The ongoing dilemma in pelvic lymph node dissection during radical prostatectomy: who should decide and in which patients?

Rational use of Ga-68 PSMA PET-CT according to nomograms and risk groups for the detection of lymph node metastasis in prostate cancer

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.

Development of a novel nomogram to identify the candidate to extended pelvic lymph node dissection in patients who underwent mpMRI and target biopsy only

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.

Development of a novel nomogram incorporating platelet-to-lymphocyte ratio for the prediction of lymph node involvement in prostate carcinoma

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.