Postoperative VTE has been a major concern amongst surgeons for many decades, as has been the risk of bleeding postoperatively. To reduce VTE risk, some surgeons prescribe pharmacological thromboprophylaxis while others opt for only mechanical compressions and early mobilization (Ref). This variation in practice is largely due to challenges in weighing the benefits of reducing VTE and the risk of major bleeding with pharmacological thromboprophylaxis [4]. To achieve a trade-off, various attempts have been made to develop risk-prediction models for predicting the development of VTE in surgical patients. These models include the Wells score and the Caprini score for stratifying risks for VTE, which are already validated and utilized in clinical practice [13, 14]. However, there are currently no radical prostatectomy procedure-specific scoring systems, most certainly for minimally invasive approaches.

The practice of VTE prophylaxis following urological procedures is debated across the globe. In a survey conducted by Gavin et al., only 24% of urologists from the USA had reported to have prescribed thromboprophylaxis as compared to higher percentages (100% and 50%, respectively) in Britain and Ireland [15]. In this present study, 28 days of prophylactic Dalteparin was prescribed starting September 2019, to all patients without contraindications upon discharge. However, no pharmacological prophylaxis was practiced between 2010 and 2019.

The 30-day postoperative incidence of VTE is very variable among urological surgeries. Reported rates are 5.5%, 1.9%, and 1.1% for radical cystectomy (113/2,065), radical nephrectomy (52/4568), and radical prostatectomy (178/16,484), respectively [16]. Our study shows a relatively consistent result of 1.1% (6/522) of VTE within 3 months post-radical prostatectomy. In this study based on the National Surgical Quality Improvement Program database in the USA, Alberts et al. reported that 82.6% (147/178) of patients who developed VTE after radical prostatectomy, VTE only developed after discharge from hospital [16]. Similarly, 66.7% (4/6) of our VTE incidences also occurred only after discharge. This highlights the burden of VTE beyond the time of discharge; thus, the identification of high-risk patients is crucial to guide the extended duration of thromboprophylaxis in outpatient settings.

The main question that stems from this study is whether thromboprophylaxis should be offered to all patients with post-radical prostatectomy. From the results of our study, the authors feel that thromboprophylaxis should be guided by risk stratification rather than the religious use of thromboprophylaxis for all patients due to the following reasons: (1) only 1.1% (6/522) of our study population developed VTE within 3 months postoperatively, (2) 98.9% (516/522) of patients who were not given prophylaxis never developed VTE within 3 months postoperatively, and (3) self-administration of thromboprophylaxis at home may be unnecessary and challenging both mentally and physically for some patients. To support this, Koya et al. have also reported a low 0.21% of VTE incidences over 12 years in 1364 patients who underwent retropubic radical prostatectomy which again questioned the routine use of VTE prophylaxis postoperatively. Two other articles have also concluded no significant reduction in VTE when thromboprophylaxis was offered [14, 17].

In a study from China, Cheng et al. reported a very high incidence (11.4%, 40/351) of VTE in men undergoing robotic-assisted radical prostatectomy procedures. This is much higher than the reported literature from the western parts of the world. One of the reasons could be advanced disease as the mean PSA in those with VTE was 46.97 ng/ml, required a longer operation time, and extended lymph node dissection. Nevertheless, the study reported two new models and a nomogram to predict the risk of VTE. Our approach to data analysis has been different and steered towards establishing a scoring system.

There is an urgent need to produce a risk-scoring system to identify specific patients requiring thromboprophylaxis. The Caprini model has a universal standard for predicting VTE and was introduced to identify patients at risk. However, this scoring system may be more complex and time-consuming to use as it considers over 30 indicators to assess the VTE risk. Moreover, the uniqueness of prostate cancer also warrants a scoring system specific to itself [14]. Hence, we have used our dataset to produce a risk-stratified scoring system unique to prostate cancer men who underwent minimally invasive prostatectomy. Similar to the present study, the ROC reported by Cheng et al. (reference) showed an AUC of 0.988 (95% confidence intervals [CI], 0.977–1.000) for Model B and 0.957 (95% CI 0.928–0.985) for Model A. The AUC for the model used in the present study was 0.97 (95% confidence intervals [CI]: 0.945, 0.999) which is comparable to Cheng et al. but much better than the model proposed by Caprini et al. with an AUC of 0.807 (95% CI 0.700–0.914).

In view of the findings from the present study data, we are proposing a risk-stratified approach to guide thromboprophylaxis specifically for post-minimally invasive prostatectomy patients. We have found the duration of hospital stay, PSA, and BMI had the highest predictive value of VTE. A cut-off point of ≥ 5/24 was obtained for high-risk patients, and 19.5% (102/522) of patients who scored < 5 were low-risk. This shows that thromboprophylaxis could potentially be avoided safely in the 102 low-risk patients who did not develop VTE. The development of this new scoring system may therefore be helpful in avoiding unnecessary thromboprophylaxis in low-risk patients.

This study has limitations including it being a single center with no external validation. The extent to which this approach can be extended into more complex situations is unclear and found to be worth future research efforts. It should be noted that it is likely that a larger study population may help in improving cut-off scores definition. We have attempted to compensate for low numbers by simulation of the dataset based on the real-life prospectively collected episodes of care. The strengths of the present study lie within its prospective design where a cohort of patients was observed with adequate follow-up post-procedure. Data collection also covers all episodes of care recorded in the system linked to each patient through Community-Health-Index numbers unique to each patient. Our results represent the data of a defined geographical area, and they are obtained based on robust modeling of our dataset including the re-sampling of data. We did consider validating our model using previously reported risk models such as the PADUA risk scoring system [18]; however, significant differences in the population of patient, methodology, and non-procedure/condition-specific nature of the model precluded the possibility of any useful information with additive value to the study.