Personalising Adjuvant Therapy in Common Solid Tumours Using Data from the Add-Aspirin Trial
Bibliographic record
Abstract
BACKGROUND: \nPersonalisation of medicine involves the categorisation of patients into biologically stratified groups enabling more tailored treatment for the individual. Using data from the Add-Aspirin trial, I aimed to improve trial outcomes and methodology by evaluating three different aspects of personalised approaches to cancer care. Through review of geriatric assessments (GA) embedded within the trial, I evaluated older participants in the trial as an example of patient-related personalisation. Secondly, through a collaboration with pharmacologists in Rome I explored differences in levels of platelet activation between participants with cancer and the effect of aspirin, using the in vivo marker urinary 11-dehydro-thromboxane B2 (TXB2) excretion – treatment-related personalisation. Finally I assessed the feasibility of a molecularly stratified adjuvant trial of immune checkpoint inhibition in colorectal cancers, as an example of tumour-related personalisation, by reviewing the extent and accuracy of mismatch repair (MMR) reporting across all UK sites. \n \nRESULTS: \nEvaluation of GA results in 1905 participants over 65 years, using available data from October 2015 to 2020, demonstrated that patients aged 70 years and over were significantly less likely to proceed from the run-in period to randomised phase, and more likely to cease randomised trial treatment early compared to patients aged 65-69 years (p<0.05). A high rate of cognitive impairment (using the Montreal Cognitive Assessment) was observed in this otherwise fit population of older individuals. \nEnhanced platelet activation was identified at baseline between June 2018 and February 2020 in n=575 patients with a diagnosis of cancer (median urine TXB2 719 pg/mg creatinine), particularly in individuals with gastro-oesophageal and colorectal cancer (p < 0.001). Higher excretion rates of TXB2 were also found in patients with known stimuli of inflammation including BMI > 35 kg/m2, and elevated inflammatory markers. Low dose (100mg) aspirin inhibited thromboxane biosynthesis to levels expected in healthy people, with only a slight further reduction with a 3-fold higher aspirin dose. \nEvaluation of colorectal pathology forms from 1474 participants recruited between October 2015 and December 2019 exposed the national underutilisation of mismatch repair (MMR) testing. Thus, an adjuvant trial of immune checkpoint inhibitors in MMR deficient colorectal cancers is not feasible without an international effort or improvement in rates of testing. Furthermore, concerns were raised about the accuracy of more complex clinical trial data collection. \n \nCONCLUSION: \nFormalising personalisation, rather than clinical acumen alone, including the use of GA in older trial participants, biomarkers to evaluate pharmacodynamics, as well as molecular stratification factors, is required even with simple repurposed drugs such as aspirin.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.020 | 0.068 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".