Pre-treatment radiomic features predict individual lymph node failure for head and neck cancer patients

Background and purpose: To develop and validate a pre-treatment radiomics-based prediction model to identify pathological lymph nodes (pLNs) at risk of failures after definitive radiotherapy in head and neck squamous cell carcinoma patients. Materials and methods: Training and validation cohorts consisted of 165 patients with 558 pLNs and 112 patients with 467 pLNs, respectively. All patients were primarily treated with definitive radiotherapy, with or without systemic treatment. The endpoint was the cumulative incidence of nodal failure. For each pLN, 82 pre-treatment CT radiomic features and 7 clinical features were included in the Cox proportional-hazard analysis. Results: There were 68 and 23 nodal failures in the training and validation cohorts, respectively. Multivariable analysis revealed three clinical features (T-stage, gender and WHO Performance-status) and two radiomic features (Least-axis-length representing nodal size and gray level co-occurrence matrix based - Correlation representing nodal heterogeneity) as independent prognostic factors. The model showed good discrimination with a c-index of 0.80 (0.69–0.91) in the validation cohort, significantly better than models based on clinical features (p < 0.001) or radiomics (p = 0.003) alone. High- and low-risk groups were defined by using thresholds of estimated nodal failure risks at 2-year of 60% and 10%, resulting in positive and negative predictive values of 94.4% and 98.7%, respectively. Conclusion: A pre-treatment prediction model was developed and validated, integrating the quantitative radiomic features of individual lymph nodes with generally used clinical features. Using this prediction model, lymph nodes with a high failure risk can be identified prior to treatment, which might be used to select patients for intensified treatment strategies targeted on individual lymph nodes

Acute symptoms during the course of head and neck radiotherapy or chemoradiation are strong predictors of late dysphagia

AbstractPurposeTo determine if acute symptoms during definitive radiotherapy (RT) or chemoradiation (CHRT) are prognostic factors for late dysphagia in head and neck cancer (HNC).Material and methodsThis prospective cohort study consisted of 260 HNC patients who received definitive RT or CHRT. The primary endpoint was grade 2–4 swallowing dysfunction at 6months after completing RT (SWALM6). During treatment, acute symptoms, including oral mucositis, xerostomia and dysphagia, were scored, and the scores were accumulated weekly and entered into an existing reference model for SWALM6 that consisted of dose–volume variables only.ResultsBoth acute xerostomia and dysphagia were strong prognostic factors for SWALM6. When acute scores were added as variables to the reference model, model performance increased as the course of treatment progressed: the AUC rose from 0.78 at the baseline to 0.85 in week 6. New models built for weeks 3–6 were significantly better able to identify patients with and without late dysphagia.ConclusionAcute xerostomia and dysphagia during the course of RT are strong prognostic factors for late dysphagia. Including accumulated acute symptom scores on a weekly basis in prediction models for late dysphagia significantly improves the identification of high-risk and low-risk patients at an early stage during treatment and might facilitate individualized treatment adaptation

The Use of Decision–Analytic Models in Atopic Eczema: A Systematic Review and Critical Appraisal

Objective: The objective of this systematic review was to identify and assess the quality of published economic decision–analytic models within atopic eczema against best practice guidelines, with the intention of informing future decision–analytic models within this condition. Methods: A systematic search of the following online databases was performed: MEDLINE, EMBASE, Cumulative Index to Nursing and Allied Health Literature (CINAHL), Cochrane Central Register of Controlled Trials, Database of Abstracts of Reviews of Effects, Cochrane Database of Systematic Reviews, NHS Economic Evaluation Database, EconLit, Scopus, Health Technology Assessment, Cost-Effectiveness Analysis Registry and Web of Science. Papers were eligible for inclusion if they described a decision–analytic model evaluating both the costs and benefits associated with an intervention or prevention for atopic eczema. Data were extracted using a standardised form by two independent reviewers, whilst quality was assessed using the model-specific Philips criteria. Results: Twenty-four models were identified, evaluating either preventions (n = 12) or interventions (n = 12): 14 reported using a Markov modelling approach, four utilised decision trees and one a discrete event simulation, whilst five did not specify the approach. The majority, 22 studies, reported that the intervention was dominant or cost effective, given the assumptions and analytical perspective taken. Notably, the models tended to be short-term (16 used a time horizon of ≤1 year), often providing little justification for the limited time horizon chosen. The methodological and reporting quality of the studies was generally weak, with only seven studies fulfilling more than 50% of their applicable Philips criteria. Conclusions: This is the first systematic review of decision models in eczema. Whilst the majority of models reported favourable outcomes in terms of the cost effectiveness of the new intervention, the usefulness of these findings for decision-making is questionable. In particular, there is considerable scope for increasing the range of interventions evaluated, for improving modelling structures and reporting quality

Cost effectiveness of support for people starting a new medication for a long term condition through community pharmacies: an economic evaluation of the New Medicine Service (NMS) compared with normal practice

Background: The English community pharmacy New Medicine Service (NMS) significantly increases patient adherence to medicines, compared with normal practice. We examined the cost-effectiveness of NMS compared with normal practice by combining adherence improvement and intervention costs with the effect of increased adherence on patient outcomes and healthcare costs. Methods: We developed Markov models for diseases targeted by the NMS (hypertension, type 2 diabetes, chronic obstructive pulmonary disease, asthma and antiplatelet regimens) to assess the impact of patients’ non-adherence. Clinical event probability, treatment pathway, resource-use and costs were extracted from literature and costing tariffs. Incremental costs and outcomes associated with each disease were incorporated additively into a composite probabilistic model and combined with adherence rates and intervention costs from the trial. Costs per extra quality-adjusted-life-year(QALY) were calculated from the perspective of NHS England, using a lifetime horizon. Results: NMS generated a mean of 0.05 (95%CI: 0.00, 0.13) more QALYs per patient, at a mean reduced cost of -£144 (95%CI: -769, 73). The NMS dominates normal practice with probability of 0.78 (ICER: - £3166 per QALY). NMS has a 96.7% probability of cost-effectiveness compared with normal practice at a willingness-to-pay of £20000 per QALY. Sensitivity analysis demonstrated that targeting each disease with NMS has a probability over 0.90 of cost-effectiveness compared with normal practice at a willingness-to-pay of £20000 per QALY. Conclusions: Our study suggests that the New Medicine Service increased patient medicine adherence compared with normal practice, which translated into increased health gain at reduced overall cost

Coverage, statistical power, absolute value of the bias and mean absolute deviation (MAD) of health-economic outcomes for three of the eight scenarios.

<p>Coverage, statistical power, absolute value of the bias and mean absolute deviation (MAD) of health-economic outcomes for three of the eight scenarios.</p

Design of the chronic disease model.

<p>Design of the chronic disease model.</p

Reference outcomes for Usual Care and New Intervention, per patient after 12 cycles—Mean (Standard deviation)^a.

<p>Reference outcomes for Usual Care and New Intervention, per patient after 12 cycles—Mean (Standard deviation)<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0171292#t002fn001" target="_blank">^a</a>.</p