|Year : 2020 | Volume
| Issue : 2 | Page : 528-533
A simplified model of Clinical Research Office of Endourological Society nomogram to predict percutaneous nephrolithotomy outcomes
Abd E. M. Elderay1, Mohamed M Abdallah1, Mohamed A Selim1, Ahmed Hamady Mostafa2
1 Department of Urology, Faculty of Medicine, Menoufia University, Menoufia, Egypt
2 Department of Urology, Alex, Police Hospital, Ministry of Interior, Alexandria, Egypt
|Date of Submission||14-Aug-2019|
|Date of Decision||12-Oct-2019|
|Date of Acceptance||14-Oct-2019|
|Date of Web Publication||27-Jun-2020|
Ahmed Hamady Mostafa
Source of Support: None, Conflict of Interest: None
The aim was to predict stone-free status calculated by the Clinical Research Office of Endourological Society (CROES) nomogram and to test the accuracy of our regression model to predict outcomes of percutaneous nephrolithotomy (PCNL).
Patients and methods
From July 2018 to May 2019, data of 100 patients who underwent PCNL procedure at Urology Department of the Menoufia University were collected, and postoperative results were compared with the preoperative predicted stone-free status. The CROES nomogram was applied to the data of all cases using its scale to calculate the total score and percent of stone-free status. The authors used binary logistic regression to test whether the six factors in the study can predict the PCNL outcome. We compared the calculated probabilities of stone free by the regression model with the traditional method using the six parameters on the scale of nomogram.
A total of 100 patients were included in the study. Mean patients' age was 41 ± 9.6 years, and mean stone burden was 564.59 ± 533.869 mm2. Postoperative treatment success rate was 62%. CROES score was found to be an independent predictor of treatment success. The estimated area under the curve was 0.96, and the model provided good calibration. The accuracy of the fitted logistic model was 78% when using it as a single method when compared with the probabilities of CROES nomogram.
CROES nomogram is an efficient tool to predict outcomes of PCNL. The model has noticeable accuracy in predicting PCNL outcomes using the most influent variables in the CROES nomogram.
Keywords: nomogram, percutaneous nephrolithotomy, regression analysis, reliability, stone-free rates
|How to cite this article:|
Elderay AE, Abdallah MM, Selim MA, Mostafa AH. A simplified model of Clinical Research Office of Endourological Society nomogram to predict percutaneous nephrolithotomy outcomes. Menoufia Med J 2020;33:528-33
|How to cite this URL:|
Elderay AE, Abdallah MM, Selim MA, Mostafa AH. A simplified model of Clinical Research Office of Endourological Society nomogram to predict percutaneous nephrolithotomy outcomes. Menoufia Med J [serial online] 2020 [cited 2020 Jul 16];33:528-33. Available from: http://www.mmj.eg.net/text.asp?2020/33/2/528/287767
| Introduction|| |
After urologists adopted percutaneous nephrolithotomy (PCNL) with a standardization of its practice, there has been a dramatic reduction in morbidity and mortality as a result of renal urolithiasis. PCNL has now become the most preferred procedure used to treat large and complex kidney stones. Many large-scale studies have shown that PCNL is an effective procedure that offers a high postoperative stone-free rate (SFR).
The preoperative selection of the most suitable procedure is vital to decrease complications and increase the SFR. Applying computed tomography in choosing the most appropriate line of treatment allowed us to move toward the right direction by giving detailed anatomical information.
Several scoring systems have been proposed by a number of authors for use in the percutaneous management of nephrolithiasis to allow appropriate counseling of patients, decrease adverse results, and provide a means for the standardized reporting of stone complexity and postoperative patient outcomes.
Smith et al. developed the Clinical Research Office of Endourological Society (CROES) nomogram using data from the CROES PCNL global study which included 2086 patients from 96 centers worldwide.
Several preoperative variables were defined and compared with their SFRs, defined as an absence of greater than 4 mm residual stones using KUB radiography and binary logistic regression for statistical analysis.
Multiple variants such as stone burden, case volume, previous stone treatment, presence of Staghorn calculus, and stone location were found to be predictive of stone-free outcomes and overall procedure success.
The aim of this study was to assess the applicability of the CROES nomogram in predicting the treatment outcomes of PCNL at Menoufia University Hospital.
| Patients and Methods|| |
From July 2018 to May 2019, the data of 100 patients who underwent PCNL procedures for renal stones at the Urology Department of Menoufia University Hospital were collected.
The study included all adult patients with kidney stones who underwent PCNL with an initial, radio-opaque stone size of 20 mm or more and a radiolucent stone size of 20 mm or more who failed medical treatment or Extra Corporeal Shock Wave Lithotripsy. We excluded cases with severe coagulopathy, patients with skeletal deformity, and patients who were generally unfit for surgery along with patients with anatomical abnormalities. A detailed history was compiled for each patient, which included personal data, such as name, age, and sex, as well as a medical history to assess any recent complaints and any associated urinary symptoms.
The medical history was taken to reveal any contraindications to the procedure along with the patient's history of previous urological procedures and any trials of treatment for the recent stones. All participants provided an informed consent, and the study protocol was approved by the Menoufia Ethics Committee.
All patients were subjected preoperatively to noncontrast computed tomography (NCCT) and KUB. The preoperative details from the NCCT were assessed alongside the retrograde pyelography, the intraoperative findings, and the most beneficial way to reach stone-free status. On the first day, postoperative KUB was obtained along with NCCT if the procedure involved radiolucent stones. Patients were defined as stone free if there was no residual greater than 4 mm.
The CROES nomogram was applied to the data of all cases using its scale model to calculate preoperatively the total score and corresponding percentage of stone-free patients after the procedure. Postoperative results were compared with the preoperative predicted percentage of stone-free status.
Our fitted logistic model
Where p is the estimated probability of stone-free status, e is a constant = 2.73, SB is the score of stone burden (mm2), PCNL is the score of prior treatment, and NS is the score of number of stones. All of the three predictors were calculated from CROES nomogram scoring scale [Figure 1] and [Figure 2]).
|Figure 2: Clinical Research Office of Endourological Society nomogram scoring scale.|
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We used binary logistic regression to test whether the six factors in the study can predict the PCNL outcome. The accuracy of the logistic regression model was tested using the receiver operating characteristic curve and area under the curve (AUC) to determine by what percentage the used model predicted the outcome. By using a Microsoft Excel sheet (Microsoft corp, Redmond, Washington, USA), the results of our equation can be calculated in no time.
The stone-free probabilities calculated by our model are compared with those predicted by the CROES nomogram.
Data were analyzed using Statistical Package for the Social Sciences (SPSS) version 24 with statistical significance considered at 0.05 (IBM corp, Armonk, NY, USA). P values below 0.05 indicate significant tests.
| Results|| |
The study included 100 patients, with a mean age of 41 ± 9.6 years. The average radiodensity measured in Hounsfield Units (HU) was 1030.20 ± 334.821 HU, and the mean stone burden was 564.59 ± 533.869 mm2. Regarding the location of stones, the largest proportion of stones were in multiple calyces, representing 55% of the sample. In 27% of the sample, stones were pelvic, and in 10%, they were in the lower calyx.
Data of all patients were plotted on the CROES nomogram. The mean calculated score was 185.37 ± 55.025. The participating sample reported a mean SFR of 84.59 ± 14.344%.
Postoperative follow-up showed that when patients' outcome was arranged in two groups, the stone-free group of patients represented 62 (62%) and the non-stone free group represented 38 (38%) [Table 1].
A multivariate and univariate logistic regression analysis was conducted for 100 patients. The multivariate logistic regression analysis included a full model using all six CROES parameters (stone burden, location of stones, prior treatment, presence of Staghorn stone, number of stones, and case volume), and a reduced model using only parameters that showed statistical significance (stone burden, prior treatment, and number of stones) [Table 2].
|Table 2: Univariate and multivariate logistic regression analyses of predictors of percutaneous nephrolithotomy success using receiver operating characteristic curve area under the curve|
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The stone-free probabilities calculated by our model was compared with those predicted by the CROES nomogram, and the accuracy of the fitted logistic model was 78% when using it as a single method.
Area under the curve and receiver operating characteristic curve
The AUC is 0.959, with a 95% confidence interval of 0.915–1.000. Moreover, the AUC is significantly different from 0.5, as P value is 0.000, meaning that the logistic regression classifies the group significantly better than random [Figure 3].
|Figure 3: Receiver operating characteristic curve demonstrating the sensitivity and specificity of Clinical Research Office of Endourological Society nomogram.|
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| Discussion|| |
With a worldwide increase in renal stone disease, optimization in choosing suitable procedures has become mandatory. Many authors revealed that PCNL is an efficient procedure that offers a high rate of postoperative stone-free results.
Large renal stones are a common problem affecting all population groups around the world, and if untreated, they may cause serious complications. The management of renal stones has progressed significantly over the past few years, with the beginning of the minimally invasive era. This has led to shorter hospital stays, reduced postoperative pain, and faster recovery compared with the previous usual open surgery option. PCNL continues to be the gold standard option for the treatment of complex renal stones and large-sized stones. Modifications in techniques, improvements in equipment, and increasing clinical experience have led to improved SFRs, being achieved with decreased patient morbidity.
Guy's stone score, the STONE score, the CROES nomogram, and the Seoul National University Renal Stone Complexity Score (S-ReSC) are modern scoring systems introduced to provide a standardized grading of stone complexity and percutaneous stone surgery outcomes.
Our study plotted the data of six parameters on the CROES nomogram, and treatment success was defined as the absence of any fragment greater than 4 mm, as in the original study by Smith and colleagues and another study by Gravas and colleagues,.
Our mean patient age was 40.57 ± 9.600 years, which is comparable to that reported by Smith and colleagues in the original study, which reported a mean age of 49.2 ± 14.7 years, and to that reported by Sfoungaristos et al., which was 55.2 ± 13.9 years.
Our study showed there were 64 (64%) males and 36 (36%) female cases, whereas Smith and colleagues reported 59.8% males and 40.2% females. Sfoungaristos and colleagues reported 67% males and 33% females.
With the pre-operative data of the studied cases collected by both KUB and NCCT, 78 cases had radiopaque stones and 22 cases had radiolucent stones, with an overall mean HU of 1030.20 ± 334.821. Sfoungaristos and colleagues also used preoperative KUB and NCCT to include radiolucent stones within their study, whereas Kumar and colleagues used only KUB as a preoperative tool,,.
Smith and colleagues included only the radiopaque stones and considered KUB only as a postoperative indicator for stone-free status. They excluded all patients who were evaluated postoperatively by NCCT scan or ultrasound. This raised doubts concerning the correct evaluation of patients with radiolucent stones or with clinical features, like severe obesity, which may decrease the sensitivity of KUB. Our inclusion criteria overcome these problems as the treatment success outcomes were assessed by NCCT.
Our study included 54 (54%) cases with a single renal stone, whereas multiple stones were found in 46 (46%) cases. This was similar to Smith and colleagues, who reported 54.7% of cases with a single stone and 45.3% with multiple stones.
Our results showed a mean stone burden of 564.59 ± 533.869 mm2, with 670.24 ± 609.804 mm2 in the post-PCNL stone-free group and 384.71 ± 300.967 mm2 in the nonfree group. In comparison with the original study results, stone burden was 463.9 ± 310.0 and 433.5 ± 292.8 mm2 in patients with postoperative stone-free status and 602.2 ± 346.6 mm2 in the non-free group.
These numbers identify the important fact that stone burden comes first among all the predictors of PCNL success, and its effect on the results appeared clearly on a statistical basis, with a P value of less than 0.001, which also was reported by Smith and colleagues, Labadie and colleagues, and Kumar and colleagues.
Our results showed that the more calyces occupied by stones, the less stone-free status we reach. Upon multivariate analysis, 55% of our cases had multiple calyceal stones with a success rate of 35.48%. This is parallel to that reported by Smith and colleagues (39.8%), as also observed by Sfoungaristos and colleagues and Kumar and colleagues.
To overcome this problem, Smith and colleagues suggested combining techniques, and Sfoungaristos and colleagues tried this by incorporating the use of a flexible nephroscope as a standard step after stone fragmentation, inspecting the collecting system and proximal ureter, and removing any residual fragment that could not be approached by the rigid nephroscope,,.
We had only eight (8%) cases with Staghorn stones, and all of them had a residual stone upon postoperative follow-up radiology. This goes along with the results of the global CROES PCNL study, which stated that the presence of Staghorn stones decreases the SFR.
Our mean CROES-calculated total score was 185.37 ± 55.025. Our results revealed that, with increase in the total score, the chance of a stone-free result increased. as the mean total score of the stone-free group was 215.84 ± 40.935, whereas of the non-free was 135.65 ± 35.267. Subsequently, the corresponding percentage of SFR increases. Choi et al. reported an overall mean total score of 202.1 ± 66.4, with 218.8 ± 58.0 in the stone-free group and 140.3 ± 59.1 in the nonfree group.
Our study showed a SFR of 62 (62%) cases and residual stones greater than 4 mm in 38 (38%) cases. Our SFR is less than the original study by Smith and colleagues owing to many factors.
According to Opondo et al., the SFR increases by increasing the case volume of the center with a peak at 120 cases per year, but even with very high case volumes, the SFR appears to decrease owing to a variety of reasons: centers with high case volumes have surgeons with a different level of surgical experience, may have a teaching program for junior surgeons, or also may be a main referral center for the surrounding city or region.
Kumar et al. reported a mean SFR of 76%, but this may be owing to the larger sample (313 patients) and their use of KUB only to detect residual stones.
We developed a new model using a logistic regression analysis based on the most significant factors among the predictors of the CROES nomogram and compared the calculated probabilities of a stone-free outcome produced by our model with the traditional method using all six parameters of the nomogram.
We suppose that the main cause of difference in SFRs is that we included in our study radiolucent stones with postoperative NCCT, whereas Smith and colleagues, for statistical purposes, excluded all patients evaluated postoperatively by computed tomography or ultrasound.
Moreover, our results might be affected by the early nature of the postoperative follow-up as there are residual fragments that may pass through the urinary tract spontaneously. Our study database relied on the single-center experiences of 100 patients with a relatively short inclusion period of 1 year.
Our results show that the CROES nomogram provided high predictive accuracy regardless of the follow-up imaging technique. The AUC was 0.959 with a 95% confidence interval. The receiver operating characteristic curve AUC for predictions based on this nomogram by Tepeler et al. was 0.729.
They also reported that the nomogram is clinically applicable if urologists use a 60% or greater SFR as the threshold to decide whether to perform PCNL or modify the treatment strategy.
The accuracy of our fitted logistic model was 78% when using it as a single method when compared with the probabilities of CROES nomogram. The reason for this is that this is a new, primitive trial to make the nomogram easier to use in daily practice. Moreover, the data were based on a narrow scale.
| Conclusion|| |
The CROES nomogram represents a significant tool to evaluate the complexity of renal stones and provides high-accuracy prediction to estimate postoperative treatment success, expressing its ability to translate well to the clinical setting.
Applying multivariate logistic regression analysis, the scoring system was found to be valid and a significant independent predictor of postoperative efficacy outcomes. Our data show that stone burden, number of stones, and prior treatment are the most influential parameters in predicting PCNL success.
Our fitted logistic model would be a good start in the way of reaching a simple standardized method of predicting stone-free status after PCNL, which would make it easier in daily practice. This, however, is just the precursor to the building of a project with a wider scale and larger number of cases to create an even better, more refined, and standardized model.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
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[Figure 1], [Figure 2], [Figure 3]
[Table 1], [Table 2]