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Record W4415200663 · doi:10.1016/j.lanprc.2025.100031

Clinical effectiveness and cost-effectiveness of the Needs Assessment Tool-Cancer in primary care (CANAssess2): a pragmatic, cluster-randomised, controlled trial

2025· article· en· W4415200663 on OpenAlexaboutno aff
Miriam J. Johnson, Alexandra Wright‐Hughes, Emma McNaught, Alice Hankin, Joseph Clark, Terry McCormack, Jon M Dickson, Robbie Foy, Scott Wilkes, David Meads, John O’Dwyer, Sonya Begum, Flavia Swan, Florence Day, Amanda Farrin, Alice Hankin, John Blenkinsopp, F Conneh, Katie Whitehead, Mishell Cunningham, Samia Mujahid, Carol Singleton, Annie S. K. Jones, Bethan Copsey, Laura Marsden, Suzanne Hartley, Petra Bijsterveld, Jamie Metherell, Lucy Sheehan, Julia Burrows, Lucia Crowther

Bibliographic record

VenueThe Lancet Primary Care · 2025
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsnot available
FundersUniversity of LeedsYorkshire Cancer ResearchUniversity of Hull
KeywordsTriageRandomized controlled trialNeeds assessmentIntervention (counseling)Palliative carePrimary careClinical trialClinical effectivenessMEDLINE

Abstract

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Background The Needs Assessment Tool-Cancer (NAT-C) is a consultation guide to identify and triage patients' and carers' cancer-related unmet needs, but its effectiveness in primary care is unknown. We aimed to evaluate the clinical effectiveness and cost-effectiveness of the NAT-C in reducing patient unmet needs and reducing carer burden in primary care. Methods The Cancer Patients' Needs Assessment in Primary Care (CANAssess2) trial was a pragmatic, cluster-randomised, controlled trial of the NAT-C versus usual care in patients aged 18 years and older with active cancer (ie, receiving anticancer treatment with curative or palliative intent; managed with a watch and wait approach; or with recurrent or metastatic disease), conducted across northeast England and Yorkshire. Eligible general practices (clusters) were willing to be trained and deliver the NAT-C for recruited patients if so allocated, were willing to commit to trial procedures, and gave written informed practice-level consent. Practices were randomly assigned (1:1) to deliver the NAT-C intervention or usual care alone by use of minimisation incorporating a random element to ensure treatment groups were well balanced for patient list size, locality, and training centre status. Patients and carers (family or friend nominated by patient) consented to complete follow-up questionnaires at baseline, 1 month, 3 months, and 6 months and attend a NAT-C appointment if registered with an intervention practice. The primary outcome was at least one moderate-to-severe unmet need at 3 months (according to the Supportive Care Needs Survey-Short Form 34 [SCNS-SF34]). Secondary outcomes included at least one moderate-to-severe unmet need at 1 month and 6 months, level of unmet needs (SCNS-SF34 score), symptoms (Revised Edmonton Symptom Assessment System [ESAS-r]), mood and quality of life (EQ-5D-5L and European Organisation for Research and Treatment of Cancer Quality of Life-C15-Palliative questionnaire [EORTC QLQ-C15-PAL]), performance status (Australia-modified Karnofsky Performance Score), carers' ability to care, and carer wellbeing, at all timepoints. Primary effectiveness analyses were done in all participants with at least one post-baseline measurement (at either 1, 3, or 6 months) according to modified intention-to-treat principles. The original sample size target of 1080 participants across 54 practices was reduced in a protocol amendment to 950 across at least 38 practices due to recruitment challenges and improved retention. The trial is registered with ISRCTN, ISRCTN15497400. Findings Between Oct 21, 2020, and April 12, 2023, of 65 general practices screened, 41 (63%) were randomly assigned: 21 (51%) to NAT-C and 20 (49%) to usual care. Between Dec 1, 2020, and Aug 30, 2023, 788 participants (mean age 66·9 years, SD 10·9; 404 [51%] female and 384 [49%] male) were enrolled: 376 (48%) in the NAT-C group and 412 (52%) in the usual care group. 427 (54%) of 788 participants identified a potentially eligible carer, and a carer was recruited alongside 249 (32%) participants. Follow-up was completed on Jan 19, 2024. For the 3-month primary outcome, 149 (46%) of 321 participants in the NAT-C group and 173 (48%) of 364 participants in the usual care group reported at least one moderate-to-severe unmet need (odds ratio [OR] 0·98 [95% CI 0·63 to 1·53]; p=0·94; intracluster correlation coefficient 0·067). There was no evidence of benefit for any clinical effectiveness outcomes at 1 month or 3 months. However, at 6 months we found evidence that the NAT-C was superior to usual care at reducing the level of unmet need (mean difference –3·57, 95% CI –6·57 to –0·58; p=0·020; predominantly psychological and physical needs). There was also evidence of benefit in the NAT-C group on 6-month symptoms (ESAS-r mean difference –2·98, 95% CI –5·35 to –0·61; p=0·014) and mood and quality of life (mean difference in EORTC QLQ-C15-PAL domains of overall quality of life 3·97, 1·03 to 6·91, p=0·0082; pain –3·81, –7·26 to –0·35, p=0·031; appetite loss –4·02, –7·31 to –0·72, p=0·017; emotional functioning 3·54, 0·21 to 6·87, p=0·037). There was weak evidence of benefit for the 6-month outcome of at least one moderate-to-severe unmet need (OR 0·66, 95% CI 0·42 to 1·04; p=0·075), but no evidence of benefit on performance status (mean difference –0·02, –2·22 to 2·17; p=0·98), carers' ability to care (–0·06, –4·21 to 4·09; p=0·98), or wellbeing (0·00, –1·90 to 1·90; p=0·99). Interpretation We found no evidence of benefit of the NAT-C versus usual care at the 3-month primary endpoint timepoint. However, our data suggest potential benefits for patients at 6 months, although future studies with longer follow-up are needed to clarify these findings. Funding Yorkshire Cancer Research.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.015
metaresearch head score (Gemma)0.026
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.077

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.026
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0070.006
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0020.003
Open science0.0020.002
Research integrity0.0050.004
Insufficient payload (model declined to judge)0.0110.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.119
GPT teacher head0.442
Teacher spread0.323 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations1
Published2025
Admission routes1
Has abstractyes

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