Dynamic contrast-enhanced CT compared with positron emission tomography CT to characterise solitary pulmonary nodules : the SPUtNIk diagnostic accuracy study and economic modelling

Background Current pathways recommend positron emission tomography–computerised tomography for the characterisation of solitary pulmonary nodules. Dynamic contrast-enhanced computerised tomography may be a more cost-effective approach. Objectives To determine the diagnostic performances of dynamic contrast-enhanced computerised tomography and positron emission tomography–computerised tomography in the NHS for solitary pulmonary nodules. Systematic reviews and a health economic evaluation contributed to the decision-analytic modelling to assess the likely costs and health outcomes resulting from incorporation of dynamic contrast-enhanced computerised tomography into management strategies. Design Multicentre comparative accuracy trial. Setting Secondary or tertiary outpatient settings at 16 hospitals in the UK. Participants Participants with solitary pulmonary nodules of ≥ 8 mm and of ≤ 30 mm in size with no malignancy in the previous 2 years were included. Interventions Baseline positron emission tomography–computerised tomography and dynamic contrast-enhanced computer tomography with 2 years’ follow-up. Main outcome measures Primary outcome measures were sensitivity, specificity and diagnostic accuracy for positron emission tomography–computerised tomography and dynamic contrast-enhanced computerised tomography. Incremental cost-effectiveness ratios compared management strategies that used dynamic contrast-enhanced computerised tomography with management strategies that did not use dynamic contrast-enhanced computerised tomography. Results A total of 380 patients were recruited (median age 69 years). Of 312 patients with matched dynamic contrast-enhanced computer tomography and positron emission tomography–computerised tomography examinations, 191 (61%) were cancer patients. The sensitivity, specificity and diagnostic accuracy for positron emission tomography–computerised tomography and dynamic contrast-enhanced computer tomography were 72.8% (95% confidence interval 66.1% to 78.6%), 81.8% (95% confidence interval 74.0% to 87.7%), 76.3% (95% confidence interval 71.3% to 80.7%) and 95.3% (95% confidence interval 91.3% to 97.5%), 29.8% (95% confidence interval 22.3% to 38.4%) and 69.9% (95% confidence interval 64.6% to 74.7%), respectively. Exploratory modelling showed that maximum standardised uptake values had the best diagnostic accuracy, with an area under the curve of 0.87, which increased to 0.90 if combined with dynamic contrast-enhanced computerised tomography peak enhancement. The economic analysis showed that, over 24 months, dynamic contrast-enhanced computerised tomography was less costly (£3305, 95% confidence interval £2952 to £3746) than positron emission tomography–computerised tomography (£4013, 95% confidence interval £3673 to £4498) or a strategy combining the two tests (£4058, 95% confidence interval £3702 to £4547). Positron emission tomography–computerised tomography led to more patients with malignant nodules being correctly managed, 0.44 on average (95% confidence interval 0.39 to 0.49), compared with 0.40 (95% confidence interval 0.35 to 0.45); using both tests further increased this (0.47, 95% confidence interval 0.42 to 0.51). Limitations The high prevalence of malignancy in nodules observed in this trial, compared with that observed in nodules identified within screening programmes, limits the generalisation of the current results to nodules identified by screening. Conclusions Findings from this research indicate that positron emission tomography–computerised tomography is more accurate than dynamic contrast-enhanced computerised tomography for the characterisation of solitary pulmonary nodules. A combination of maximum standardised uptake value and peak enhancement had the highest accuracy with a small increase in costs. Findings from this research also indicate that a combined positron emission tomography–dynamic contrast-enhanced computerised tomography approach with a slightly higher willingness to pay to avoid missing small cancers or to avoid a ‘watch and wait’ policy may be an approach to consider. Future work Integration of the dynamic contrast-enhanced component into the positron emission tomography–computerised tomography examination and the feasibility of dynamic contrast-enhanced computerised tomography at lung screening for the characterisation of solitary pulmonary nodules should be explored, together with a lower radiation dose protocol. Study registration This study is registered as PROSPERO CRD42018112215 and CRD42019124299, and the trial is registered as ISRCTN30784948 and ClinicalTrials.gov NCT02013063

Comparative Accuracy and Cost-Effectiveness of Dynamic Contrast Enhanced Computed Tomography and Positron Emission Tomography in the Characterisation of Solitary Pulmonary Nodules

Abstract Introduction: Dynamic contrast-enhanced computed tomography (DCE-CT) and Positron Emission Tomography/Computed Tomography (PET/CT) have a high reported accuracy for the diagnosis of malignancy in solitary pulmonary nodules. The aim of this study was to compare the accuracy and cost-effectiveness of these. Methods: In this prospective multicentre trial, 380 participants with a solitary pulmonary nodule (8-30mm) and no recent history of malignancy underwent DCE-CT and PET/CT. All patients underwent either biopsy with histological diagnosis or completed CT follow-up. Primary outcome measures were sensitivity, specificity, and overall diagnostic accuracy for PET/CT and DCE-CT. Costs and cost-effectiveness were estimated from a healthcare provider perspective using a decision-model. Results: 312 participants (47% female, 68.1±9.0 years) completed the study, with 61% rate of malignancy at 2 years. The sensitivity, specificity, positive predictive value and negative predictive values for DCE-CT were 95.3% [95% CI 91.3;97.5], 29.8% [95% CI 22.3;38.4], 68.2% [95% CI 62.4%;73.5%] and 80.0% [95% CI 66.2;89.1] respectively, and for PET/CT were 79.1% [95% CI 72.7;84.2], 81.8% [95% CI 74.0;87.7], 87.3%[95% CI 81.5;91.5) and 71·2% [95% CI 63.2;78.1]. The area under the receiver operator characteristic curve (AUROC) for DCE-CT and PET/CT was 0.62 [95%CI 0.58;0.67] and 0.80 [95%CI 0.76;0.85] respectively (p<0.001). Combined results significantly increased diagnostic accuracy over PET/CT alone (AUROC=0.90 [95%CI 0.86;0.93], p<0.001). DCE-CT was preferred when the willingness to pay per incremental cost per correctly treated malignancy was below £9000. Above £15500 a combined approach was preferred. Conclusions: PET/CT has a superior diagnostic accuracy to DCE-CT for the diagnosis of solitary pulmonary nodules. Combining both techniques improves the diagnostic accuracy over either test alone and could be cost-effective. (Clinical trials.gov - NCT02013063)

Supporting good quality, community-based end-of-life care for people living with dementia: the SEED research programme including feasibility RCT

Background In the UK, most people with dementia die in the community and they often receive poorer end-of-life care than people with cancer. Objective The overall aim of this programme was to support professionals to deliver good-quality, community-based care towards, and at, the end of life for people living with dementia and their families. Design The Supporting Excellence in End-of-life care in Dementia (SEED) programme comprised six interlinked workstreams. Workstream 1 examined existing guidance and outcome measures using systematic reviews, identified good practice through a national e-survey and explored outcomes of end-of-life care valued by people with dementia and family carers (n = 57) using a Q-sort study. Workstream 2 explored good-quality end-of-life care in dementia from the perspectives of a range of stakeholders using qualitative methods (119 interviews, 12 focus groups and 256 observation hours). Using data from workstreams 1 and 2, workstream 3 used co-design methods with key stakeholders to develop the SEED intervention. Worksteam 4 was a pilot study of the SEED intervention with an embedded process evaluation. Using a cluster design, we assessed the feasibility and acceptability of recruitment and retention, outcome measures and our intervention. Four general practices were recruited in North East England: two were allocated to the intervention and two provided usual care. Patient recruitment was via general practitioner dementia registers. Outcome data were collected at baseline, 4, 8 and 12 months. Workstream 5 involved economic modelling studies that assessed the potential value of the SEED intervention using a contingent valuation survey of the general public (n = 1002). These data informed an economic decision model to explore how the SEED intervention might influence care. Results of the model were presented in terms of the costs and consequences (e.g. hospitalisations) and, using the contingent valuation data, a cost–benefit analysis. Workstream 6 examined commissioning of end-of-life care in dementia through a narrative review of policy and practice literature, combined with indepth interviews with a national sample of service commissioners (n = 20). Setting The workstream 1 survey and workstream 2 included services throughout England. The workstream 1 Q-sort study and workstream 4 pilot trial took place in North East England. For workstream 4, four general practices were recruited; two received the intervention and two provided usual care. Results Currently, dementia care and end-of-life care are commissioned separately, with commissioners receiving little formal guidance and training. Examples of good practice rely on non-recurrent funding and leadership from an interested clinician. Seven key components are required for good end-of-life care in dementia: timely planning discussions, recognising end of life and providing supportive care, co-ordinating care, effective working with primary care, managing hospitalisation, continuing care after death, and valuing staff and ongoing learning. Using co-design methods and the theory of change, the seven components were operationalised as a primary care-based, dementia nurse specialist intervention, with a care resource kit to help the dementia nurse specialist improve the knowledge of family and professional carers. The SEED intervention proved feasible and acceptable to all stakeholders, and being located in the general practice was considered beneficial. None of the outcome measures was suitable as the primary outcome for a future trial. The contingent valuation showed that the SEED intervention was valued, with a wider package of care valued more than selected features in isolation. The SEED intervention is unlikely to reduce costs, but this may be offset by the value placed on the SEED intervention by the general public. Limitations The biggest challenge to the successful delivery and completion of this research programme was translating the ‘theoretical’ complex intervention into practice in an ever-changing policy and service landscape at national and local levels. A major limitation for a future trial is the lack of a valid and relevant primary outcome measure to evaluate the effectiveness of a complex intervention that influences outcomes for both individuals and systems. Conclusions Although the dementia nurse specialist intervention was acceptable, feasible and integrated well with existing care, it is unlikely to reduce costs of care; however, it was highly valued by all stakeholders (professionals, people with dementia and their families) and has the potential to influence outcomes at both an individual and a systems level. Future work There is no plan to progress to a full randomised controlled trial of the SEED intervention in its current form. In view of new National Institute for Health and Care Excellence dementia guidance, which now recommends a care co-ordinator for all people with dementia, the feasibility of providing the SEED intervention throughout the illness trajectory should be explored. Appropriate outcome measures to evaluate the effectiveness of such a complex intervention are needed urgently. Trial registration Current Controlled Trials ISRCTN21390601. Funding This project was funded by the National Institute for Health Research (NIHR) Programme Grants for Applied Research programme and will be published in full in Programme Grants for Applied Research, Vol. 8, No. 8. See the NIHR Journals Library website for further project information