Phase 2 Evidence and Impact Analysis
Article 1 — BRUIN CLL-322: Pirtobrutinib + VR vs VR in R/R CLL (PMID: 42425121)
| Dimension | Score | Rationale |
|---|---|---|
| Scientific Novelty | 8 | First Phase 3 RCT establishing a non-covalent BTKi + venetoclax-rituximab regimen; closes the pivotal evidence gap for post-covalent BTKi failure |
| Clinical Relevance | 9 | 45% reduction in progression/death risk in a population with very limited options post-covalent BTKi; fixed-duration design reduces treatment burden |
| Population Reach | 7 | CLL is the most common adult leukaemia (~20,000 new US cases/year; >200,000 living with disease globally); R/R segment is substantial |
| Implementation Speed | 8 | Phase 3 RCT in a high-priority indication; pirtobrutinib already FDA-approved as monotherapy (accelerated); label expansion likely within 1–2 years |
| Evidence Strength | 9 | Lancet Phase 3 RCT; HR 0.547 (p=0.0001); 639 patients; IRC-masked review; consistent across pre-specified subgroups including 80% prior covalent BTKi |
Key quantitative result: HR 0.547 (95% CI 0.400–0.748); 24-month PFS 87% vs 72%
External validation/replication: Single trial; no independent replication yet, but trial design and sponsor involvement (Lilly) are transparent; subgroup consistency is reassuring
Main limitation: Open-label design; overall survival data immature; median follow-up not specified in metadata; single pivotal trial without confirmatory study yet published
Equity implications: Patients in lower-income settings may lack access to pirtobrutinib (novel branded agent); patients who never received covalent BTKi (20% of cohort) may derive different benefit; geographic diversity of trial sites not specified
Evidence Maturity (confirmed): ✅ Potentially Practice-Changing
Article 2 — mDNN-cHM: CBC-based AI for Hematolymphoid Malignancy Classification (PMID: 42421054)
| Dimension | Score | Rationale |
|---|---|---|
| Scientific Novelty | 8 | First multimodal fusion of CBC numeric data + WBC scattergram images for simultaneous 6-subtype hematolymphoid classification vs infection; novel architecture and input modality |
| Clinical Relevance | 8 | Operates on universal, low-cost test; sub-30-min turnaround; directly actionable in after-hours and resource-limited settings where morphology review is unavailable |
| Population Reach | 8 | Hematolymphoid malignancies affect millions globally; CBC is performed billions of times annually; triage utility spans all healthcare settings |
| Implementation Speed | 7 | Software-based; integrates with existing analyzer output; regulatory clearance (IVD) required but pathway is established for AI diagnostics; potential 2–4 year horizon |
| Evidence Strength | 8 | 6-centre multicenter validation; AUC 0.98–1.00 (internal) and 0.95–1.00 (external); 4,996 patients; rigorous head-to-head vs current CBC review rules |
Key quantitative result: AUC 0.95–1.00 across subtypes in external validation; results within 0.5 hours of sample receipt
External validation/replication: External validation across 6 centres explicitly performed — a meaningful strength; no fully independent blind hold-out from a geographically distinct country
Main limitation: All centres are within a single country (China); performance in non-Asian ethnic populations and different analyzer platforms unvalidated; CBC scattergram formats vary by manufacturer
Equity implications: High potential benefit in low- and middle-income countries where haematopathology expertise is scarce; current validation limited to China, so generalizability to Africa, South Asia requires prospective testing
Evidence Maturity (confirmed): ✅ Potentially Practice-Changing (within current validation scope; broader deployment is Validated pending multi-platform, multi-ethnic testing)
Article 3 — NEVA: Vision-Language AI for Neuroblastoma Precision Oncology (PMID: 42426002)
| Dimension | Score | Rationale |
|---|---|---|
| Scientific Novelty | 9 | First disease-specific, end-to-end hierarchical vision-language foundation model for neuroblastoma; outperforms 10 leading general-purpose foundation models across 11 tasks |
| Clinical Relevance | 8 | NMYC amplification determines risk stratification and treatment intensity; predicting it from H&E alone removes dependency on costly FISH in resource-limited settings |
| Population Reach | 6 | Neuroblastoma is rare (~800 US cases/year; ~13,000 globally); however, relative to the affected paediatric population and unmet need, this is highly impactful |
| Implementation Speed | 5 | Retrospective validation only; prospective clinical deployment requires regulatory approval, pathology lab integration, and clinical workflow redesign; 3–6 year realistic horizon |
| Evidence Strength | 7 | 1,238 patients multi-institutional retrospective; AUROC 0.924 (NMYC), 0.916 (subtype); strong benchmarking against leading foundation models; Nature Communications peer-reviewed |
Key quantitative result: AUROC 0.924 for NMYC amplification; 0.916 for subtype classification from H&E alone; 11/11 tasks exceed comparison models
External validation/replication: Multi-institutional cohort used; but not a fully prospective independent external validation — training and validation cohorts drawn from same multi-site dataset
Main limitation: Retrospective design; no prospective clinical endpoint (e.g., treatment change, survival impact) measured; H&E slide quality and staining variation across institutions not fully characterised
Equity implications: Major potential benefit in low-resource settings where FISH-based NMYC testing is unavailable or unaffordable; paediatric cancer is disproportionately concentrated in LMICs; implementation may still require digital pathology infrastructure
Evidence Maturity (revised): Validated (strong retrospective) → targeting Potentially Practice-Changing pending prospective clinical validation
Article 4 — ASTARTÉ: Temocillin vs Carbapenems for 3GCR-E Bacteraemia (PMID: 42425122)
| Dimension | Score | Rationale |
|---|---|---|
| Scientific Novelty | 8 | First Phase 3 RCT for temocillin; validates a long-neglected narrow-spectrum agent in a high-priority AMR indication; novel contribution to carbapenem-sparing evidence |
| Clinical Relevance | 9 | Directly addresses a major unmet need: preserving carbapenems in 3GCR-E bacteraemia is an urgent global priority; non-inferiority achieved |
| Population Reach | 8 | 3GCR-E bacteraemia is globally prevalent, particularly in hospital settings; carbapenem-resistant organisms are a WHO priority pathogen group |
| Implementation Speed | 7 | Drug already exists (available in Belgium, UK); regulatory expansion needed in other markets; formulary acceptance and infectious disease stewardship uptake could be rapid |
| Evidence Strength | 8 | Lancet Phase 3 non-inferiority RCT; 328 patients; 29 centres; investigator-initiated design reduces industry bias; non-inferiority margin met (p=0.017) |
Key quantitative result: Clinical success 74% vs 73% (difference +0.3%, 95% CI −7.7% to ∞); non-inferiority demonstrated
External validation/replication: Single pivotal trial; trial conducted in Spain only — generalizability to other resistance epidemiology settings needs assessment
Main limitation: Single-country (Spain); open-label; abstract-only access limits full critical appraisal; non-inferiority margin threshold not specified in metadata; 28-day endpoint may miss longer-term outcomes
Equity implications: Narrow-spectrum agent reduces collateral resistance pressure — a public health equity benefit; temocillin is currently unavailable in most of the world including high-burden LMICs; regulatory approval required for broader access
Evidence Maturity (confirmed): ✅ Potentially Practice-Changing
Article 5 — AI for Early PNH Detection in 1.3M EHR Patients (PMID: 42426209)
| Dimension | Score | Rationale |
|---|---|---|
| Scientific Novelty | 8 | First large-scale prospective real-world AI deployment for PNH screening; EHR-based phenotyping for ultra-rare disease at population scale is a methodological milestone |
| Clinical Relevance | 8 | PNH diagnosis delays of 5+ years are common and life-threatening; improving PPV and reducing time-to-diagnosis directly impacts survival and complement inhibitor eligibility |
| Population Reach | 5 | PNH is ultra-rare (~15,000 US patients); scored relative to the affected population and extreme diagnostic unmet need |
| Implementation Speed | 8 | Algorithm is EHR-deployable; already prospectively deployed across 14 institutions; regulatory pathway for software screening aids is manageable; near-term scalable |
| Evidence Strength | 7 | Prospective deployment across 1.3M real-world patients; PPV improvement documented; 13/119 confirmed diagnoses; AstraZeneca sponsorship introduces bias risk; NPJ Digital Medicine peer-reviewed |
Key quantitative result: PPV 10.92% vs conventional 6.9%; 74–1,337 day diagnostic delays identified retrospectively; 13 new confirmed PNH diagnoses from 356 flagged
Main limitation: Low absolute PPV (10.9%) means ~89% of flagged patients do not have PNH; AstraZeneca (ravulizumab manufacturer) sponsorship is a meaningful conflict; single-country deployment (Poland)
Equity implications: Model trained and deployed in a single healthcare system (Polish) — may not generalize to other EHR structures or coding practices; benefit is concentrated in health systems with digitised EHR infrastructure
Evidence Maturity: ✅ Validated (real-world deployment demonstrated)
Article 6 — GeneLLM: Transformer LLM for Multi-Cancer cfRNA Detection (PMID: 42425994)
| Dimension | Score | Rationale |
|---|---|---|
| Scientific Novelty | 9 | Sequence-level LLM applied to raw cfRNA nucleotides is conceptually distinct from all prior annotation-dependent liquid biopsy approaches; "transcriptomic dark matter" utilisation is novel |
| Clinical Relevance | 5 | Multi-cancer detection demonstrated but no prospective clinical validation; no tissue-of-origin resolution reported; sensitivity/specificity at population-screening thresholds not assessed |
| Population Reach | 8 | Multi-cancer early detection is a population-scale opportunity; lower sequencing cost potentially democratises access |
| Implementation Speed | 3 | Retrospective proof-of-concept; clinical validation studies, regulatory approval, and assay standardisation needed; 5–8 year realistic horizon |
| Evidence Strength | 6 | Multi-centre retrospective cohort; AUC 0.925–0.996; Nature Communications; no prospective arm; annotation-free approach requires regulatory conceptual framework not yet established |
Key quantitative result: AUC 0.9250–0.9962 across cancer types at 1/6th standard sequencing depth
Main limitation: Retrospective only; cancer-vs-healthy binary without tissue-of-origin; no assessment of performance in early-stage asymptomatic screening population
Evidence Maturity (revised): Exploratory → Validated for proof-of-concept; Potentially Practice-Changing framing is premature without prospective data
Article 7 — GLP-1RA Discontinuation and Psychiatric Risk in T2D (PMID: 42426287)
| Dimension | Score | Rationale |
|---|---|---|
| Scientific Novelty | 8 | First large-scale study specifically examining post-discontinuation psychiatric risk signal for GLP-1RAs; rebound triglyceride mediation is a novel mechanistic hypothesis |
| Clinical Relevance | 8 | Tens of millions of patients are on or stopping GLP-1RAs annually; a post-cessation psychiatric risk signal has immediate monitoring implications |
| Population Reach | 9 | GLP-1RAs among most widely prescribed drug classes globally; T2D affects ~500M people; discontinuation rates are high |
| Implementation Speed | 8 | Observational finding requiring clinical monitoring protocol changes only; no regulatory action needed to begin post-cessation mental health follow-up |
| Evidence Strength | 6 | Active-comparator cohort design (strongest feasible observational design); large EHR cohort (Shanghai); abstract-only; cannot establish causation; confounding by indication possible |
Key quantitative result: Significantly elevated risk of incident depression/anxiety post-GLP-1RA cessation vs DPP4i/SGLT2i cessation (magnitude not specified in metadata — abstract-only limitation)
Main limitation: Observational — cannot rule out residual confounding; effect size not available from abstract; single-country EHR database; no biological confirmation of triglyceride mediation mechanism
Equity implications: Patients with limited access to mental health services (already disadvantaged) may be most harmed by unmonitored post-cessation psychiatric events; finding relevant to all GLP-1RA users globally but evidence base is Chinese
Evidence Maturity (confirmed): ✅ Validated (observational)
Article 8 — Tri-Cistronic NK Cell Platform for Pan-Cancer Immunosuppression Override (PMID: 42425951)
| Dimension | Score | Rationale |
|---|---|---|
| Scientific Novelty | 9 | Triple-mechanism simultaneous override in a single retroviral construct (PD-L1→activating signal + HLA-E/NKG2A blockade + IL15 autocrine) is conceptually unique |
| Clinical Relevance | 3 | Preclinical only; species unknown; no human data; Clinical Relevance capped per non-human study rule |
| Population Reach | 7 | Pan-cancer platform — if translated, applicable across many solid and haematological tumours |
| Implementation Speed | 2 | Lab stage; IND application, Phase 1 manufacturing, safety studies needed; 6–10 year realistic horizon |
| Evidence Strength | 4 | Preclinical mechanistic; species unclear; Signal Transduct Target Ther is reputable; no in vivo xenograft survival data mentioned in metadata |
Key quantitative result: Pan-cancer cytotoxicity demonstrated; de novo PD-L1 induction in PD-L1-negative tumours; extended in vivo NK persistence — quantitative magnitudes not specified
Main limitation: Unknown species model; no human data; no survival endpoint; allogenicity and GvH risk not assessed; single lab; no independent replication
Evidence Maturity (confirmed): ✅ Exploratory
Article 9 — China-AIHeart Transformer for CVD Risk Prediction (PMID: 42425502)
| Dimension | Score | Rationale |
|---|---|---|
| Scientific Novelty | 7 | Transformer architecture for CVD risk is novel in this population; but CVD prediction ML models are a crowded field; sex-specific design adds distinction |
| Clinical Relevance | 7 | Improved reclassification (NRI 0.478–0.560) over guideline risk scores directly applicable to statin/intervention decision-making in Chinese adults |
| Population Reach | 9 | China has >300M adults at CVD risk; model trained specifically for Chinese population fills a validated gap in Western-centric risk score performance |
| Implementation Speed | 6 | Needs clinical workflow integration, regulatory pathway, and physician uptake; independently validated but not yet guideline-endorsed; 3–5 year horizon |
| Evidence Strength | 7 | 156,790 derivation cohort + 2 independent external validations; C-statistic 0.767–0.780; EHJ publication; abstract-only limits full appraisal |
Key quantitative result: C-statistic 0.767–0.780; NRI 0.478–0.560 vs Cox; ΔAUROC +0.027–0.031 over identical-predictor Cox model
Main limitation: All cohorts are Chinese — generalizability to Chinese diaspora or other Asian populations untested; abstract-only access; no randomised comparison of outcomes under model-guided vs standard risk score-guided treatment
Equity implications: Specifically addresses underserved Chinese/Asian populations who are miscalibrated by Western risk scores — a meaningful equity advance; but limited to those with access to digital health infrastructure
Evidence Maturity (confirmed): ✅ Validated
Article 10 — Biomni: Autonomous AI Agent for Biomedical Research (PMID: 42424436)
| Dimension | Score | Rationale |
|---|---|---|
| Scientific Novelty | 9 | Autonomous general-purpose biomedical research agent across 25 domains without task-specific tuning; Science publication; landmark in AI-driven discovery |
| Clinical Relevance | 4 | Rare-disease diagnosis capability demonstrated, but this is a research tool — not a point-of-care diagnostic; indirect clinical relevance via accelerated discovery |
| Population Reach | 7 | Accelerates research across all disease areas; indirect population benefit is broad |
| Implementation Speed | 4 | Research infrastructure tool; wet-lab integration requires significant validation; not deployable at bedside; 3–5 year research utility realisation |
| Evidence Strength | 6 | Computational benchmarking study; Science peer review; no clinical trial data; benchmark task performance may not reflect real-world research value |
Main limitation: Benchmarking metrics may not translate to real research breakthroughs; hallucination risk in LLM reasoning chains not quantified; no prospective research study using Biomni as primary tool yet published
Evidence Maturity (confirmed): ✅ Validated (for benchmarking claims); research utility remains to be demonstrated prospectively
Article 11 — 3D V-Net + MedGemma LLM for csPCa Detection on mpMRI (PMID: 42425805)
| Dimension | Score | Rationale |
|---|---|---|
| Scientific Novelty | 7 | LLM integration with volumetric 3D segmentation for prostate MRI is architecturally novel; MedGemma (4B parameters) application to medical imaging is timely |
| Clinical Relevance | 7 | csPCa detection on mpMRI is a high-volume, high-stakes clinical problem; AUROC 0.900 with superior DCA net benefit across thresholds 0.3–0.9 is clinically meaningful |
| Population Reach | 8 | Prostate cancer is the most common male cancer; mpMRI interpretation variability between radiologists is a known problem |
| Implementation Speed | 5 | Retrospective external validation; PI-RADS workflow integration and regulatory clearance needed; heterogeneous scanner protocols partially addressed by validation design |
| Evidence Strength | 7 | 1,154-patient external validation; DCA and NRI reported; multi-institutional; abstract-only limits full critical review |
Key quantitative result: AUROC 0.900 (95% CI 0.882–0.918); ΔAUROC +0.060–0.145 vs individual models (p<0.001)
Main limitation: Retrospective; no prospective biopsy-endpoint trial; MedGemma is proprietary (Google); generalizability to low-field MRI or non-3T scanners unclear
Evidence Maturity (confirmed): ✅ Potentially Practice-Changing (with further prospective validation)
Article 12 — RareBoost: Stepwise Genomics for Undiagnosed Rare Diseases (PMID: 42426151)
| Dimension | Score | Rationale |
|---|---|---|
| Scientific Novelty | 6 | Stepwise genomic strategy is established concept; novelty is in systematic framework demonstration and RNA integration yield; incremental rather than transformative |
| Clinical Relevance | 7 | 50.8% diagnostic yield in previously negative families directly ends diagnostic odysseys; actionable in any genomic medicine centre |
| Population Reach | 6 | Rare disease collectively affects 300M globally; undiagnosed subset is large; this framework is replicable |
| Implementation Speed | 7 | No new technology needed; existing sequencing platforms + reanalysis pipeline; scalable in countries with genomic medicine infrastructure |
| Evidence Strength | 6 | Prospective cohort; 120 families; European Journal of Human Genetics; no control arm; modest sample size |
Main limitation: n=120 families; no randomised design; yield may vary by disease spectrum; non-coding variant interpretation remains subjective; abstract-only
Evidence Maturity (confirmed): ✅ Validated
Article 13 — Lung Transplantation for PAP: International Multicenter Retrospective (PMID: 42425729)
| Dimension | Score | Rationale |
|---|---|---|
| Scientific Novelty | 6 | Largest PAP transplant dataset ever — fills a pure evidence void; not conceptually novel but empirically necessary |
| Clinical Relevance | 7 | Directly informs transplant listing decisions for an otherwise lethal condition where no alternative exists; best available evidence |
| Population Reach | 4 | PAP is ultra-rare (~1/1.25M); scored relative to affected community and transplant decision impact |
| Implementation Speed | 7 | Data immediately applicable to clinical decision-making; no new technology required |
| Evidence Strength | 5 | 37-centre retrospective; medium confidence classification; abstract-only; largest available series but inherently limited by design |
Main limitation: Retrospective; medium classification confidence; abstract-only; selection bias in transplant listing; outcome data completeness across 37 international centres variable
Evidence Maturity (confirmed): ✅ Validated (best available for this indication)
Article 14 — NCCN MPN Guidelines v2.2026 (PMID: 42425157)
| Dimension | Score | Rationale |
|---|---|---|
| Scientific Novelty | 3 | Guideline update — synthesises existing evidence; no new primary data |
| Clinical Relevance | 8 | Immediately shapes treatment decisions for tens of thousands of MPN patients in US and internationally |
| Population Reach | 7 | MPN affects ~150,000 US patients; guideline reach is global |
| Implementation Speed | 10 | Already in practice; clinicians consult NCCN daily |
| Evidence Strength | 7 | Expert consensus of 32 specialists + evidence review; limited by guideline methodology (not primary trial) |
Evidence Maturity (confirmed): ✅ Validated (consensus synthesis)
Article 15 — DISSECT: Cytological Image + Spatial Transcriptomics Cell Segmentation (PMID: 42426365)
| Dimension | Score | Rationale |
|---|---|---|
| Scientific Novelty | 8 | Novel fusion of image and transcriptome modalities via deep generative model for segmentation; addresses a genuine technical bottleneck in spatial transcriptomics |
| Clinical Relevance | 4 | Research methodology; applied to gastric cancer/anti-PD-1 context but not a clinical diagnostic tool yet |
| Population Reach | 5 | Enables better research tools broadly but indirect clinical impact at this stage |
| Implementation Speed | 3 | Research software; requires spatial transcriptomics infrastructure; 3–5 years to clinical research translation |
| Evidence Strength | 6 | Computational validation + small gastric cancer application; Nature Computational Science; abstract-only |
Evidence Maturity (confirmed): ✅ Validated (methodological tool)
Article 16 — ABCB8/Iron-Epigenetic Axis in -7/del(7q) AML (PMID: 42425977)
| Dimension | Score | Rationale |
|---|---|---|
| Scientific Novelty | 9 | Previously unknown tumour suppressor mechanism linking mitochondrial iron transport to KDM6A/H3K27me3 in the most aggressive AML cytogenetic subtype |
| Clinical Relevance | 3 | Preclinical; no therapeutic candidates yet; Clinical Relevance capped per mixed-species preclinical rule |
| Population Reach | 5 | del(7q) AML is a high-mortality subset of AML (~30% of de novo AML has 7q abnormalities); mechanism may be more broadly relevant |
| Implementation Speed | 2 | Basic discovery; drug development pipeline years away |
| Evidence Strength | 6 | CRISPR screen + mechanistic validation in mixed human/mouse models; Nature Communications; high quality for a mechanistic study |
Evidence Maturity (confirmed): ✅ Exploratory
Article 17 — utDNA Dynamics for UTUC Recurrence Prediction (PMID: 42425884)
| Dimension | Score | Rationale |
|---|---|---|
| Scientific Novelty | 7 | Combined mutation + fragmentomics (utLIFE) in urine for UTUC surveillance is novel; longitudinal trajectory approach adds methodological value |
| Clinical Relevance | 7 | 5.67-month lead time over cystoscopy; 83% vs 17% sensitivity is a clinically dramatic difference; actionable for adjuvant therapy decisions |
| Population Reach | 4 | UTUC is uncommon (~16,000 US cases/year); moderate unmet need |
| Implementation Speed | 5 | Small study requires larger validation; urine ctDNA assays exist but utLIFE pipeline needs standardisation |
| Evidence Strength | 5 | Prospective design is a strength; n=47 is a major limitation; abstract-only |
Key quantitative result: Sensitivity 83.3% vs 16.7% (cystoscopy); lead time 5.67 months; independent predictor of RFS
Evidence Maturity: Validated (for signal detection) → needs larger prospective confirmation
Article 18 — P4hb(Y393C) Mouse Model and Therapeutics for Cole-Carpenter Syndrome (PMID: 42425402)
| Dimension | Score | Rationale |
|---|---|---|
| Scientific Novelty | 7 | First disease model for an untreatable ultra-rare disorder; dual therapeutic readout (drug repurposing + allele-specific siRNA) is meaningful for so rare a condition |
| Clinical Relevance | 3 | Animal model; Clinical Relevance capped at ≤5 per non-human study rule; FDA-approved drug repurposing shortens path |
| Population Reach | 3 | Ultra-rare (<100 known cases worldwide); scored relative to extreme unmet need |
| Implementation Speed | 3 | Preclinical; IND, toxicology, and Phase 1 studies needed |
| Evidence Strength | 4 | Mouse model with compound screen; Life Sciences (moderate journal); abstract-only; no in vivo therapeutic efficacy data specified |
Evidence Maturity (confirmed): ✅ Exploratory
Article 19 — Geriatric Assessment Tools Comparison for Older Adults (PMID: 42421064)
| Dimension | Score | Rationale |
|---|---|---|
| Scientific Novelty | 4 | Comparative head-to-head of existing validated tools; incremental rather than novel |
| Clinical Relevance | 5 | Helps clinicians choose appropriate tools; useful but indirect — no evidence that switching tools improves outcomes |
| Population Reach | 8 | Aging populations globally; highly relevant to geriatric, primary, and preventive care |
| Implementation Speed | 7 | Findings immediately applicable without new technology; changes tool selection practice |
| Evidence Strength | 5 | Comparative validation study; medium confidence; BMC Medicine; meaningful population follow-up data |
Evidence Maturity (confirmed): ✅ Validated
Article 20 — Medulloblastoma Therapeutic Development Workshop Consensus (PMID: 42426296)
| Dimension | Score | Rationale |
|---|---|---|
| Scientific Novelty | 5 | Consensus output identifies targets (B7-H3 CAR-T, SRC degraders); no new trial data; roadmap document |
| Clinical Relevance | 5 | Shapes near-term trial design for a high-mortality paediatric cancer; 35+ expert centres contributing |
| Population Reach | 5 | Rare paediatric cancer (~500 US cases/year); high-risk subgroup mortality >50%; relative unmet need is extreme |
| Implementation Speed | 5 | Shapes trials that will take 5–10 years; near-term impact is on trial design only |
| Evidence Strength | 4 | Expert consensus; no clinical data presented; British Journal of Cancer |
Evidence Maturity (confirmed): ✅ Validated (consensus quality evidence)