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Madendere S, Kılıç M, Köseoğlu E, Aykanat İC, Eden AB, Coşkun B, Tekkalan FB, Balbay MD. Rational use of Ga-68 PSMA PET-CT according to nomograms and risk groups for the detection of lymph node metastasis in prostate cancer. Urol Oncol 2024; 42:29.e9-29.e15. [PMID: 38114351 DOI: 10.1016/j.urolonc.2023.11.006] [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: 08/14/2023] [Revised: 10/18/2023] [Accepted: 11/06/2023] [Indexed: 12/21/2023]
Abstract
OBJECTIVES The aim was to ensure efficient utilization of PSMA PET-CT by examining the correlation of pathological lymph node metastasis with nomogram scores and risk classifications. METHODS AND MATERIALS Robot-assisted radical prostatectomy and bilateral pelvic lymph node dissections for pelvic lymph nodes were performed using the same template. Bilaterally pelvic lymph nodes were removed within the boundaries of genitofemoral nerves, psoas muscle and lateral pelvic wall laterally, ureteric crossing of the iliac vessels superiorly, lateral bladder wall medially, Cooper ligaments distally, and endopelvic fascia, neurovascular bundles and internal iliac arteries posteriorly. Clinical nomograms were used to calculate the probability of lymph node metastasis preoperatively. Using receiver operating characteristics analysis, discriminatory cut-offs were calculated. The diagnostic performance of PSMA PET-CT was determined for detecting lymph node metastasis. RESULTS For 81 patients, the median age was 64 years. The median PSA was 6.8 ng/ml. Most patients were in the D'Amico intermediate (56.8%) and high (37%) risk groups. Median Briganti 2017, MSKCC, and Partin scores were 35 (4-99), 37 (8-90), and 12 (2-38), respectively, in pN1 patients. The area under the curve for Briganti 2017, MSKCC, Partin nomograms and PSMA PET-CT scans were 0.852, 0.871, 0.862, and 0.588. Sensitivity, specificity, positive predictive value and negative predictive value for Ga-68 PSMA PET-CT for lymph node metastasis detection were 21.4%, 94%, 42.9%, and 85.1%, respectively, for the whole group. By using higher threshold values for clinical nomograms (Briganti 2017 >32, MSKCC >12, Partin >5), PSMA PET-CT had higher sensitivity (42.9, 30, 27.2) in detecting lymph node metastasis. CONCLUSIONS Patients in the D'Amico high-risk group and those with high nomogram scores are the best candidates who will benefit from preoperative PSMA PET-CT staging to estimate lymph node metastasis.
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Affiliation(s)
| | - Mert Kılıç
- Department of Urology, VKV American Hospital, Istanbul, Turkey
| | - Ersin Köseoğlu
- Department of Urology, Koç University School of Medicine, Istanbul, Turkey
| | | | - Arzu Baygül Eden
- Department of Biostatistics, Koç University School of Medicine, Istanbul, Turkey
| | - Bilgen Coşkun
- Department of Radiology, VKV American Hospital, Istanbul, Turkey
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Fiori C, Checcucci E, Stura I, Amparore D, De Cillis S, Piana A, Granato S, Volpi G, Sica M, Piramide F, Verri P, Manfredi M, De Luca S, Autorino R, Migliaretti G, Porpiglia F. Development of a novel nomogram to identify the candidate to extended pelvic lymph node dissection in patients who underwent mpMRI and target biopsy only. Prostate Cancer Prostatic Dis 2022:10.1038/s41391-022-00565-y. [PMID: 35750851 DOI: 10.1038/s41391-022-00565-y] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Revised: 05/16/2022] [Accepted: 06/10/2022] [Indexed: 11/09/2022]
Abstract
BACKGROUND Nowadays a tool able to predict the risk of lymph-node invasion (LNI) in patients underwent target biopsy (TB) only before radical prostatectomy (RP) is still lacking. Our aim is to develop a model based on mp-MRI and target biopsy (TB) alone able to predict the risk of LNI. METHODS We retrospectively extracted data of patients with preoperative positive mp-MRI and TB only who underwent RARP with ePLND from April 2014 to March 2020. A logistic regression model was performed to evaluate the impact of pre- and intra-operative factors on the risk of LNI. Model discrimination was assessed using an area under (AUC) the ROC curve. A nomogram, and its calibration plot, to predict the risk of LNI were generated based on the logistic model. A validation of the model was done using a similar cohort. RESULTS 461 patients were included, of which 52 (11.27) had LNI. After logistic regression analysis and multivariable model DRE, PI-RADS, seminal vesicle invasion, PSA and worst GS at I and II target lesions were significant predictors of LNI. The AUC was 0.74 [0.67-0.81] 95% CI. The calibration plot shows that our model is very close to the ideal one which is in the 95% CI. After the creation of a visual nomogram, the cut-off to discriminate between the risk or not of LNI was set with Youden index at 60 points that correspond to a risk of LNI of 7%. The model applied on a similar cohort shown a LH+ of 2.58 [2.17-2.98] 95% CI. CONCLUSIONS Our nomogram for patients undergoing MRI-TB only takes into account clinical stage, SVI at MRI, biopsy Gleason pattern and PSA and it is able to identify patients with risk of LNI when a score higher than 7% is achieved.
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Affiliation(s)
- Cristian Fiori
- Division of Urology, Department Of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano, Turin, Italy
| | - Enrico Checcucci
- Division of Urology, Department Of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano, Turin, Italy. .,Department of Surgery, Candiolo Cancer Institute, FPO-IRCCS, Candiolo, Turin, Italy.
| | - Ilaria Stura
- Department of Public Health and Pediatric Sciences, School of Medicine, University of Turin, Turin, Italy
| | - Daniele Amparore
- Division of Urology, Department Of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano, Turin, Italy
| | - Sabrina De Cillis
- Division of Urology, Department Of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano, Turin, Italy
| | - Alberto Piana
- Division of Urology, Department Of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano, Turin, Italy
| | - Stefano Granato
- Division of Urology, Department Of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano, Turin, Italy
| | - Gabriele Volpi
- Division of Urology, Department Of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano, Turin, Italy
| | - Michele Sica
- Division of Urology, Department Of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano, Turin, Italy
| | - Federico Piramide
- Division of Urology, Department Of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano, Turin, Italy
| | - Paolo Verri
- Division of Urology, Department Of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano, Turin, Italy
| | - Matteo Manfredi
- Division of Urology, Department Of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano, Turin, Italy
| | - Stefano De Luca
- Division of Urology, Department Of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano, Turin, Italy
| | | | - Giuseppe Migliaretti
- Department of Public Health and Pediatric Sciences, School of Medicine, University of Turin, Turin, Italy
| | - Francesco Porpiglia
- Division of Urology, Department Of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano, Turin, Italy
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Merhe A, Labban M, Hout M, Bustros G, Abou Heidar N, El-Asmar JM, Bulbul M, El Hajj A. Development of a novel nomogram incorporating platelet-to-lymphocyte ratio for the prediction of lymph node involvement in prostate carcinoma. Urol Oncol 2020; 38:930.e1-930.e6. [PMID: 32736935 DOI: 10.1016/j.urolonc.2020.05.026] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2020] [Revised: 05/20/2020] [Accepted: 05/28/2020] [Indexed: 02/05/2023]
Abstract
OBJECTIVE The available nomograms used to predict lymph node involvement (LNI) are not comprehensive. We sought to derive a novel nomogram incorporating the platelet to lymphocyte ratio (PLR) to predict LNI and compare its performance to validated preoperative risk nomograms in a cohort of men undergoing robotic-assisted radical prostatectomy at our institution. METHODS Our electronic health record was queried for patients who underwent robotic-assisted radical prostatectomy with bilateral pelvic lymphadenectomy between 2013 and 2019. A bootstrapped multivariate logistic regression model was constructed for the predictors of LNI while adjusting for other covariates. Then, we used the derived logistic regression formula to estimate each patient's risk (%) for LNI. Individualized risks were also calculated using the following verified nomograms: Briganti-2012, Cagiannos, Godoy, and Memorial Sloan Kettering Cancer Center. Subsequently, we plotted the risks for our nomogram and the 4 verified nomograms into receiver operating characteristics curves. We reported the area under the curve (AUC) for each of the 5 nomograms and the corresponding 95% confidence interval (CI). RESULTS The cohort included 173 patients, of which 13.9% demonstrated LNI. LNI was associated with higher preoperative prostate-specific antigen (PSA) ≥ 10 [odds ratio [OR] = 4.89; 95% confidence interval [CI] (1.42-16.83)], higher grade (WHO group ≥ 3)[19.21; (2.23-195.25)], and higher percentage of positive biopsy cores (≥60%) [3.38, (1.04-11.00)]. With every 30-unit increase in PLR the risk of LNI increased by 47%. The nomogram derived from our data had the highest AUC [(AUC 0.877; 95% CI (0.806-0.947)]. The Memorial Sloan Kettering Cancer Center and Briganti 2012 displayed almost congruent ability [0.836; 95% CI (0.758-0.915)] and [0.827; (0.752-0.902)] to identify patients with positive nodes in our cohort with perfect sensitivity and negative predictive value. CONCLUSION The nomogram incorporating PLR demonstrated 94.7% sensitivity to predict LNI and avoided pelvic lymphadenectomy in half of the patients at a cut-off between 6.5% and 8.5%. A prospective study with a larger sample is needed to validate our findings.
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Affiliation(s)
- Ali Merhe
- Division of Urology, Department of Surgery, American University of Beirut Medical Center, Lebanon
| | - Muhieddine Labban
- Division of Urology, Department of Surgery, American University of Beirut Medical Center, Lebanon
| | - Mohammad Hout
- Division of Urology, Department of Surgery, American University of Beirut Medical Center, Lebanon
| | - Gerges Bustros
- Division of Urology, Department of Surgery, American University of Beirut Medical Center, Lebanon
| | - Nassib Abou Heidar
- Division of Urology, Department of Surgery, American University of Beirut Medical Center, Lebanon
| | - Jose M El-Asmar
- Division of Urology, Department of Surgery, American University of Beirut Medical Center, Lebanon
| | - Muhammad Bulbul
- Division of Urology, Department of Surgery, American University of Beirut Medical Center, Lebanon
| | - Albert El Hajj
- Division of Urology, Department of Surgery, American University of Beirut Medical Center, Lebanon.
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