A Reliable Nomogram Model to Predict the Recurrence of Chronic Subdural Hematoma After Burr Hole Surgery

Clinical Use of Hematoma Volume Based On Automated Segmentation of Chronic Subdural Hematoma Using 3D U-Net

PURPOSE

To propose a method for calculating hematoma volume based on automatic segmentation of chronic subdural hematoma (CSDH) using 3D U‑net and investigate whether it can be used clinically to predict recurrence.

METHODS

Hematoma volumes manually measured from pre- and postoperative computed tomography (CT) images were used as ground truth data to train 3D U‑net in 200 patients (400 CT scans). A total of 215 patients (430 CT scans) were used as test data to output segmentation results from the trained 3D U‑net model. The similarity with the ground truth data was evaluated using Dice scores for pre and postoperative separately. The recurrence prediction accuracy was evaluated by obtaining receiver operating characteristic (ROC) curves for the segmentation results. Using a typical mobile PC, the computation time per case was measured and the average time was calculated.

RESULTS

The median Dice score of the test data were preoperative hematoma volume (Pre-HV): 0.764 and postoperative subdural cavity volume (Post-SCV): 0.741. In ROC analyses assessing recurrence prediction, the area under the curve (AUC) of the manual was 0.755 in Pre-HV, whereas the 3D U‑net was 0.735. In Post-SCV, the manual AUC was 0.779; the 3D U‑net was 0.736. No significant differences were found between manual and 3D U‑net for all results. Using a mobile PC, the average time taken to output the test data results was 30 s per case.

CONCLUSION

The proposed method is a simple, accurate, and clinically applicable; it can contribute to the widespread use of recurrence prediction scoring systems for CSDH.

A Linear Regression Equation for Predicting the Residual Volume of Chronic Subdural Hematoma 1 Week After Surgery

Objective

The outcome of chronic subdural hematoma (CSDH) is influenced not only by the choice of treatment but also by various baseline characteristics. The main objective of this study is to identify the risk factors that can affect the prognosis of CSDH and develop a regression equation based on these risk factors.

Methods

A total of 212 patients with CSDH were included in the study. We collected clinical data including age, gender, and so on, and radiological data including preoperative hematoma volume (V1), effusion volume 1 day after surgery (V2), gas volume 1 day after surgery (V3), and so on. These were considered independent variables, while residual volume 1 week after surgery (V4) was the dependent variable. Univariate linear regression analysis was performed to identify factors that were significantly related. Subsequently, multivariate linear regression analysis was conducted to determine the relationship between each independent variable and the dependent variable. Multiple linear regression analysis was used to obtain a regression equation predicting V4.

Results

We have found that age (t = 3.109, P = 0.002), aspirin (t = 2.762, P = 0.006), hemostatic agents (haemocoagulase, t = 3.731, P < 0.001; vitamin K, t = 2.824, P = 0.005 < 0.05), V2 (t = 8.73, P < 0.001), and V3 (t = 5.968, P < 0.001) are significantly associated with V4. Furthermore, we have developed a regression equation that can predict this volume with CSDH. The fit of the model is robust with an R-squared value of 65.2% > 50%.

Conclusion

Age, aspirin, hemostatic agent, V2, and V3 are significantly associated with V4. We developed a regression equation to predict this volume with CSDH.

Burr hole locations are associated with recurrence in single burr hole drainage surgery for chronic subdural hematoma

Background

Various factors have been reported as risk factors for chronic subdural hematomas (CSDH) recurrence. However, few studies have quantitatively evaluated the impact of CSDH locations and burr hole positions on recurrence. This study aimed to reveal the relation between CSDH recurrence and the locations of CSDH and burr holes.

Methods

Initial single burr hole surgeries for CSDH with a drainage tube between April 2005 and October 2021 at Otemae Hospital were enrolled. Patients' medical records, CSDH volume, and CSDH computed tomography values (CTV) were evaluated. The locations of CSDH and burr holes were assessed using Montreal Neurological Institute coordinates.

Results

A total of 223 patients were enrolled, including 34 patients with bilateral CSDH, resulting in 257 surgeries investigated. The rate of CSDH recurrence requiring reoperation (RrR) was 13.5%. The RrR rate was significantly higher in patients aged ≥76 years, those with bilateral CSDH, and those with postoperative hemiplegia. In RrR, the preoperative CSDH volume was significantly larger, and CTV was significantly smaller. The locations of CSDH had no influence on recurrence. However, in RrR, the locations of burr holes were found to be more lateral and more ventral. Multivariate Cox proportional hazards regression analysis showed that bilateral CSDH, more ventral burr hole positions, and postoperative hemiplegia were risk factors for recurrence.

Conclusions

The locations of burr holes are associated with CSDH recurrence. In RrR, CSDH profiles tend to show a larger volume and reduced CTV. Hemiplegia after burr hole surgery serves as a warning sign for RrR.

Development and validation of a recurrent prediction model for patients with unilateral chronic subdural hematoma without hematoma volumetric analysis

OBJECTIVE

Approximately 10 % of patients with chronic subdural hematoma (CSDH) undergo reoperation after initial surgery. This study aimed to develop a predictive model for the recurrence of unilateral CSDH at initial surgery without hematoma volumetric analysis.

METHODS

This single-center retrospective cohort study evaluated pre- and postoperative computed tomography (CT) images of patients with unilateral CSDH. The pre- and postoperative midline shift (MLS), residual hematoma thickness, and subdural cavity thickness (SCT) were measured. CT images were classified based on the internal architecture of the hematoma (homogenous, laminar, trabecular, separated, and gradation subtypes).

RESULTS

Total 231 patients with unilateral CSDH underwent burr hole craniostomy. After receiver operating characteristic analysis, preoperative MLS and postoperative SCT showed better areas under the curve (AUCs) (0.684 and 0.756, respectively). According to the CT classification of preoperative hematomas, the recurrence rate was significantly higher in the separated/gradation group (18/97, 18.6 %) than in the homogenous/laminar/trabecular group (10/134, 7.5 %). Four-point score was derived from the multivariate model using the preoperative MLS, postoperative SCT, and CT classification. The AUC of this model was 0.796, and the recurrence rates at 0-4 points were 1.7 %, 3.2 %, 13.3 %, 25.0 %, and 35.7 %, respectively.

CONCLUSION

Pre- and postoperative CT findings without hematoma volumetric analysis may predict CSDH recurrence.

Efficacy evaluation of neuroendoscopy vs burr hole drainage in the treatment of chronic subdural hematoma: An observational study

BACKGROUND

Chronic subdural hematoma (CSDH) is a common disease in neurosurgery. The traditional treatment methods include burr hole drainage, bone flap craniectomy and other surgical methods, and there are certain complications such as recurrence, pneumocephalus, infection and so on. With the promotion of neuroendoscopic technology, its treatment effect and advantages need to be further evaluated.

AIM

To study the clinical effect of endoscopic small-bone approach in CSDH.

METHODS

A total of 122 patients with CSDH admitted to our hospital from August 2018 to August 2021 were randomly divided into two groups using the digital table method: the neuroendoscopy group (n = 61 cases) and the burr hole drainage group (n = 61 cases). The clinical treatment effect of the two groups of patients with CSDH was compared.

RESULTS

At the early postoperative stage (1 d and 3 d), the proportion of 1/2 re-expansion of brain tissue in the hematoma cavity and the proportion of complete re-expansion was higher in the neuroendoscopy group than in the burr hole drainage group, and the difference between the two groups was statistically significant (P < 0.05). The recurrence rate of hematoma in the neuroendoscopy group was lower than that in the burr hole drainage group, and the difference between the two groups was statistically significant (P < 0.05). No intracranial hematoma, low cranial pressure, tension pneumocephalus or other complications occurred in the neuroendoscopy group.

CONCLUSION

The neuroendoscopic approach for the treatment of CSDH can clear the hematoma under direct vision and separate the mucosal lace-up. The surgical effect is apparent with few complications and definite curative effect, which is worthy of clinical promotion and application.

Brain re-expansion predict the recurrence of unilateral CSDH: A clinical grading system

Objective

Assessing the risk of postoperative recurrence of chronic subdural hematoma (CSDH) is a clinical focus. To screen the main factors associated with the perioperative hematoma recurrence. The brain re-expansion is the core factor of recurrence. A clinical prognostic scoring system was also proposed.

Methods

We included 295 patients with unilateral CSDH as the training group for modeling. Factors predicting postoperative recurrence requiring reoperation (RrR) were determined using univariate and multivariate regression analyses, and bivariate Pearson correlation coefficient analysis was used to exclude related factors. Receiver operating characteristic curve analysis evaluates the ability of main factors to predict RrR and determines the cut-off value of brain re-expansion rate. We developed a prognostic scoring system and conducted preliminary verification. A verification group including 119 patients with unilateral CSDH was used to verify the grading systems.

Results

The key factors for predicting unilateral CSDH recurrence were cerebral re-expansion rate (≤ 40%) at postoperative days 7–9 (OR 25.91, p < 0.001) and the preoperative CT density classification (isodense or hyperdense, or separated or laminar types) (OR 8.19, p = 0.007). Cerebral atrophy played a key role in brain re-expansion (OR 2.36, p = 0.002). The CSDH prognostic grading system ranged from 0 to 3. An increased score was associated with a more accurate progressive increase in the RrR rate (AUC = 0.856).

Conclusions

Our prognostic grading system could screen clinically high-risk RrR patients with unilateral CSDH. However, increased attention should be paid to brain re-expansion rate after surgery in patients with CSDH.

Risk factors for Drug-resistant Epilepsy (DRE) and a nomogram model to predict DRE development in post-traumatic epilepsy patients

Objectives

To identify factors affecting the development of drug‐resistant epilepsy (DRE), and establish a reliable nomogram to predict DRE development in post‐traumatic epilepsy (PTE) patients.

Methods

This study conducted a retrospective clinical analysis in patients with PTE who visited the Epilepsy Center, Beijing Tiantan Hospital from January 2013 to December 2018. All participants were followed up for at least 3 years, and the development of DRE was assessed. Data from January 2013 to December 2017 were used as development dataset for model building. Those independent predictors of DRE were included in the final multivariable logistic regression, and a derived nomogram was built. Data from January 2018 to December 2018 were used as validation dataset for internal validation.

Results

Complete clinical information was available for 2830 PTE patients (development dataset: 2023; validation dataset: 807), of which 21.06% (n = 596) developed DRE. Among all parameters of interest including gender, age at PTE, family history, severity of traumatic brain injury (TBI), single or multiple injuries, lesion location, post‐TBI treatments, acute seizures, PTE latency, seizure type, status epilepticus (SE), and electroencephalogram (EEG) findings, four predictors showed independent effect on DRE, they were age at PTE, seizure type, SE, and EEG findings. A model incorporating these four variables was created, and a nomogram to calculate the probability of DRE using the coefficients of the model was developed. The C‐index of the predictive model and the validation was 0.662 and 0.690, respectively. The goodness‐of‐fit test indicated good calibration for model development and validation (p = 0.272, 0.572).

Conclusions

The proposed nomogram achieved significant potential for clinical utility in the prediction of DRE among PTE patients. The risk of DRE for individual PTE patients can be estimated by using this nomogram, and identified high‐risk patients might benefit from non‐pharmacological therapies at an early stage.

Risk factors and risk nomogram model of reoperation for hemorrhages after severe traumatic brain injury craniotomy

Objective

This study aimed to explore the risk factors associated with reoperation for postoperative hemorrhages after severe traumatic brain injury (sTBI) craniotomy and establish a risk nomogram model.

Methods

A retrospective case-control study was performed. Overall, 367 patients who were diagnosed with sTBI and fulfilled the inclusion criteria were enrolled from the Department of Neurosurgery of the Affiliated Hospital of Zunyi Medical University between January 2015 and December 2020. They were divided into a reoperation group and a non-reoperation group according to whether they underwent reoperation for hemorrhages. Using univariate binary logistic regression analysis, the possible risk factors were screened. Subsequently, the independent risk factors of reoperation for postoperative hemorrhages were screened using the forward step method of multivariate binary logistic regression analysis, and a corresponding nomogram model was constructed. The receiver operative characteristic (ROC) curve was used to evaluate the reliability of the model. Finally, 30% of the data were randomly selected for internal verification of the model.

Results

The reoperation rate for hemorrhage after sTBI emergency craniotomy was 14.71% (54/367); multivariate logistic regression analysis showed that multiple hemorrhages (odds ratio [OR] = 4.38, 95% confidence interval [CI]: 1.815-10.587, p = 0.001), day or night surgery (OR = 0.26, 95% CI: 0.119-0.547, p < 0.001), operation duration (OR = 0.74, 95% CI: 0.119-0.547, p < 0.025), and abnormal intraoperative blood pressure fluctuation (OR = 4.15, 95% CI: 2.090-8.245, p < 0.001) were statistically significant. The sensitivity and specificity of the nomogram model were 0.815 and 0.661, respectively, and the area under ROC curve was 0.76 (95% CI: 0.705-0.833). Internal verification showed that the area under the ROC curve was 0.783 (95% CI: 0.683-0.883).

Conclusions

Taken together, the results of our study reveal that multiple preoperative intracranial hemorrhages, day and night operation, operation duration, and abnormal fluctuation of intraoperative blood pressure were independent risk factors for postoperative bleeding and reoperation for sTBI. Through the analysis of the influencing factors, a prediction model for the risk of bleeding and reoperation after craniocerebral trauma was developed. Compared with other relevant studies, this prediction model has good prediction efficiency and can be used to predict the occurrence of bleeding and reoperation after sTBI in patients.

A reliable nomogram model for predicting esophageal stricture after endoscopic submucosal dissection

ABSTRACT

Currently, endoscopic submucosal dissection (ESD) has gradually become the diagnosis and treatment of choice for initial esophageal cancer. However, the formation of esophageal stricture after ESD is one of its important complications. In this paper, we intend to identify the risk factors of esophageal stricture to develop a nomogram model to predict the risk of esophageal stricture and validate this model.A total, 159 patients were included in this study, including 21 patients with esophageal stenosis. Multivariate analysis showed that age greater than 60 years, high neutrophil-to-lymphocyte ratio, the extent of esophageal mucosal defect greater than 1/2, and postoperative pathological type of early esophageal squamous cell carcinoma were independent risk factors for predicting esophageal stricture. We constructed a nomogram model to predict esophageal stenosis by these 4 independent predictors.The prediction performance of the model was verified by the area under the receiver operating characteristic curve, the area under the receiver operating characteristic curve of the model was 0.889, and the sensitivity and specificity were 80.00% and 91.28%, respectively, indicating that the prediction performance of the model was good; The calibration curve constructed by internal cross-validation suggested that the predicted results of the nomogram agreed well with the actual observed values.The nomogram model has a high accuracy for predicting esophageal stricture after esophageal ESD and is extremely important to reduce or avoid the occurrence of esophageal stricture. But it needs more external and prospective validation.

External validation of prognostic models predicting outcome after chronic subdural hematoma

BACKGROUND

Several prognostic models for outcomes after chronic subdural hematoma (CSDH) treatment have been published in recent years. However, these models are not sufficiently validated for use in daily clinical practice. We aimed to assess the performance of existing prediction models for outcomes in patients diagnosed with CSDH.

METHODS

We systematically searched relevant literature databases up to February 2021 to identify prognostic models for outcome prediction in patients diagnosed with CSDH. For the external validation of prognostic models, we used a retrospective database, containing data of 2384 patients from three Dutch regions. Prognostic models were included if they predicted either mortality, hematoma recurrence, functional outcome, or quality of life. Models were excluded when predictors were absent in our database or available for < 150 patients in our database. We assessed calibration, and discrimination (quantified by the concordance index C) of the included prognostic models in our retrospective database.

RESULTS

We identified 1680 original publications of which 1656 were excluded based on title or abstract, mostly because they did not concern CSDH or did not define a prognostic model. Out of 18 identified models, three could be externally validated in our retrospective database: a model for 30-day mortality in 1656 patients, a model for 2 months, and another for 3-month hematoma recurrence both in 1733 patients. The models overestimated the proportion of patients with these outcomes by 11% (15% predicted vs. 4% observed), 1% (10% vs. 9%), and 2% (11% vs. 9%), respectively. Their discriminative ability was poor to modest (C of 0.70 [0.63-0.77]; 0.46 [0.35-0.56]; 0.59 [0.51-0.66], respectively).

CONCLUSIONS

None of the examined models showed good predictive performance for outcomes after CSDH treatment in our dataset. This study confirms the difficulty in predicting outcomes after CSDH and emphasizes the heterogeneity of CSDH patients. The importance of developing high-quality models by using unified predictors and relevant outcome measures and appropriate modeling strategies is warranted.

Development and validation of a prognostic prediction model for antithrombotic-related chronic subdural hematoma in patients with recent acute myocardial infarction

BACKGROUND

Antithrombotic therapy is a cornerstone of acute myocardial infarction (AMI) treatment and is thought to be associated with an increased risk of chronic subdural hematoma (CSDH). However, no well-established model exists to predict subsequent antithrombotic treatment outcomes after CSDH in patients with recent AMI. We aimed to identify a prognostic model to predict the 6-month outcome of treatment with antithrombotic therapy.

METHODS

This multicenter retrospective analysis involved 553 patients with recent AMI with antithrombotic-related CSDH. Several candidate clinical variables and biomarkers were examined in the training cohort (Chengdu training cohort; n=368). Patients with unfavorable outcomes had experienced at least 1 of the following: major adverse cardiovascular events (MACE), recurrence, or a modified Rankin scale (mRS) score of 2 to 6. To develop a 6-month outcome prediction model, three approaches were used: (I) a demographic variable model, (II) a clinical marker model and (III) a decision-driven model. A clinical outcome prediction model based on the superior predictors was assessed by logistic regression analysis. The nomogram for the final model was internally validated using a bootstrap procedure and externally validated in an independent cohort (Anhui cohort; n=185).

RESULTS

Model A produced 7 predictors of unfavorable outcomes, while models B and C yielded 2 and 1 predictors, respectively. The areas under the curve (AUC) increased from 0.743 [model A; 95% confidence interval (CI): 0.680-0.782] to 0.889 (model A + B + C; 95% CI: 0.851-0.916). The final prediction model included age, systolic blood pressure (SBP), body mass index (BMI), the Glasgow Coma Scale (GCS), the estimated glomerular filtration rate (eGFR), the early resumption of antithrombotic therapy, hematoma thickness and the presence of abdominal obesity, frailty and previous bleeding. Internal and external validation of the selected final model revealed adequate C-statistics and calibration slope values (internal validation: 0.81 and 0.78; external validation: 0.80 and 0.76, respectively).

CONCLUSIONS

This model provided a risk stratification tool to predict unfavorable outcomes in patients with recent AMI with antithrombotic-related CSDH. Because the study was based on ten readily practical and available variables, it may be widely applicable to guide management and complement clinical assessment.

Radiological prognostic factors of chronic subdural hematoma recurrence: a systematic review and meta-analysis

Purpose

Chronic subdural hematoma (CSDH) is associated with high recurrence rates. Radiographic prognostic factors may identify patients who are prone for recurrence and who might benefit further optimization of therapy. In this meta-analysis, we systematically evaluated pre-operative radiological prognostic factors of recurrence after surgery.

Methods

Electronic databases were searched until September 2020 for relevant publications. Studies reporting on CSDH recurrence in symptomatic CSDH patients with only surgical treatment were included. Random or fixed effects meta-analysis was used depending on statistical heterogeneity.

Results

Twenty-two studies were identified with a total of 5566 patients (mean age 69 years) with recurrence occurring in 801 patients (14.4%). Hyperdense components (hyperdense homogeneous and mixed density) were the strongest prognostic factor of recurrence (pooled RR 2.83, 95% CI 1.69–4.73). Laminar and separated architecture types also revealed higher recurrence rates (RR 1.37, 95% CI 1.04–1.80 and RR 1.76 95% CI 1.38–2.16, respectively). Hematoma thickness and midline shift above predefined cut-off values (10 mm and 20 mm) were associated with an increased recurrence rate (RR 1.79, 95% CI 1.45–2.21 and RR 1.38, 95% CI 1.11–1.73, respectively). Bilateral CSDH was also associated with an increased recurrence risk (RR 1.34, 95% CI 0.98–1.84).

Limitations

Limitations were no adjustments for confounders and variable data heterogeneity. Clinical factors could also be predictive of recurrence but are beyond the scope of this study.

Conclusions

Hyperdense hematoma components were the strongest prognostic factor of recurrence after surgery. Awareness of these findings allows for individual risk assessment and might prompt clinicians to tailor treatment measures.

A nomogram to predict metastasis of soft tissue sarcoma of the extremities

Soft tissue sarcoma (STS) of the extremities are a rare tumor. Metastases develop in about 40%-50% of patients, most of whom die from their disease. We sought to identify potential risk factors associated with metastatic diseases upon presentation for patients with STS and established a reliable nomogram model to predict distant metastasis of STS at presentation. The current study retrospectively analyzed 3884 STS of the extremities or trunk patients from the Surveillance, Epidemiology, and End Results (SEER) database between 2010 and 2015. Based on patient registration, all patients were randomly allocated to training sets and validation sets (2:1). Then, univariate and binary logistic regression analysis was used to determine the significantly correlated predictors of metastasis. Finally, the nomogram model was established, using these predictors and validated it. 311 (8.21%) of the cases experienced distant metastatic disease was present at the time of presentation. The nomogram was developed from age, histology subtype, primary site, tumor size, grade and depth. Encouragingly, the nomogram showed favorable calibration with C-index 0.790 in the training set and 0.801 in validation set. The DCA showed that the novel model was clinically useful. This nomogram model had a high precision to predict the metastasis of soft tissue sarcoma of the extremities. We expect this model could be used in different clinical consultation and established risk assessment.

Development of the Subdural Hematoma in the Elderly (SHE) score to predict mortality

OBJECTIVE

The purpose of this study was to describe the development of a novel prognostic score, the Subdural Hematoma in the Elderly (SHE) score. The SHE score is intended to predict 30-day mortality in elderly patients (those > 65 years of age) with an acute, chronic, or mixed-density subdural hematoma (SDH) after minor, or no, prior trauma.

METHODS

The authors used the Prognosis Research Strategy group methods to develop the clinical prediction model. The training data set included patients with acute, chronic, and mixed-density SDH. Based on multivariate analyses from a large data set, in addition to review of the extant literature, 3 components to the score were selected: age, admission Glasgow Coma Scale (GCS) score, and SDH volume. Patients are given 1 point if they are over 80 years old, 1 point for an admission GCS score of 5-12, 2 points for an admission GCS score of 3-4, and 1 point for SDH volume > 50 ml. The sum of points across all categories determines the SHE score.

RESULTS

The 30-day mortality rate steadily increased as the SHE score increased for all SDH acuities. For patients with an acute SDH, the 30-day mortality rate was 3.2% for SHE score of 0, and the rate increased to 13.1%, 32.7%, 95.7%, and 100% for SHE scores of 1, 2, 3, and 4, respectively. The model was most accurate for acute SDH (area under the curve [AUC] = 0.94), although it still performed well for chronic (AUC = 0.80) and mixed-density (AUC = 0.87) SDH.

CONCLUSIONS

The SHE score is a simple clinical grading scale that accurately stratifies patients' risk of mortality based on age, admission GCS score, and SDH volume. Use of the SHE score could improve counseling of patients and their families, allow for standardization of clinical treatment protocols, and facilitate clinical research studies in SDH.

Factors influencing the results of surgical therapy of non-acute subdural haematomas

PURPOSE

To identify predictive factors with an impact on the outcome of surgical treatment of non-acute subdural haematomas (NASH).

METHODS

One hundred eleven patients who underwent an evacuation of 132 NASH by means of burr hole or craniotomy from January 2014 to December 2018 were retrospectively analyzed. We evaluated the impact of factors that could possibly predict the result of surgical treatment. The assessment was focused on the impact of factors, such as age, gender, pre-operative clinical symptoms, timing and extent of surgical procedure, intake of anticoagulants and antiplatelet drugs, morphological type, recurrence, side localization or bilateral occurrence of NASH. Patients' functional outcome was quantified using the Glasgow Outcome Score (GOS) with a follow-up period of 3 months.

RESULTS

Morphological type of NASH did not have any significant impact on the final GOS. The risk factors associated with less favorable GOS included preoperative intake of anticoagulants and preoperative finding of phatic disorder, quantitative disorder of consciousness and disorientation. Preoperative intake of antiplatelet drugs or anticoagulants and craniotomy were risk factors for postoperative development of a surgically significant acute extracerebral haematoma. The complications occurred significantly more often after a craniotomy when compared to the burr hole evacuation (p = 0.0163), but the incidence of recurrence of NASH was significantly lower (p = 0.0439).

CONCLUSION

The risk factors for the surgical treatment of NASH included preoperative intake of antithrombotic drugs and evacuation of NASH through craniotomy. Craniotomy resulted in a significantly lower incidence of recurrence.