression and subsequent PCa-specific mortality, and thus could benefit from treatment intensification. Given the increasing complexity of diagnostic and therapeutic modalities, multidisciplinary care (MDC) can play a crucial role in the individualized management of this patient population. This review explores the role for MDC when evaluating the clinical evidence for the evolving definition of high-risk BCR and the emerging therapeutic strategies, especially with novel hormone therapies (NHTs), for patients with either high-risk BCR or oligometastatic PCa. Clinical studies have used different characteristics to define high-risk BCR and there is no consensus regarding the definition of high-risk BCR nor for management strategies. Next-generation imaging and multigene panels offer potential enhanced patient identification and precision-based decision-making, respectively. Treatment intensification with NHTs, either alone or combined with radiotherapy or metastasis-directed therapy, has been promising in clinical trials in patients with high-risk BCR or oligometastases. As novel risk-stratification and treatment options as well as evidence-based literature evolve, it is important to involve a multidisciplinary team to identify patients with high-risk features at an earlier stage, and make informed decisions on the treatments that could optimize their care and long-term outcomes. Nevertheless, MDC data are scarce in the BCR or oligometastatic setting. Efforts to integrate MDC into the standard management of this patient population are needed, and will likely improve outcomes across this heterogeneous PCa patient population.
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Affiliation(s)
- Jason A Efstathiou
- Department of Radiation Oncology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street, Boston, MA 02114, USA.
| | - Alicia K Morgans
- Dana-Farber Cancer Institute, 850 Brookline Ave, Dana 09-930, Boston, MA 02215, USA.
| | - Christopher S Bland
- US Oncology Medical Affairs, Pfizer Inc., 66 Hudson Boulevard, Hudson Yards, Manhattan, New York, NY 10001, USA.
| | - Neal D Shore
- Carolina Urologic Research Center, GenesisCare US, 823 82nd Pkwy, Myrtle Beach, SC, USA.
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Lee HW, Kim E, Na I, Kim CK, Seo SI, Park H. Novel Multiparametric Magnetic Resonance Imaging-Based Deep Learning and Clinical Parameter Integration for the Prediction of Long-Term Biochemical Recurrence-Free Survival in Prostate Cancer after Radical Prostatectomy. Cancers (Basel) 2023; 15:3416. [PMID: 37444526 DOI: 10.3390/cancers15133416] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2023] [Revised: 06/19/2023] [Accepted: 06/26/2023] [Indexed: 07/15/2023] Open
Abstract
Radical prostatectomy (RP) is the main treatment of prostate cancer (PCa). Biochemical recurrence (BCR) following RP remains the first sign of aggressive disease; hence, better assessment of potential long-term post-RP BCR-free survival is crucial. Our study aimed to evaluate a combined clinical-deep learning (DL) model using multiparametric magnetic resonance imaging (mpMRI) for predicting long-term post-RP BCR-free survival in PCa. A total of 437 patients with PCa who underwent mpMRI followed by RP between 2008 and 2009 were enrolled; radiomics features were extracted from T2-weighted imaging, apparent diffusion coefficient maps, and contrast-enhanced sequences by manually delineating the index tumors. Deep features from the same set of imaging were extracted using a deep neural network based on pretrained EfficentNet-B0. Here, we present a clinical model (six clinical variables), radiomics model, DL model (DLM-Deep feature), combined clinical-radiomics model (CRM-Multi), and combined clinical-DL model (CDLM-Deep feature) that were built using Cox models regularized with the least absolute shrinkage and selection operator. We compared their prognostic performances using stratified fivefold cross-validation. In a median follow-up of 61 months, 110/437 patients experienced BCR. CDLM-Deep feature achieved the best performance (hazard ratio [HR] = 7.72), followed by DLM-Deep feature (HR = 4.37) or RM-Multi (HR = 2.67). CRM-Multi performed moderately. Our results confirm the superior performance of our mpMRI-derived DL algorithm over conventional radiomics.
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Affiliation(s)
- Hye Won Lee
- Samsung Medical Center, Department of Urology, Sungkyunkwan University School of Medicine, Seoul 06351, Republic of Korea
| | - Eunjin Kim
- Department of Electrical and Computer Engineering, Sungkyunkwan University, Suwon 16419, Republic of Korea
| | - Inye Na
- Department of Electrical and Computer Engineering, Sungkyunkwan University, Suwon 16419, Republic of Korea
| | - Chan Kyo Kim
- Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Republic of Korea
| | - Seong Il Seo
- Samsung Medical Center, Department of Urology, Sungkyunkwan University School of Medicine, Seoul 06351, Republic of Korea
| | - Hyunjin Park
- Department of Electrical and Computer Engineering, Sungkyunkwan University, Suwon 16419, Republic of Korea
- Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon 16419, Republic of Korea
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Menges D, Piatti MC, Omlin A, Cathomas R, Benamran D, Fischer S, Iselin C, Küng M, Lorch A, Prause L, Rothermundt C, O'Meara Stern A, Zihler D, Lippuner M, Braun J, Cerny T, Puhan MA. Patient and General Population Preferences Regarding the Benefits and Harms of Treatment for Metastatic Prostate Cancer: A Discrete Choice Experiment. EUR UROL SUPPL 2023; 51:26-38. [PMID: 37187724 PMCID: PMC10175729 DOI: 10.1016/j.euros.2023.03.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/03/2023] [Indexed: 05/17/2023] Open
Abstract
Background Patient preferences for treatment outcomes are important to guide decision-making in clinical practice, but little is known about the preferences of patients with metastatic hormone-sensitive prostate cancer (mHSPC). Objective To evaluate patient preferences regarding the attributed benefits and harms of systemic treatments for mHSPC and preference heterogeneity between individuals and specific subgroups. Design setting and participants We conducted an online discrete choice experiment (DCE) preference survey among 77 patients with metastatic prostate cancer (mPC) and 311 men from the general population in Switzerland between November 2021 and August 2022. Outcome measurements and statistical analysis We evaluated preferences and preference heterogeneity related to survival benefits and treatment-related adverse effects using mixed multinomial logit models and estimated the maximum survival time participants were willing to trade to avert specific adverse effects. We further assessed characteristics associated with different preference patterns via subgroup and latent class analyses. Results and limitations Patients with mPC showed an overall stronger preference for survival benefits in comparison to men from the general population (p = 0.004), with substantial preference heterogeneity between individuals within the two samples (both p < 0.001). There was no evidence of differences in preferences for men aged 45-65 yr versus ≥65 yr, patients with mPC in different disease stages or with different adverse effect experiences, or general population participants with and without experiences with cancer. Latent class analyses suggested the presence of two groups strongly preferring either survival or the absence of adverse effects, with no specific characteristic clearly associated with belonging to either group. Potential biases due to participant selection, cognitive burden, and hypothetical choice scenarios may limit the study results. Conclusions Given the relevant heterogeneity in participant preferences regarding the benefits and harms of treatment for mHSPC, patient preferences should be explicitly discussed during decision-making in clinical practice and reflected in clinical practice guidelines and regulatory assessment regarding treatment for mHSPC. Patient summary We examined the preferences (values and perceptions) of patients and men from the general population regarding the benefits and harms of treatment for metastatic prostate cancer. There were large differences between men in how they balanced the expected survival benefits and potential adverse effects. While some men strongly valued survival, others more strongly valued the absence of adverse effects. Therefore, it is important to discuss patient preferences in clinical practice.
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Affiliation(s)
- Dominik Menges
- Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland
- Corresponding author. Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Hirschengraben 84, 8001 Zurich, Switzerland. Tel. +41 44 6344615.
| | - Michela C. Piatti
- Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland
| | - Aurelius Omlin
- Department of Medical Oncology and Hematology, Kantonsspital St. Gallen, St. Gallen, Switzerland
- Onkozentrum Zürich, Zurich, Switzerland
| | - Richard Cathomas
- Division of Oncology/Hematology, Kantonsspital Graubünden, Chur, Switzerland
| | - Daniel Benamran
- Department of Urology, Hôpitaux Universitaires Genève, Geneva, Switzerland
| | - Stefanie Fischer
- Department of Medical Oncology and Hematology, Kantonsspital St. Gallen, St. Gallen, Switzerland
| | - Christophe Iselin
- Department of Urology, Hôpitaux Universitaires Genève, Geneva, Switzerland
| | - Marc Küng
- Department of Oncology, Hôpital Cantonal Fribourg, Fribourg, Switzerland
| | - Anja Lorch
- Department of Medical Oncology and Hematology, University Hospital Zurich, Zurich, Switzerland
| | - Lukas Prause
- Department of Urology, Kantonsspital Aarau, Aarau, Switzerland
| | - Christian Rothermundt
- Department of Medical Oncology and Hematology, Kantonsspital St. Gallen, St. Gallen, Switzerland
| | - Alix O'Meara Stern
- Department of Oncology, Réseau Hospitalier Neuchâtelois, Neuchâtel, Switzerland
| | - Deborah Zihler
- Department of Oncology, Hematology and Transfusion Medicine, Kantonsspital Aarau, Aarau, Switzerland
| | - Max Lippuner
- Europa Uomo Switzerland, Ehrendingen, Switzerland
| | - Julia Braun
- Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland
| | - Thomas Cerny
- Foundation Board, Cancer Research Switzerland, Bern, Switzerland
- Human Medicines Expert Committee, Swissmedic, Bern, Switzerland
| | - Milo A. Puhan
- Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland
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