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Lookup NU author(s): Dr Richard Thomson, Professor Barbara HanrattyORCiD
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
© 2024 Roman et al. Background: Arising in blood and lymph-forming tissues, haematological malignancies (leukaemias, lymphomas and myelomas) are the fifth most common group of cancers. Around 60% are currently incurable and follow a chronic, remitting–relapsing pathway often initially managed by ‘watch & wait’. This involves hospital-based monitoring, followed by treatment if the cancer progresses (which not all do) and then further observation, in a process that may continually repeat. New treatments are constantly emerging, survival is improving and prevalence is rising, but population-based data documenting entire care pathway are sparse. Hence, empirically-based incidence and prevalence estimates about various treatment states (watch and wait, first-line treatment, observation, second-line treatment, etc.) and patterns of healthcare activity are lacking. Likewise, despite complex trajectories, anxiety-provoking watch and wait, and therapies that impede quality of life and incur marked healthcare costs, evidence about patient preferences for information sharing and treatment decisions is scant. Objectives: Primary – to generate high-quality, evidence-based information about the care pathways of the general population of patients with chronic haematological malignancies. Secondary – to produce information resources suitable for testing in routine National Health Service practice. Design: Population-based cohort of ≈ 8000 patients with chronic haematological malignancies, incorporating five nested work packages, each with its own individual design: (1) exploration of patient experiences: information and treatment decisions; (2) population-based analyses; (3) health economics; (4) development of information resources to support decision-making; and (5) patient well-being and decision-making survey. Setting: This programme is predicated on the infrastructure of the United Kingdom’s Haematological Malignancy Research Network (www.hmrn.org); which provides ‘real-world’, robust, generalisable data to inform research and clinical practice, nationally and internationally. Set in Yorkshire and Humberside, the Haematological Malignancy Research Network’s catchment population of ≈ 4 million has a comparable sex, age, urban/rural, and area-based deprivation (Index of Multiple Deprivation, income domain) distribution to the United Kingdom as a whole; and in terms of ethnic diversity the region is centrally ranked, with around 80% of residents identifying as White British, 9% as Asian and 2% as black. Within the Haematological Malignancy Research Network, clinical practice adheres to national guidelines, and all patients with blood cancers are centrally diagnosed (≈ 2500 each year), tracked through their treatment pathways and linked to national databases (deaths, cancer registrations and Hospital Episode Statistics). Linked to the same national databases, the Haematological Malignancy Research Network also contains an age-and sex-matched general-population cohort. Participants: Patients aged ≥ 18 years, resident in the study region, and diagnosed with chronic lymphocytic leukaemia, follicular lymphoma or myeloma. Methods: Core Haematological Malignancy Research Network data were used to compare the hospital activity of patients with chronic lymphocytic leukaemia, follicular lymphoma and myeloma with that of the general population. Following additional linkages to genetic and clinical data, follicular lymphoma prognostic factors were examined. Two self-administered questionnaires addressing (1) quality of life and well-being and (2) decision-making were iteratively developed, piloted and deployed. Linkage to quality of life, clinical information and Hospital Episode Statistics enabled economic (myeloma) model development. In-depth interviews were conducted with 35 patients (10 alongside relatives). Results: Trajectories of ≈ 8000 patients were mapped, and patient-pathway visualisations summarising individual and aggregate information were developed. As expected, patients with chronic blood cancers experienced higher levels of hospital activity than their general population counterparts, the largest effects being for myeloma. Following survey deployment, 3153 patients were recruited across 14 hospitals, 1282 with chronic lymphocytic leukaemia, follicular lymphoma or myeloma. Over half of the questionnaires were completed by patients on watch and wait; the remainder were completed during treatment or post-chemotherapy monitoring. Information gathered, coupled with in-depth interviews, demonstrated patients’ marked anxiety and fluctuating preferences for information sharing and decision-making, contingent on complex, inter-related factors. In turn, prognostic and microsimulation economic models were used to predict individual-level trajectories across multiple treatment lines, examining associated overall survival, costs and quality-adjusted life-years. Limitations: Survey mapping to individual care pathways could not be completed because the COVID-19 pandemic delayed clinical data collection. Patients who attended clinics and participated in the survey were more likely than non-attenders to have had first-line chemotherapy, be slightly younger and live in more affluent areas. Conclusions: This programme collated high-quality, population-based evidence. Previously lacking, this, coupled with new findings on preferences for information sharing and treatment decisions, provides the foundation for future research. Future work: The translation of information accrued into resources suitable for testing in routine NHS practice is key. In this regard, COVID-19 has changed the communication landscape. The visualisations developed by this programme require further refinement/testing using participatory co-design with stakeholder groups. Underpinned by a suitable protocol applied within a single multidisciplinary team setting, prior to further evaluation within/outside the region, such outputs require testing in a cluster-randomised trial.
Author(s): Roman E, Howell D, Smith A, Crouch S, Bagguley T, Painter D, Sheridan R, McCaughan D, Blase J, Curson W, Wang H-I, Manca A, Bennett A, Gc VS, Miller C, Atkin K, Thomson R, Hanratty B, Burton C, Ashcroft J, Patmore R
Publication type: Article
Publication status: Published
Journal: Programme Grants for Applied Research
Year: 2024
Volume: 12
Issue: 5
Print publication date: 31/07/2024
Acceptance date: 30/08/2023
Date deposited: 16/08/2024
ISSN (print): 2050-4322
ISSN (electronic): 2050-4330
Publisher: NIHR Journals Library
URL: https://doi.org/10.3310/TKNQ7004
DOI: 10.3310/TKNQ7004
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