MétaCan
Menu
Retour à la cohorte
Enregistrement W7134818711 · doi:10.3310/pplhg1141

Digital intervention to support cancer survivors: the CLASP research programme

2025· article· en· W7134818711 sur OpenAlexaff
P. S. Little, Katherine Bradbury, B. Stuart, Jane Barnett, Adele Krusche, Mary Steele, Elena Heber, Steph Easton, Kirsten A. Smith, Joanna Slodowska-Barabasz, Liz Payne, Teresa Corbett, Sebastien Pollet, Jazzine Smith, Judith Joseph, Megan Lawrence, Dankmar Böhning, Tara Cheetham-Blake, Diana Eccles, Claire Foster, Adam WA Geraghty, Geraldine Leydon, André Müller, R. Neal, Richard Osborne, Shanaya Rathod, Chloe Grimmett, Geoffrey Sharman, Roger Bacon, Lesley Turner, Richard Stephens, Tamsin Burford, Laura Wilde, Megan Liddiard, Kirsty Rogers, James Raftery, Shihua Zhu, Karmpal Singh, Frances Webley, Gareth Griffiths, Trudie Chalder, Clare Wilkinson, Eila Watson, Lucy Yardley

Notice bibliographique

RevueProgramme Grants for Applied Research · 2025
Typearticle
Langueen
DomaineMedicine
ThématiqueCancer survivorship and care
Établissements canadiensUniversity of Calgary
Organismes subventionnairesProgramme Grants for Applied ResearchNational Institute for Health Research Southampton Biomedical Research CentreNational Institute for Health and Care Research
Mots-clésIntervention (counseling)Psychological interventionQuality of life (healthcare)Qualitative researchDigital healthBespokeDistressCancerRandomized controlled trial

Résumé

récupéré en direct d'OpenAlex

Background There are increasing numbers of cancer survivors who have finished their primary treatment, but whose quality of life remains consistently poor over years. There is limited evidence for pragmatic, brief interventions to support cancer survivors in primary care, where most patients are managed. Objective To develop, trial and assess the effectiveness and cost-effectiveness of a digital intervention to support cancer survivors (named ‘Renewed’) designed to require minimal health service resources. Design Qualitative development of the intervention, then open randomised controlled trial, with a process analysis and health economic analysis. Setting United Kingdom primary care Interventions: Development of the intervention We systematically reviewed the relevant qualitative and quantitative literature to inform initial intervention planning, intervention content and design features of a digital intervention. This was followed by iterative development and optimisation of intervention content and the human support component – in qualitative studies of the views of cancer survivor, and of National Health Service, volunteer and charity workers. Main trial: Participants People who had finished primary treatment for colorectal, breast or prostate cancer with lower quality of life (European Organization for Research and Treatment of Cancer QLQ-C30 score < 85) within the last 10 years. Participants were randomised to one of three groups: (1) ‘generic’ advice: detailed digital National Health Service support for healthier living (‘Living Well’), (2) a bespoke digital intervention (‘Renewed’) addressing symptom management, physical activity, diet, weight, distress and/or fear of recurrence, or (3) ‘Renewed’ plus support (additional brief support by e-mail, telephone, or face to face) Main outcome measures Primary outcome: European Organization for Research and Treatment of Cancer QLQ-C30 (overall score). Secondary outcomes: subscales of European Organization for Research and Treatment of Cancer QLQ-C30 (global self-rated health; functional subscales; symptom subscales), EuroQol-5 Dimensions, five-level version, psychological measures and costs. Results At the primary time point of 6 months, there were clinically important improvements in European Organization for Research and Treatment of Cancer QLQ-C30 score contrary to the expected trajectory of quality of life in this population, but with no evidence of differences between groups. By 12 months, the Renewed plus support group had continued to improve and was better than generic advice (1.42, 95% confidence intervals 0.33 to 2.51), with the largest differences in the prostate cancer subgroup. 13 of the 14 subscales also improved compared to generic advice, statistically significant for self-rated global health (Renewed: 3.06, 1.39 to 4.74; Renewed plus support: 2.78, 1.08 to 4.48), dyspnoea, constipation and enablement. For Renewed plus support, there were also statistically significant differences for physical, cognitive and emotional functioning and fatigue. Renewed and Renewed plus support were dominant given improved effectiveness combined with and lower mean primary care National Health Service costs per patient (respectively −£141, −153 to −128; −£77, −90 to −65). Limitations Of those sent invitation letters, 14% (7883/59,295) were assessed for eligibility and 35% (2732/7883) of those assessed were eligible and agreed to participate – which is normal with the ‘cold calling’ method of invitation. The digital intervention would not suit people who find technology or the internet difficult to access, but only 25% (2649/10,697) of those who gave reasons for declining did so due to lack of internet access. The extensive generic advice available to participants in the National Health Service limited the ability to assess the specific benefits of Renewed in the short term, but nevertheless longer-term benefit and lower National Health Service costs are likely to be achieved with the bespoke intervention. Conclusions Cancer survivors with lower quality of life given detailed generic online support improve significantly. Providing robustly developed, low-cost, bespoke digital support can provide further modest long-term improvements in enablement, symptom management and self-rated global health, with substantially lower National Health Service costs. Future work The cost-effectiveness and benefits for symptom management on self-rated health suggest a more widespread implementation study should be undertaken. Trial registration This trial is registered as Current Controlled Trials ISRCTN 96374224. Funding This award was funded by the National Institute for Health and Care Research (NIHR) Programme Grants for Applied Research programme (NIHR award ref: RP-PG-0514-20001) and is published in full in Programme Grants for Applied Research ; Vol. 14, No. 4. See the NIHR Funding and Awards website for further award information.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,009
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,965
Score d'incertitude au seuil0,994

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0090,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,004
Études des sciences et des technologies0,0010,001
Communication savante0,0010,000
Science ouverte0,0010,001
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,183
Tête enseignante GPT0,474
Écart entre enseignants0,292 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2025
Routes d'admission1
Résumé présentoui

Explorer davantage

Même revueProgramme Grants for Applied ResearchMême sujetCancer survivorship and careTravaux en français237 207