Current decision support tools fail to agree or predict therapeutic decisions in a single cohort of unruptured intracranial aneurysms.

BACKGROUND: There is limited evidence to direct the management of unruptured intracranial aneurysms. Models extrapolated from existing data have been proposed to guide treatment recommendations. The aim of this study is to assess whether a consensus-based treatment score (UIATS) or rupture rate estimation model (PHASES) can be used to benchmark UK multi-disciplinary team (MDT) practice. METHODS: Prospective data was collected on a consecutive series of all patients with unruptured intracranial aneurysms (UIAs) presenting to a major UK neurovascular centre between 2012 and 2015. The agreement between the UIATS and PHASES scores, and their sensitivity and specificity in predicting the real-world MDT outcome were calculated and compared. RESULTS: A total of 366 patients (456 aneurysms) were included in the analysis. The agreement between UIATS and MDT recommendation was low (weighted kappa 0.26 [95% CI 0.19, 0.32]); sensitivity and specificity were also low at 36% and 52% respectively. Groups that the MDT allocated to treatment, equipoise or no treatment had significantly different PHASES scores (p = 0.004). There was no significant difference between the two scores when predicting patients for whom MDT outcome was to recommend aneurysm treatment, but the UIATS score was superior in predicting patients who received an MDT recommendation of 'treatment-equipoise', or 'not-for-treatment' (AUC of 0.73 compared to 0.59 for PHASES). CONCLUSIONS: The models studied failed to agree with the consensus view of multi-disciplinary team in a major neurovascular centre. We conclude that decision support tools such as the UIATS and PHASES scores should not be blindly introduced in respective institutions without prior internal validation, as they may not represent the local reality.

Validation of the Subaxial Cervical Spine Injury Classification score in children: a single-institution experience at a level 1 pediatric trauma center.

OBJECTIVE: The Subaxial Cervical Spine Injury Classification (SLIC) score has not been previously validated for a pediatric population. The authors compared the SLIC treatment recommendations for pediatric subaxial cervical spine trauma with real-world pediatric spine surgery practice. METHODS: A retrospective cohort study at a pediatric level 1 trauma center was conducted in patients < 18 years of age evaluated for trauma from 2012 to 2021. An SLIC score was calculated for each patient, and the subsequent recommendations were compared with actual treatment delivered. Percentage misclassification, sensitivity, specificity, positive (PPV) and negative predictive value (NPV), and area under the receiver operating characteristic (ROC) curve (AUC) were calculated. RESULTS: Two hundred forty-three pediatric patients with trauma were included. Twenty-five patients (10.3%) underwent surgery and 218 were managed conservatively. The median SLIC score was 2 (interquartile range = 2). Sixteen patients (6.6%) had an SLIC score of 4, for which either conservative or surgical treatment is recommended; 27 children had an SLIC score ≥ 5, indicating a recommendation for surgical treatment; and 200 children had an SLIC score ≤ 3, indicating a recommendation for conservative treatment. Of the 243 patients, 227 received treatment consistent with SLIC score recommendations (p < 0.001). SLIC sensitivity in determining surgically treated patients was 79.2% and the specificity for accurately determining who underwent conservative treatment was 96.1%. The PPV was 70.3% and the NPV was 97.5%. There was a 5.7% misclassification rate (n = 13) using SLIC. Among patients for whom surgical treatment would be recommended by the SLIC, 29.6% (n = 8) did not undergo surgery; similarly, 2.5% (n = 5) of patients for whom conservative management would be recommended by the SLIC had surgery. The ROC curve for determining treatment received demonstrated excellent discriminative ability, with an AUC of 0.96 (OR 3.12, p < 0.001). Sensitivity decreased when the cohort was split by age (< 10 and ≥ 10 years old) to 0.5 and 0.82, respectively; specificity remained high at 0.98 and 0.94. CONCLUSIONS: The SLIC scoring system recommended similar treatment when compared with the actual treatment delivered for traumatic subaxial cervical spine injuries in children, with a low misclassification rate and a specificity of 96%. These findings demonstrate that the SLIC can be useful in guiding treatment for pediatric patients with subaxial cervical spine injuries. Further investigation into the score in young children (< 10 years) using a multicenter cohort is warranted.

Validation of late recurrence prediction by gene expression profiles and clinicopathological factors in estrogen receptor-positive breast cancer.

BACKGROUND: The mechanism of late recurrence (LR) of estrogen receptor (ER)-positive breast cancer remains unclear, as previous studies have separately investigated "gene expression profiles" and "clinicopathological factors." Thus, this study aimed to evaluate the predictive capability of LR by combining the two independent factors of gene expression profiles (42-gene classifier: 42GC) and clinicopathological factors (Clinical Treatment Score post-5 years: CTS5) in multiple large cohorts. METHODS: We analyzed microarray CEL file data downloaded from public databases of 28 global cohorts. A total of 2,454 patients with ER-positive breast cancer were analyzed for 42GC, and 1,263 of these, with complete clinicopathological data were analyzed for CTS5. RESULTS: In the analysis of recurrent patients, the 42GC LR and CTS5 low-risk group tended to have LR. Notably, in the analysis of patients with and without recurrence, the highest LR rate beyond 5 years was observed in the CTS5 high-risk group. The combination of the 42GC and CTS5 high-risk groups showed the highest LR rate (16.9%), significantly exceeding that of the 42GC non-LR (NLR) and CTS5 low-risk combination (5.41%) (p = 0.038, odds ratio = 3.53). Furthermore, incorporating a third factor, 95GC, potentially reduced the number of patients prioritized for extended hormonal therapy for approximately one-quarter of patients. CONCLUSIONS: Results confirmed that the two factors, gene expression profiles and clinicopathological factors, affect the time of recurrence. It also showed that the biological predisposition for LR (CTS5 low-risk) differed from the high LR rate (CTS5 high-risk). In clinical practice, patients with the 42GC LR and CTS5 high-risk combination should be prioritized for extended hormonal therapy. The addition of CTS5 and 95GC to 42GC allows for better risk classification of LR.

Comparison of CTS5 risk model and 21-gene recurrence score assay in large-scale breast cancer population and combination of CTS5 and recurrence score to develop a novel nomogram for prognosis prediction.

BACKGROUND: Breast cancer is the most common malignancy in women. Clinical models such as Oncotype DX recurrence score (RS) and Clinical Treatment Score post-5 years (CTS5) model for survival prediction are crucial for clinical practice. However, it remains unclear whether CTS5 or RS would be a more powerful clinical model for recurrence risk evaluation. Therefore, we conducted the present study to compare the performance of CTS5 risk model and RS on different recurrence evaluation. And we further integrated the two models into a novel nomogram to improve the power for prognosis prediction. METHODS: Female patients with invasive hormone receptor positive breast cancer in the Surveillance, Epidemiology, and End Results Program (SEER) database with RS data available were included. The clinicopathological data were directly extracted from SEER database. Participants were divided into three subsets according to recurrence timing (<36 months, between 36 and 60 months, and >60 months) for model evaluation. Survival receiver operating characteristic curve and C-index were calculated to evaluate discrimination. Calibration curve were used to visual inspection for calibration. Model comparison was assessed by net reclassification index (NRI) method. Nomogram prognostic model was developed with the combination of CTS5 score and RS and also included other critical clinicopathological parameters. RESULTS: In total, 64044 breast cancer patients were enrolled for analysis. The number of patients with survival <36 months (early recurrence subset), 36-60 months (intermediate recurrence subset) and >60 months (late recurrence subset) were 64044, 36878 and 15926, respectively. For model discrimination, CTS5 model was superior to RS for overall survival (OS) prediction (likelihood ratio test P < 0 0.001). RS model showed better performance for breast cancer specific survival (BCSS) in late recurrence subsets and worse performance in early and intermediate recurrence subsets than CTS5 (likelihood ratio test P < 0 0.001). For calibration, CTS5 model was superior to RS model for OS, which overestimated the recurrence risk in low-risk subgroup. Both models overestimated the risk for BCSS. In either early/intermediate/late recurrence patient subsets, there was no significant difference in NRI between two models in terms of both BCSS and OS, indicating the two models had comparable prognostic value. The nomogram which combined these two models largely improved the discrimination and calibration power (C-index 0.70-0.72). CONCLUSIONS: Our study proved the CTS5 risk model had comparable prognostic value as RS in HR + breast cancer patients. And the novel nomogram model had better discrimination and calibration than both CTS5 and RS, and future large-scale clinical trials are warranted for further validation.

Comparison of Unruptured Intracranial Aneurysm Treatment Score and PHASES Score in Subarachnoid Hemorrhage Patients With Multiple Intracranial Aneurysms.

Objective: Unruptured Intracranial Aneurysm (UIA) Treatment Score (UIATS) and PHASES score are used to inform treatment decision making for UIAs (treatment or observation). We assessed the ability of the scoring systems to discriminate between ruptured aneurysms and UIAs in a subarachnoid hemorrhage (SAH) cohort with multiple aneurysms. Methods: We retrospectively applied PHASES and UIATS scoring to the aneurysms of 40 consecutive patients with SAH and multiple intracranial aneurysms. Results: PHASES score discriminated better between ruptured aneurysms and UIAs than UIATS. PHASES scores and the difference between the UIATS subscores were higher for ruptured aneurysms compared with UIAs, which reached significance for the PHASES score. PHASES score estimated a low 5-year rupture risk in a larger proportion of the UIAs (≤0.7% in 62.3%, ≤1.7% in 98.4%) than of the ruptured aneurysms (≤0.7% in 22.5%, ≤1.7% in 82.5%). In the 40 ruptured aneurysms, UIATS provided recommendation for treatment in 11 (27.5%), conservative management in 14 (35.0%), and was inconclusive in 15 cases (37.5%). In the 61 UIAs, UIATS recommended treatment in 16 (26.2%), conservative management in 29 (47.5%), and was inconclusive in 16 (26.2%) cases. Conclusion: Similar to previous SAH cohorts, a significant proportion of the ruptured aneurysms exhibited a low-rupture risk. Nevertheless, PHASES score discriminated between ruptured aneurysms and UIAs in our cohort; the lower discriminatory power of UIATS was due to high weights of aneurysm-independent factors. We recommend careful integration of the scores for individual decision making. Large-scale prospective trials are required to establish score-based treatment strategies for UIAs.

Rhabdomyosarcoma in adults: analysis of treatment modalities in a prospective single-center series.

Rhabdomyosarcoma (RMS) is rare in adults and it is generally characterized by poor outcome. In a previous retrospective study, we demonstrated a better prognosis in adults treated with multimodality approach resembling pediatric protocols. Thereafter, we developed specific recommendations based on the principles adopted in pediatric oncology. The present analysis reports the results in a subsequent prospective series. The study included 95 consecutive patients (age 18-77 years) treated from 2002 to 2015 for embryonal and alveolar RMS. As in the previous series, patients were stratified by the appropriateness of their treatment according to therapeutic guidelines for childhood RMS. The 5-year event-free survival (EFS) and overall survival (OS) rates were 33.6% and 40.3%, respectively. The 5-year EFS was 40.8% for patients with the highest treatment score, and 15% for those with lower score, while OS was 44.4% and 24.5%, respectively. The developing of specific recommendations enabled an increase in the number of patients treated with intensive multimodal treatment resembling pediatric strategy (69.7% vs. 39.1% in the retrospective series). This study reinforced the idea that adherence to the principles of pediatric protocols, improves adult RMS outcomes. However, treating adults with pediatric-type strategy is not enough to achieve the results obtained in children. Issues in compliance and a more aggressive biology of adult RMS might have a role in the different outcome according to age. Improving the collaboration between pediatric and adult oncologists in promoting specific clinical and biological research is crucial to improve the outcome for this patient population.

Validation of the unruptured intracranial aneurysm treatment score: comparison with real-world cerebrovascular practice.

OBJECTIVE The purpose of this study was to compare the unruptured intracranial aneurysm treatment score (UIATS) recommendations with the real-world experience in a quaternary academic medical center with a high volume of patients with unruptured intracranial aneurysms (UIAs). METHODS All patients with UIAs evaluated during a 3-year period were included. All factors included in the UIATS were abstracted, and patients were scored using the UIATS. Patients were categorized in a contingency table assessing UIATS recommendation versus real-world treatment decision. The authors calculated the percentage of misclassification, sensitivity, specificity, and area under the receiver operating characteristic (ROC) curve. RESULTS A total of 221 consecutive patients with UIAs met the inclusion criteria: 69 (31%) patients underwent treatment and 152 (69%) did not. Fifty-nine (27%) patients had a UIATS between -2 and 2, which does not offer a treatment recommendation, leaving 162 (73%) patients with a UIATS treatment recommendation. The UIATS was significantly associated with treatment (p < 0.001); however, the sensitivity, specificity, and percentage of misclassification were 49%, 80%, and 28%, respectively. Notably, 51% of patients for whom treatment would be recommended by the UIATS did not undergo treatment in the real-world cohort and 20% of patients for whom conservative management would be recommended by UIATS had intervention. The area under the ROC curve was 0.646. CONCLUSIONS Compared with the authors' experience, the UIATS recommended overtreatment of UIAs. Although the UIATS could be used as a screening tool, individualized treatment recommendations based on consultation with a cerebrovascular specialist are necessary. Further validation with longitudinal data on rupture rates of UIAs is needed before widespread use.

A generic viral dynamic model to systematically characterize the interaction between oncolytic virus kinetics and tumor growth.

Oncolytic viruses (OV) represent an encouraging new therapeutic concept for treatment of human cancers. OVs specifically replicate in tumor cells and initiate cell lysis whilst tumor cells act as endogenous bioreactors for virus amplification. This complex bidirectional interaction between tumor and oncolytic virus hampers the establishment of a straight dose-concentration-effect relation. We aimed to develop a generic mathematical pharmacokinetic/pharmacodynamics (PK/PD) model to characterize the relationship between tumor cell growth and kinetics of different OVs. U87 glioblastoma cell growth and titer of Newcastle disease virus (NDV), reovirus (RV) and parvovirus (PV) were systematically determined in vitro. PK/PD analyses were performed using non-linear mixed effects modeling. A viral dynamic model (VDM) with a common structure for the three different OVs was developed which simultaneously described tumor growth and virus replication. Virus specific parameters enabled a comparison of the kinetics and tumor killing efficacy of each OV. The long-term interactions of tumor cells with NDV and RV were simulated to predict tumor reoccurrence. Various treatment scenarios (single and multiple dosing with same OV, co-infection with different OVs and combination with hypothetical cytotoxic compounds) were simulated and ranked for efficacy using a newly developed treatment rating score. The developed VDM serves as flexible tool for the systematic cross-characterization of tumor-virus relationships and supports preselection of the most promising treatment regimens for follow-up in vivo analyses.