Impact of treatment decision algorithms on treatment costs in recurrent glioblastoma: a health economic study.

AIMS: Recurrent glioblastoma (GBM) is a disease with poor prognosis. Although several therapeutic approaches such as chemotherapy, irradiation or surgery have been investigated, there is no established standard therapy. A recent survey among Swiss neuro-oncology centres has shown considerable controversy in the treatment recommendations for any specific scenario of recurrent GBM. In view of the cost differences of the available treatment alternatives, the aim of our study was assess the financial impact of different institutional therapeutic strategies for recurrent GBM in Switzerland. METHODS: We created a decision analytic model for each of the eight centres participating in the initial study with a centre-specific treatment algorithm to evaluate the average treatment cost per patient. The probability of decision criteria was varied by univariate and probabilistic sensitivity analysis over a wide range to account for the high level of uncertainty. Treatment costs were calculated from the perspective of the Swiss healthcare payer. RESULTS: Mean treatment costs per patient calculated on the basis of the institutional treatment algorithms ranged from CHF 13,748 to CHF 22,072 depending on the probability of individual decision criteria. The most influential decision factors for the mean treatment costs were the probability of fit patients and the proportion of patients with resectable tumour recurrences. There was a significant correlation between the complexity of treatment algorithms in a centre and the resulting mean treatment costs. CONCLUSIONS: Institutional treatment algorithms can be used to estimate the average treatment costs per patient, which are, however, highly sensitive to probability changes of individual decision criteria. Our study demonstrates a high variability in treatment costs for recurrent GBM among eight Swiss neuro-oncology centres based on individual institutional treatment algorithms.

A cost-effectiveness analysis of consolidative local therapy in oligometastatic non-squamous non-small cell lung cancer (NSCLC).

BACKGROUND: Novel systemic therapies have improved the prognosis of metastatic non-small cell lung cancer (NSCLC), but costs of some of these drugs are a matter of ongoing debate. More recently, local therapies (LT) such as radiotherapy and surgery have been suggested as additional treatment in oligometastatic NSCLC demonstrating an improved progression-free survival (PFS) in a phase II trial compared to maintenance chemotherapy (MC) alone. The aim of this analysis was to assess the cost-effectiveness of local therapies in oligometastatic NSCLC. METHODS: We constructed a Markov model comparing the cost-effectiveness of LT versus MC for oligometastatic NSCLC from the Swiss healthcare payer's perspective. Treatment specifications and PFS were based on the phase II trial (NCT01725165). Overall survival (OS) was inferred from a recent phase III trial. Utilities were taken from published data. Primary outcome was the incremental cost-effectiveness-ratio (ICER, costs in Swiss Francs (CHF) per quality-adjusted life-year (QALY) gained). RESULTS: PFS in the model was 3.8 months for MC and 11.4 months for LT (compared to 3.9 months and 11.9 months in the trial). OS in the model was 15.5 months in both arms. LT was cost-effective with a gain of 0.24 QALYs at an additional cost of CHF 9641, resulting in an ICER of CHF 40,972/QALY gained. Probabilistic sensitivity analyses demonstrated that LT was dominant or cost-effective at a willingness-to-pay threshold of CHF 100,000 per QALY in 61.7% of the simulations. CONCLUSIONS: LT may be cost-effective for selected patients with oligometastatic NSCLC responding to first-line systemic therapy.

Assessment of pancreatic colloid carcinoma using 18F-FDG PET/CT compared with MRI and enhanced CT.

Pancreatic colloid carcinoma (CC) is a rare sub-type of pancreatic adenocarcinoma which has an improved prognosis compared with pancreatic ductal carcinoma. Consequently, the early detection of CC by imaging may be of great significance in guiding patient management and therapeutic decisions. The present study aimed to analyze 18F-FDG PET/CT findings of CC in comparison to MRI and CT. PET/CT findings in 5 patients with CC were retrospectively reviewed based on visual interpretation and semi-quantitative index of SUVmax and TNR. Four patients received dual-time-point PET/CT scans. Additionally, one patient underwent contrast-enhanced CT scan, one MRI, and three received both. A total of five lesions were detected in five patients. Visually, two cases presented with mild FDG uptake, two with moderate and one with high. The mean of SUVmax and TNR was 5.1±2.2 and 2.8±0.7, respectively. Compared with CCs with low SUVmax, CCs with high SUVmax were more aggressive. No distant metastases were observed in five cases. Among four patients with dual-time-point PET/CT imaging, SUVmax increased in three cases and decreased in one case. The mean early and delayed SUVmax were 4.2±1.1 and 4.7±1.9, respectively (P>0.05). Radiological findings mainly included septated cystic components, internal sponge-like contrast-enhancement, calcification and 'salt-and-pepper sign' on MRI T2-weighted imaging. Thus, PET/CT provided additional information on metabolic tumor activity as well as locoregional and distant staging, which are important prognostic markers and may improve further patient management. However, PET/CT did not show any findings in addition to MRI and contrast-enhanced CT that were unique to CC and allowed a clear differentiation from other pancreatic malignancies.

Applied Swarm-based medicine: collecting decision trees for patterns of algorithms analysis.

BACKGROUND: The objective consensus methodology has recently been applied in consensus finding in several studies on medical decision-making among clinical experts or guidelines. The main advantages of this method are an automated analysis and comparison of treatment algorithms of the participating centers which can be performed anonymously. METHODS: Based on the experience from completed consensus analyses, the main steps for the successful implementation of the objective consensus methodology were identified and discussed among the main investigators. RESULTS: The following steps for the successful collection and conversion of decision trees were identified and defined in detail: problem definition, population selection, draft input collection, tree conversion, criteria adaptation, problem re-evaluation, results distribution and refinement, tree finalisation, and analysis. CONCLUSION: This manuscript provides information on the main steps for successful collection of decision trees and summarizes important aspects at each point of the analysis.

Objective consensus from decision trees.

BACKGROUND: Consensus-based approaches provide an alternative to evidence-based decision making, especially in situations where high-level evidence is limited. Our aim was to demonstrate a novel source of information, objective consensus based on recommendations in decision tree format from multiple sources. METHODS: Based on nine sample recommendations in decision tree format a representative analysis was performed. The most common (mode) recommendations for each eventuality (each permutation of parameters) were determined. The same procedure was applied to real clinical recommendations for primary radiotherapy for prostate cancer. Data was collected from 16 radiation oncology centres, converted into decision tree format and analyzed in order to determine the objective consensus. RESULTS: Based on information from multiple sources in decision tree format, treatment recommendations can be assessed for every parameter combination. An objective consensus can be determined by means of mode recommendations without compromise or confrontation among the parties. In the clinical example involving prostate cancer therapy, three parameters were used with two cut-off values each (Gleason score, PSA, T-stage) resulting in a total of 27 possible combinations per decision tree. Despite significant variations among the recommendations, a mode recommendation could be found for specific combinations of parameters. CONCLUSION: Recommendations represented as decision trees can serve as a basis for objective consensus among multiple parties.

Assessment and monitoring tumor vascularity with contrast-enhanced ultrasound maximum intensity persistence imaging.

OBJECTIVES: Contrast-enhanced ultrasound imaging is increasingly being used in the clinic for assessment of tissue vascularity. The purpose of our study was to evaluate the effect of different contrast administration parameters on the in vivo ultrasound imaging signal in tumor-bearing mice using a maximum intensity persistence (MIP) algorithm and to evaluate the reliability of in vivo MIP imaging in assessing tumor vascularity. The potential of in vivo MIP imaging for monitoring tumor vascularity during antiangiogenic cancer treatment was further evaluated. MATERIALS AND METHODS: In intraindividual experiments, varying contrast microbubble concentrations (5 × 105, 5 × 106, 5 × 107, 5 × 108 microbubbles in 100 µL saline) and contrast injection rates (0.6, 1.2, and 2.4 mL/min) in subcutaneous tumor-bearing mice were applied and their effects on in vivo contrast-enhanced ultrasound MIP imaging plateau values were obtained using a dedicated small animal ultrasound imaging system (40 MHz). Reliability of MIP ultrasound imaging was tested following 2 injections of the same microbubble concentration (5 × 107 microbubbles at 1.2 mL/min) in the same tumors. In mice with subcutaneous human colon cancer xenografts, longitudinal contrast-enhanced ultrasound MIP imaging plateau values (baseline and at 48 hours) were compared between mice with and without antiangiogenic treatment (antivascular endothelial growth factor antibody). Ex vivo CD31 immunostaining of tumor tissue was used to correlate in vivo MIP imaging plateau values with microvessel density analysis. RESULTS: In vivo MIP imaging plateau values correlated significantly (P = 0.001) with contrast microbubble doses. At 3 different injection rates of 0.6, 1.2, and 2.4 mL/min, MIP imaging plateau values did not change significantly (P = 0.61). Following 2 injections with the same microbubble dose and injection rate, MIP imaging plateau values were obtained with high reliability with an intraclass correlation coefficient of 0.82 (95% confidence interval: 0.64, 0.94). In addition, in vivo MIP imaging plateau values significantly correlated (P = 0.01; R² = 0.77) with ex vivo microvessel density analysis. Tumor volumes in treated and nontreated mice did not change significantly (P = 0.22) within 48 hours. In contrast, the change of in vivo MIP imaging plateau values from baseline to 48 hours was significantly different (P = 0.01) in treated versus nontreated mice. CONCLUSIONS: Contrast-enhanced ultrasound MIP imaging allows reliable assessment of tumor vascularity and monitoring of antiangiogenic cancer therapy in vivo, provided that a constant microbubble dose is administered.