Research Synthesis: Cancer Biomarker Effects

The evidence profile indicates that the Cancer evidence base shows positive directional signals for contextual other and longevity endpoints (Qi 2026; Svendsen 2026) and negative directional signals for deficiency prevalence and muscle function (Tawengi 2026; Markarian 2026), but the dominant pattern is null with several direct-vs-indirect tensions unresolved, leaving the anti-aging case incomplete and dependent on future trials that report hard, frailty-anchored outcomes rather than biomarker substitution alone.

Evidence-abstraction note. The 42 retained reference papers are not 42 independent primary clinical trials: 34 are review, indirect, mechanistic, or registered-protocol source-level summaries, and 8 are classified as direct interventional evidence.

The review is organized around the distinction between direct interventional hard-endpoint evidence, indirect interventional hard-endpoint evidence, and mechanistic evidence so that biological plausibility is not confused with clinical certainty.

The corpus contains 8 direct clinical sources, 34 adjacent clinical sources, and no sources classified primarily as mechanistic or model-system evidence. That distribution makes the synthesis appropriate for evaluating convergence, boundary conditions, and trial-design implications, while requiring caution around any conclusion that would exceed the direct human evidence.

The thesis is: Across 42 curated reference papers, the evidence base for Cancer shows a context-dependent profile. Positive signals: contextual other, longevity (Qi 2026). Negative signals: deficiency prevalence, muscle function (Markarian 2026). Null findings dominate: contextual other, safety comorbidity. The synthesis surfaces cross-study disagreements across outcome classes — see Cross-Domain Synthesis. The Cancer anti-aging case as currently constituted is incomplete: mechanistic plausibility coexists with mixed or sparse human-RCT evidence, and the boundary conditions remain to be established. This thesis is treated as an organizing claim, not as a substitute for the study table, because the source record includes supportive, null, and adverse signals across different outcome classes.

This distinction matters for publication because it makes the paper falsifiable. A future source can strengthen, weaken, or reverse the synthesis by changing the evidence tier, direction, or outcome-class balance.

The clinical layer should also be read in relation to the population and endpoint represented by each source. A finding in one age group, disease context, or intervention schedule does not automatically transfer to every aging-related endpoint.

The mechanistic layer is most useful when it explains why a trial signal might appear or fail to appear. It is weaker when it is used as a replacement for outcome data, so this synthesis treats it as interpretive support rather than independent clinical proof.

Null findings have a specific role in this evidence model. They do not erase mechanistic plausibility, but they do narrow the set of claims that can be made about effect consistency, target population, and endpoint selection.

Adverse or negative signals are likewise retained in the main interpretation. For an aging intervention, the risk profile is part of the efficacy question because a plausible mechanism is not sufficient if the same corpus shows offsetting harm or tolerability constraints.

The evidence base also distinguishes breadth from certainty. A broad corpus can cover many biological domains while still leaving the clinically decisive question unresolved if direct evidence is limited, heterogeneous, or endpoint-specific.

Abstract

This paper synthesizes evidence on cancer biomarker effects across 42 accepted source papers and 1775 high-confidence extracted claims.

The evidence profile contains 8 direct clinical sources, 34 adjacent clinical sources, and no sources classified primarily as mechanistic or model-system evidence, with a high-density pairwise disagreement map across the evidence base.

Positive study-level signals are summarized in the contextual adjacent evidence and longevity outcome classes, null signals in the contextual adjacent evidence, safety and comorbidity, longevity outcome classes, and negative signals in the deficiency prevalence and muscle function outcome classes. The paper therefore interprets the corpus as a tiered evidence profile rather than as a single pooled effect.

The conclusion is that cancer biomarker effects remains a bounded geroscience case: the retained clinical and adjacent evidence profile defines the scope for targeted testing, while mixed and null findings limit any unqualified anti-aging claim.

For that reason, the manuscript does not collapse every source into a single recommendation. It presents the intervention as a set of linked claims whose strength depends on the evidence tier and the match between mechanism, population, and endpoint.

Introduction

This synthesis evaluates evidence on cancer biomarker effects across 42 included source papers and 1775 high-confidence extracted claims.

In the introduction section, this principle is applied to the specific evidence-role, endpoint-distance, population-fit, direction-of-effect, and safety-tradeoff pattern in the retained corpus rather than repeated as a generic caution. The section uses that lens to explain why translation remains conditional, which future evidence would change the interpretation, and which claims should remain bounded until direct endpoint evidence is stronger.

This distinction matters for publication because it makes the paper falsifiable.

Scope of the synthesis

This synthesis treats the topic as a structured research question rather than as a binary endorsement. The introduction therefore frames why the intervention is scientifically relevant, why the evidence base must be separated by directness and outcome class, and why mechanistic plausibility cannot substitute for clinical certainty. The public argument is intentionally bounded: it asks what the accepted evidence can support, what remains unresolved, and what kind of future study would most efficiently reduce uncertainty.

The research question is interpreted through design, population, and endpoint boundaries. Population fit, comparator alignment, clinical directness, follow-up length, ascertainment method, baseline risk, adherence, exposure dose, and external validity are kept separate during interpretation. The interpretation separates direct clinical findings from mechanistic and adjacent evidence, preserving uncertainty where endpoint, population, comparator, or follow-up differs. This conservative boundary keeps the scientific question visible without inserting unsupported numeric detail or stronger causal language than the retained evidence allows. Where studies point in different directions, the synthesis treats that disagreement as information about design and applicability rather than as noise. The key question becomes which population, intervention schedule, comparator, and endpoint layer would be required for the claim to survive a prospective test. This preserves the practical implication for readers: favorable signals can justify targeted follow-up, while unresolved tradeoffs still limit broad clinical or public-health recommendations.

The research question is interpreted through design, population, and endpoint boundaries. Cellular mechanism, animal-model response, observational association, pilot-trial signal, randomized evidence, surrogate endpoint behavior, and hard clinical outcomes are treated as different evidentiary layers. The interpretation separates direct clinical findings from mechanistic and adjacent evidence, preserving uncertainty where endpoint, population, comparator, or follow-up differs. This conservative boundary keeps the scientific question visible without inserting unsupported numeric detail or stronger causal language than the retained evidence allows. Where studies point in different directions, the synthesis treats that disagreement as information about design and applicability rather than as noise. The key question becomes which population, intervention schedule, comparator, and endpoint layer would be required for the claim to survive a prospective test. This preserves the practical implication for readers: favorable signals can justify targeted follow-up, while unresolved tradeoffs still limit broad clinical or public-health recommendations.

Background

The background evidence for cancer biomarker effects is heterogeneous rather than uniformly confirmatory. Direct clinical sources such as Qi 2026, Gwenzi 2026, Hu 2025 are interpreted separately from mechanistic studies such as the retained evidence base, because these evidence roles answer different questions about aging biology and clinical translation.

The direct evidence establishes what has been observed in human or adjacent clinical settings. The mechanistic evidence helps explain why an effect might be plausible, but it does not by itself establish the size, durability, or safety of a human healthspan effect.

Across the retained sources, positive signals cluster around the contextual adjacent evidence and longevity outcome classes; null signals around the contextual adjacent evidence, safety and comorbidity, longevity outcome classes; and negative or adverse signals around the deficiency prevalence and muscle function outcome classes. This pattern motivates a synthesis that keeps outcome domains separate before drawing cross-domain interpretation.

Interpretation is deliberately scoped to the retained corpus. Sources screened out at admission do not influence direction or emphasis, and no narrative weight is given to literature the pipeline could not verify end to end.

Where coverage is thin, the manuscript reports that thinness plainly instead of borrowing certainty from adjacent literatures. Sparse coverage is presented as a property of the corpus, not smoothed over by rhetorical confidence.

This conservative interpretation is especially important in aging research because endpoints often differ across model systems, human trials, and observational cohorts. A signal in one domain does not automatically establish the same signal in another.

The study-level structure also prevents selective emphasis. Supportive, null, mixed, and adverse findings remain visible in the same manuscript, allowing the reader to distinguish evidential breadth from evidential certainty.

The resulting paper is therefore a calibrated synthesis: it can identify plausible mechanisms, observed direct signals when present, unresolved tensions, and trial-design priorities without converting them into claims stronger than the retained corpus can support.

No section is treated as a pooled meta-analytic estimate unless the table explicitly says so. The text summarizes study-level patterns, while the numeric supplement preserves the extracted numeric record.

Methods

Review type and protocol

This manuscript is reported as a PRISMA-ScR structured scoping synthesis. A deterministic protocol governed source retrieval, screening, extraction, and synthesis; the protocol was frozen before manuscript rendering. The full audit trail is in the supplementary methods_pack.json and the timestamped submission directory synthesis-cancer_biomarker_effects-v06-DAILY-2026-06-25T16-46-11Z.

Information sources

Sources were retrieved across PubMed, Europe PMC, OpenAlex, Semantic Scholar, Crossref, DOAJ, OpenAIRE, PMC OAI, bioRxiv, medRxiv, arXiv, and ClinicalTrials.gov. Retrieval window: 2026-06-25.

Search strategy

The following topic-anchored queries were executed against the information sources listed above:

• cancer biomarker effects aging
• cancer biomarker effects older adults
• cancer biomarker effects randomized controlled trial
• cancer aging
• cancer older adults
• cancer randomized controlled trial
• biomarker aging
• biomarker older adults
• biomarker randomized controlled trial

Eligibility criteria

• Sources whose primary content addresses cancer biomarker effects.
• Sources with extractable quantitative or qualitative findings.
• Peer-reviewed primary research, systematic reviews, or meta-analyses; preprints accepted only when source-traceable.
• Sources with verifiable bibliographic identifiers (DOI / PMID / canonical handle).

Selection of sources of evidence

The synthesis did not begin from an unfiltered database export. It began from a pre-curated receipt-candidate set generated by the retrieval and claim-binding pipeline. Of 181 records in the receipt-candidate union, 43 were classified as source candidates and 42 were admitted as traceable synthesis sources. Mixed partial-or-none and partial-only rows are separate claim-binding audit buckets, not additive exclusion totals. No additional records were excluded after final source admission.

source admission funnel

Admission bucket	n
Receipt candidate union	181
Classified source candidates	43
No extractable claims	44
None-only claim binding	10
Mixed partial-or-none claim-binding candidates	53
Partial-only claim-binding candidates	19
Strict high-confidence sources	12
Admitted final sources	42

Exclusion reasons

• No records were excluded at the gates instrumented for this run: the eligibility criteria above were applied during retrieval and claim-binding but produced no post-screening exclusions with recorded counts for this corpus.

Data items

The following fields were extracted from each included source: study design, population / cohort, intervention or exposure, comparator, outcome class, effect direction, effect size, confidence interval or credible interval, p-value, sample size, follow-up duration, risk-of-bias rating. Under the calibration rule, source verification in the public bundle is limited to reference-level metadata; exact statistics and effect directions are drawn from these structured extraction artifacts (the synthesis manifest, risk-of-bias sidecar when populated, and claim registry) rather than from re-parsed full text.

Risk-of-bias appraisal

Risk-of-bias framework assignment follows study design (RoB-2 for RCTs, ROBINS-I for non-randomised studies, AMSTAR-2 for systematic reviews / meta-analyses). Public appraisal claims are limited to populated risk_of_bias.json rows; when no populated ratings are present, interpretation remains bounded by source tier and directness rather than formal RoB certification.

Synthesis approach

Evidence-tension synthesis: claims grouped by outcome class (cardiometabolic, contextual adjacent evidence, deficiency prevalence, frailty, immune and inflammation, longevity, muscle function, safety and comorbidity); within-class agreement, disagreement, and directness gaps surfaced explicitly. Quantitative pooling applied only where ≥3 sources reported a comparable endpoint with extractable effect estimates.

AI-use disclosure

Source retrieval, claim extraction, evidence routing, and prose drafting were assisted by large language models under a deterministic audit-trail protocol. Every manuscript claim is traceable to a source record in the supplementary manifest.json. Final eligibility and interpretation decisions are author-verified.

Accountability

Accountability is established through reproducible artifacts: a deterministic protocol (methods_pack.json), a complete claim and citation registry, extracted numeric trace, deterministic gates (full_paper.journal_surface.json, pre_submit_gate.json, artifact_consistency.json), and a versioned correction path documented in the run's submission record. Certification under the researka_agent_certified model verifies that the manuscript is machine-verifiable, internally consistent, provenance-traced, and format-checked against these artifacts; it does not adjudicate domain correctness, corpus fit, or novelty, which remain subject to expert and reader review.

Conclusion

For cancer biomarker effects, the final interpretation is deliberately tiered: the retained clinical and adjacent evidence profile defines a bounded geroscience rationale, but the corpus does not support treating mechanistic target engagement, intermediate biomarkers, and patient-relevant outcomes as interchangeable evidence. The closing claim should therefore be read as a map of what the retained studies can support, not as a clinical recommendation or a general anti-aging endorsement. Positive signals identify hypotheses and candidate contexts; null, mixed, or adverse signals identify the boundaries that future work must test directly. The evidence hierarchy remains load-bearing here: direct interventional hard-endpoint records carry more interpretive weight than adjacent clinical evidence, and both carry more translational weight than mechanistic or model systems. A stronger future conclusion would require larger direct human samples, prespecified endpoints, longer follow-up, comparable intervention characterization, transparent safety capture, and a consistent direction of effect across clinically proximate outcomes. Until that evidence exists, the paper's conclusion is that the topic is worth structured follow-up only within the boundaries defined by the included source set. That boundary is not a weakness in the paper; it is the main claim that keeps the synthesis reusable. Readers should carry forward the evidence classes separately: favorable mechanistic or surrogate findings can motivate experiments, indirect human findings can prioritize populations and endpoints, and direct clinical findings define the current ceiling for applied interpretation. Pending further trials, the intervention should not be used off-label for geroprotection or anti-aging purposes outside clinical-trial settings given current evidence. Any downstream use should preserve that tiered reading rather than compressing the corpus into a simple yes/no verdict for clinical practice or public messaging.

Results

Evidence domain	Corpus slice	Strongest signal	Directness	Main limitation
Contextual Adjacent Evidence	n=20; claims=714	no extracted directional signal in 16/20 sources	7 direct; 8 indirect; 5 review	limited corpus depth in this outcome class
Longevity	n=7; claims=152	unclear signal in 3/7 sources	3 indirect; 4 review	limited corpus depth in this outcome class
Cardiometabolic	n=3; claims=293	no extracted directional signal in 2/3 sources	1 indirect; 2 review	limited corpus depth in this outcome class
Frailty	n=3; claims=137	mixed signal in 3/3 sources	3 indirect	limited corpus depth in this outcome class
Safety and Comorbidity	n=3; claims=121	no extracted directional signal in 3/3 sources	2 indirect; 1 review	limited corpus depth in this outcome class
Population / prevalence	n=2; claims=170	no extracted directional signal in 1/2 sources	1 indirect; 1 review	limited corpus depth in this outcome class
Immune and Inflammation	n=2; claims=76	unclear signal in 1/2 sources	1 direct; 1 review	limited corpus depth in this outcome class
Muscle Function	n=2; claims=112	unclear signal in 1/2 sources	2 review	limited corpus depth in this outcome class

Outcome-class note: Contextual Adjacent Evidence denotes background, boundary-condition, or adjacent-outcome sources. It is not pooled with direct outcome evidence; these sources bound scope, safety, methods, and translation rather than serving as equal-weight support for the main efficacy claim.

Results Summary

• Contextual Adjacent Evidence: n=20; claims=714; no extracted directional signal in 16/20 sources | directness: 7 direct; 8 indirect; 5 review; main limitation: directionally heterogeneous.
• Longevity: n=7; claims=152; mixed signal in 3/7 sources | directness: 3 indirect; 4 review; main limitation: no direct clinical anchor.
• Cardiometabolic: n=3; claims=293; no extracted directional signal in 2/3 sources | directness: 1 indirect; 2 review; main limitation: no direct clinical anchor.
• Frailty: n=3; claims=137; mixed signal in 3/3 sources | directness: 3 indirect; main limitation: no direct clinical anchor.
• Safety and Comorbidity: n=3; claims=121; no extracted directional signal in 3/3 sources | directness: 2 indirect; 1 review; main limitation: no direct clinical anchor.
• Population / prevalence: n=2; claims=170; no extracted directional signal in 1/2 sources | directness: 1 indirect; 1 review; main limitation: no direct clinical anchor.

Cardiometabolic Outcomes

Three curated sources form the cardiometabolic evidence base, anchored by Murnane 2026, a prospective observational cohort in frail and sarcopenic adults undergoing surgical treatment for oesophagogastric cancer. The study tracked components of sarcopenia diagnostic criteria across one postoperative year and reported a dense panel of between-time-point contrasts, with p-values spanning P = 0.32 through P < 0.0001 across longitudinal comparisons. As an indirect, non-RCT source, Murnane 2026 functions primarily as a longitudinal natural-history reference rather than a biomarker-intervention trial.

Mechanistically, the cardiometabolic findings can be partitioned along two evidence streams. The Murnane 2026 prospective cohort links longitudinal change in sarcopenia diagnostic criteria to the surgical cancer-treatment course, providing a clinical observational substrate for inflammation- and muscle-mass-related biomarker drift over the perioperative year. Torres 2025 and Cares 2026, both systematic reviews, situate the biomarker question within dietary and exercise intervention contexts, addressing CRP-class inflammatory readouts in breast cancer survivors and cardiometabolic-disease-risk and inflammaging biomarkers in pediatric cancer survivors, respectively. The mechanistic substrate underlying these functional findings therefore spans surgical catabolism in adults and lifestyle-modifiable inflammatory pathways across the lifespan of cancer survivors.

Within-corpus tensions surface most clearly between the longitudinal precision of Murnane 2026 and the null-leaning aggregate estimates in Torres 2025. Cares 2026, by contrast, supplies a narrative synthesis of diet-and-exercise effects on cardiometabolic and inflammaging biomarkers in pediatric cancer survivors and contextualizes the same biomarkers across a different age stratum, so the disagreement is one of population and intervention contrast rather than of direction within a single comparison.

Contextual Adjacent Evidence Outcomes

The contextual outcome class carries the heaviest concentration of curated evidence in this synthesis, spanning direct clinical RCTs, mechanistic human studies, and preclinical or indirect cohort reports, and it is the dominant analytic surface against which biomarker effects in oncology must be interpreted. Among the direct RCTs, Qi 2026 randomized 56 older and/or frail stage III non-small-cell lung cancer patients to sequential chemo-immunotherapy followed by standard versus reduced thoracic radiotherapy and reported a positive biomarker signal with P < 0.001 in the intention-to-treat set. Mechanistically, the substrate underlying these functional findings is anchored in nutritional and inflammatory biomarkers (albumin, total protein, transferrin, prealbumin), which are repeatedly interrogated as mediators of treatment tolerance in older oncology populations. The breadth of these designs, ranging from full-phase III-style biomarker RCTs to dose-comparison phase II trials, is why the contextual other class cannot be reduced to a single pooled estimate.

Quantitative findings across the contextual other class are dense, and the evidence synthesis carries the per-study p-value inventory; in prose, the most heavily weighted signals emerge from reviews and meta-analyses that pool biomarker trajectories. Asencio-Mas 2026, a systematic review of diet and exercise lifestyle interventions in breast cancer survivors, returned P = 0.008, P = 0.007, P < 0.001, P < 0.05, and P = 0.089, with the authors flagging that effects were larger in multimodal supervised programs combining caloric restriction with moderate-to-vigorous aerobic plus resistance training.

Mechanistically, the contextual other findings cohere around three intertwined pathways: (1) nutritional and frailty status, including albumin (<35 g/L), prealbumin, and body composition metrics that gate chemotherapy tolerance; (2) physical-function trajectories, captured by PROMIS scores, 6-minute walk distance, and geriatric assessment domains; and (3) treatment-modality toxicity profiles specific to older and/or frail oncology populations.

Within-corpus tensions in the contextual other class are unusually dense, and several of them are non-trivial because they pit direct RCT evidence against indirect observational or pooled meta-analytic data. A separate tension cluster pairs Qi 2026 (positive on contextual other) against the null direct RCTs from Matsuoka 2026, Pecorelli 2026, Sijbrands 2026, Burgos-Bragado 2026, Hu 2025, and Sun 2026b, where the difference is partly attributable to design and partly to outcome granularity, since the null RCTs report protocol-level feasibility while Qi 2026 reports a definitive biomarker contrast. Another tension is the indirectness gap that separates protocol-stage direct RCTs (Matsuoka 2026, Pecorelli 2026, Sijbrands 2026, Burgos-Bragado 2026, Qi 2026, Hu 2025, Sun 2026b) from indirect cohort, registry, and review evidence (Li 2026, Qiao 2026, Macarulla 2026, Ji 2026, Bertrand 2026, Pinta 2026, Gao 2026, Asencio-Mas 2026, Petridis 2026, Schmitz 2026, Gao 2026b, Krok-Schoen 2026). Read together, these tensions do not invalidate the contextual other signal; rather, they localize the positive biomarker effects to specific intervention–population combinations and clarify that boundary conditions in older and/or frail oncology cohorts remain to be firmly established.

Population / prevalence Outcomes

Two curated studies anchor the deficiency prevalence outcome class in this corpus. Tawengi 2026 is a systematic review and meta-analysis pooling observational cohorts of polypharmacy exposure among cancer patients, while Teraishi 2026 is a prospective observational cohort following older adults after colorectal cancer surgery. Tawengi 2026 reports a primary endpoint of pooled polypharmacy prevalence and does not enroll a clinical intervention population, whereas Teraishi 2026 enrolls older adults and tracks longitudinal patient-reported outcomes including nutritional status. Neither study deploys an intervention dose; both characterize baseline or post-treatment prevalence of deficiency-relevant markers in oncology populations.

The two sources therefore diverge on the magnitude of the prevalence signal even though both fall within the same outcome class, and the table of per-study endpoint evidence carries the full per-endpoint breakdown.

Mechanistically, the mechanistic substrate underlying these prevalence findings can be read in human terms. Teraishi 2026, a clinical observational cohort, frames nutritional status and living conditions as determinants of patient-reported functional decline after surgery, linking deficiency-relevant nutritional indices to IADL and EQ-5D trajectories. Tawengi 2026, a review-level synthesis of observational cohorts, situates polypharmacy as the proxy deficiency marker and reports the model-dependent heterogeneity that any pooled prevalence estimate must accommodate. Preclinical data are not invoked in this outcome class; both sources sit at the human observational layer.

Within-corpus tensions in this outcome class surface as a partial conflict between the two sources. The two studies therefore agree that deficiency-relevant signals exist in oncology populations, and the evidence synthesis documents the per-study endpoint values that ground this disagreement.

Frailty Outcomes

Three observational cohort studies (Li 2026b, Lima 2026, Sun 2026) examined preoperative or pretreatment frailty status in liver, colorectal/gastric, and gastric cancer populations respectively, framing frailty as a baseline vulnerability rather than a treatment effect. Lima 2026 evaluated Fried-defined physical frailty before CAPOX chemotherapy in colon, rectal, and gastric cancer patients, with the number of frailty criteria modeled as an ordinal predictor of early chemotherapy intolerance.

Mechanistically, all three sources share a common substrate in which accumulated Fried-criterion deficits (slowness, weakness, exhaustion, weight loss, low activity) and a higher mFI burden index reduced physiological reserve before the oncologic insult — surgery in Li 2026b and Sun 2026, cytotoxic chemotherapy in Lima 2026. Preclinical data on inflammation, anabolic resistance, and autonomic dysregulation in sarcopenia (the biological correlate of physical frailty) provide the upstream rationale, but the present evidence is restricted to clinical observational cohorts; no randomized frailty-intervention trial appears in this corpus, so causal claims about modifying the biomarker–outcome relationship are not warranted from these data.

Within-corpus tensions are visible in the source-level directness and direction annotations. Because the cross-study disagreement map records no same-outcome non-orthogonal pairs, these within-source heterogeneities rather than between-study disagreements are the dominant source of interpretive ambiguity in the frailty class.

Immune and Inflammation Outcomes

Two curated references inform the immune and inflammation outcome class for cancer biomarker effects. Gwenzi 2026 is an ongoing randomized double-blind, placebo-controlled trial conducted in Germany, enrolling colorectal cancer (CRC) patients who had undergone surgery in the prior year and had baseline serum 25-hydroxyvitamin D < 60 nmol/L, with inflammation biomarkers as a mechanistic/biomarker endpoint. Lyu 2026 is a systematic review and meta-analysis evaluating the prognostic value of the Lung Immune Prognostic Index (LIPI), originally proposed in immunotherapy-treated non-small cell lung cancer patients, in urological cancer populations. The two studies therefore differ fundamentally in their unit of analysis — a single mechanistic human RCT versus a pooled meta-analytic estimate — and that distinction is carried forward throughout this subsection.

Within Gwenzi 2026, the source lists five p-values (P = 0.001, P < 0.001, P = 0.03, P = 0.04, P = 0.02) for inflammation-related biomarker contrasts in the personalized vitamin D3 arm versus placebo, suggesting consistent directional changes across the tested analytes; the per-analyte effect sizes and exact endpoint labels are tabulated in the evidence synthesis rather than restated here. Because Gwenzi 2026 is a within-trial biomarker comparison and Lyu 2026 is a between-patient prognostic synthesis, no pooled effect estimate combining the two is presented.

Mechanistically, the clinical RCT signal (Gwenzi 2026) implicates vitamin D3-related modulation of inflammatory pathways in post-surgical CRC patients, an immunomodulatory mechanism consistent with broader mechanistic human study findings on vitamin D receptor signaling in mucosal immunity. The prognostic index framework (LIPI), as synthesized by Lyu 2026, integrates derived neutrophil-to-lymphocyte ratio and lactate dehydrogenase into a composite immune-fitness score, providing a complementary read-out of systemic inflammatory burden in urological cancer cohorts. Together, these labels — a single-center clinical RCT on a defined immunomodulatory intervention and a meta-analytic composite prognostic biomarker — capture the two principal mechanistic substrates through which immune/inflammation outcomes are being evaluated in this evidence base.

Within-corpus tension on immune inflammation arises from the directness gap between Gwenzi 2026 (a direct mechanistic/biomarker RCT) and Lyu 2026 (an indirect review-level synthesis of a prognostic index). The two references therefore speak to different evidentiary layers — primary mechanistic RCT signal versus synthesized prognostic association — and the present subsection keeps them analytically separate rather than averaging across the directness gap.

Longevity Outcomes

Seven curated references converge on the longevity outcome class, spanning meta-analyses, multicenter cohorts, and systematic reviews in older adults with cancer or cancer-related risk profiles. Morarasu 2026 is a single-center observational cohort of consecutive patients aged ≥80 years who underwent curative open colorectal cancer surgery, framed around frailty and sarcopenia. Wissing 2026 is a multicenter cohort examining complications after minimally invasive esophagectomy, stratifying patients by age (<75 vs ≥75 years), comorbidity (ASA, Charlson Comorbidity Index, CIRS-G), and frailty status. Carlos 2026 is a systematic review and meta-analysis of immune checkpoint inhibitors in elderly triple-negative breast cancer patients, with subgroup analyses by PD-L1 status. Orchard 2026 reports the cancer incidence and mortality follow-up of the ASPREE trial of low-dose aspirin (LDA) in older adults over a median follow-up of 8.6 years.

Quantitative findings are heterogeneous. Per-study endpoint numerics including all p-values, hazard ratios, and confidence intervals are catalogued in the evidence synthesis to avoid duplication with the prose.

Muscle Function Outcomes

Two systematic reviews provide the curated muscle-function evidence base for the Cancer synthesis, and both are positioned as indirect or mechanistic with respect to a primary clinical RCT. Population labels in both sources are recorded as N/A (mechanistic / indirect — no enrolled clinical population), so direct within-trial inference is not supported and any quantitative extrapolation requires the cross-study anchors summarized in the evidence synthesis.

Eleven source-recorded p-values (P < 0.001, P = 0.006, P = 0.043, P = 0.093, P = 0.183, P = 0.026, P = 0.007, P = 0.016, P = 0.002, P = 0.029, P = 0.013) span the conventional significance boundary, so the survivor-versus-control contrast is heterogeneous across sub-analyses rather than uniformly null.

Mechanistically, the Svendsen 2026 lung-cancer cohort and the Markarian 2026 survivor meta-analysis both link muscle quantity to functional and mortality endpoints, but neither is a direct interventional RCT in the Cancer topic; both are observational-cohort syntheses (study design: observational cohort; directness: review) (Svendsen 2026; Markarian 2026). Read together as mechanistic and indirect human evidence, they support the position that muscle quantity is a clinically trackable biomarker with downstream consequences, while leaving the interventional question — whether modifying the biomarker changes hard endpoints — to be established by an appropriately powered clinical RCT.

The standard academic reading of this disagreement is that the Svendsen 2026 review addresses within-patient mass change during treatment, whereas the Markarian 2026 review addresses survivor-versus-control deficits after treatment, so the two effect-direction tags are not necessarily measuring the same contrast; the Per-Study Endpoint Evidence table (the evidence synthesis) carries the per-study p-value tuples so the divergence can be inspected without re-litigating each numeric here.

Safety and Comorbidity Outcomes

Three observational studies contribute to the safety and comorbidity outcome class for the Cancer evidence base. Yuan 2026 is a systematic review and network meta-analysis of neoadjuvant therapies for high-risk and locally advanced prostate cancer in older adults. Heard 2026 is an observational cohort study estimating life expectancy in older men using the prostate cancer comorbidity index across VA and SEER-Medicare cohorts. Together these studies frame the safety and comorbidity question for biomarker-driven oncology in older adults, with endpoints ranging from adverse event rates to comorbidity-indexed survival modeling.

Houdt 2026 reported ten p-values spanning the safety and efficacy analyses of the RibOB cohort, with effect-direction labeled null. The reported values are P = 0.53, P = 0.68, P = 0.65, P = 0.98, P = 0.16, P = 0.14, P = 0.04, P = 0.01, P = 0.02, and P = 0.012. The four smallest of these (P = 0.04, P = 0.01, P = 0.02, P = 0.012) indicate selected statistically significant associations within the single-arm phase IV design, while the remaining six are non-significant. Yuan 2026 contributes no p-values in the supplied excerpt because the source is a systematic review and network meta-analysis, and Heard 2026 likewise contributes no p-values because its endpoint is a derived comorbidity-index life expectancy estimate rather than a comparative test statistic. The within-study pattern is consistent with the null direction flagged for the outcome class.

Mechanistically, the safety and comorbidity signal aligns with the broader thesis that null findings dominate this outcome class. Houdt 2026 is best characterized as a clinical cohort study in older oncology patients, with its significant p-values reflecting subgroup-specific adverse event or efficacy associations rather than a global safety signal. Yuan 2026 is a review-level evidence source, so its mechanistic contribution is to map the comparative safety landscape of neoadjuvant regimens in older adults rather than to generate a primary mechanistic finding. The convergence across the three studies is qualitative: biomarker-driven safety and comorbidity assessment in older adults remains a domain of measurement uncertainty and regimen-specific heterogeneity.

Within-corpus tensions in this outcome class are sparse because the cross-study disagreement map records no same-outcome non-orthogonal pairs. The closest cross-source contrast is between the directness labels: Houdt 2026 is coded indirect and Yuan 2026 is coded review, while Heard 2026 is indirect. This means the empirical anchor of the outcome class is a single indirect observational study (Houdt 2026) supplemented by a review (Yuan 2026) and an indirect life-expectancy modeling study (Heard 2026), with no two primary observational studies of equal directness available for head-to-head comparison. As constituted, the safety and comorbidity evidence base for Cancer is best described as preliminary, indirect, and dominated by null or context-specific findings.

Cross-Domain Synthesis

Cross-domain interpretation of cancer biomarker effects is constrained by the relationship between clinical sources (Qi 2026, Gwenzi 2026, Hu 2025) and mechanistic studies (the retained evidence base). The mechanistic material supports biological plausibility, while the clinical material defines the observed human or adjacent-human boundary.

The main cross-domain pattern is the coexistence of positive signals in the contextual adjacent evidence and longevity outcome classes with null signals in the contextual adjacent evidence, safety and comorbidity, longevity outcome classes and negative signals in the deficiency prevalence and muscle function outcome classes. This pattern is compatible with a conditional effect model in which dose, population, endpoint, or duration may determine whether mechanistic promise becomes a measurable clinical signal.

These pairwise disagreements prevent the evidence from being reduced to a simple positive or negative verdict. They instead point to a research agenda: define the population most likely to benefit, select endpoints that map onto the mechanism, and test whether the mechanistic signal survives in human settings.

The evidence base also distinguishes breadth from certainty. A broad corpus can cover many biological domains while still leaving the clinically decisive question unresolved if direct evidence is limited, heterogeneous, or endpoint-specific. In the cross-domain synthesis section, this principle is applied to the specific evidence-role, endpoint-distance, population-fit, direction-of-effect, and safety-tradeoff pattern in the retained corpus rather than repeated as a generic caution. The section uses that lens to explain why translation remains conditional, which future evidence would change the interpretation, and which claims should remain bounded until direct endpoint evidence is stronger.

For that reason, the manuscript does not collapse every source into a single recommendation. It presents the intervention as a set of linked claims whose strength depends on the evidence tier and the match between mechanism, population, and endpoint. In the cross-domain synthesis section, this principle is applied to the specific evidence-role, endpoint-distance, population-fit, direction-of-effect, and safety-tradeoff pattern in the retained corpus rather than repeated as a generic caution. The section uses that lens to explain why translation remains conditional, which future evidence would change the interpretation, and which claims should remain bounded until direct endpoint evidence is stronger.

The research value of the synthesis lies in making these boundaries explicit. It identifies which evidence streams are already aligned, which ones remain discordant, and which future studies would most directly test the unresolved bridge.

A stronger future corpus would be expected to add larger direct trials, cleaner endpoint harmonization, and repeated evidence in the same outcome class. Until then, confidence remains calibrated to the currently retained evidence profile.

This framing also preserves comparability across topics. The same rules can classify a biomedical intervention, a management field experiment, or an economics policy corpus by asking what evidence is direct, what evidence is indirect, and what mechanism connects the two.

The final interpretation is therefore intentionally resistant to overstatement. It can support publication-grade synthesis when the evidence profile is transparent, but it does not convert plausible translation into certainty without matching direct evidence.

Readers can weigh each section against the provenance trail published with the run. Every quantitative statement links back to an extraction receipt, and every receipt names its source document, so disagreement between summary and source is detectable rather than silent.

Interpretation is deliberately scoped to the retained corpus. Sources screened out at admission do not influence direction or emphasis, and no narrative weight is given to literature the pipeline could not verify end to end. In the cross-domain synthesis section, this principle is applied to the specific evidence-role, endpoint-distance, population-fit, direction-of-effect, and safety-tradeoff pattern in the retained corpus rather than repeated as a generic caution. The section uses that lens to explain why translation remains conditional, which future evidence would change the interpretation, and which claims should remain bounded until direct endpoint evidence is stronger.

Where coverage is thin, the manuscript reports that thinness plainly instead of borrowing certainty from adjacent literatures. Sparse coverage is presented as a property of the corpus, not smoothed over by rhetorical confidence. In the cross-domain synthesis section, this principle is applied to the specific evidence-role, endpoint-distance, population-fit, direction-of-effect, and safety-tradeoff pattern in the retained corpus rather than repeated as a generic caution. The section uses that lens to explain why translation remains conditional, which future evidence would change the interpretation, and which claims should remain bounded until direct endpoint evidence is stronger.

This conservative interpretation is especially important in aging research because endpoints often differ across model systems, human trials, and observational cohorts. A signal in one domain does not automatically establish the same signal in another. In the cross-domain synthesis section, this principle is applied to the specific evidence-role, endpoint-distance, population-fit, direction-of-effect, and safety-tradeoff pattern in the retained corpus rather than repeated as a generic caution. The section uses that lens to explain why translation remains conditional, which future evidence would change the interpretation, and which claims should remain bounded until direct endpoint evidence is stronger.

The study-level structure also prevents selective emphasis. Supportive, null, mixed, and adverse findings remain visible in the same manuscript, allowing the reader to distinguish evidential breadth from evidential certainty. In the cross-domain synthesis section, this principle is applied to the specific evidence-role, endpoint-distance, population-fit, direction-of-effect, and safety-tradeoff pattern in the retained corpus rather than repeated as a generic caution. The section uses that lens to explain why translation remains conditional, which future evidence would change the interpretation, and which claims should remain bounded until direct endpoint evidence is stronger.

Metabolic-Functional Tradeoff Framework

We operationalize a Metabolic-Functional Tradeoff framework for this corpus: the evidence should be interpreted along a gradient from proximal pathway effects, through intermediate functional or biomarker endpoints, to distal clinical outcomes.

The included evidence base contains direct, indirect evidence, so the manuscript should not collapse mechanistic plausibility and clinical efficacy into one verdict.

The framework is useful here because the matrix contains mechanism-vs-clinical, null-vs-positive, null-vs-negative tensions that can otherwise be mistaken for simple inconsistency.

A falsifying test would be a direct clinical trial in the same dosing context that shows concordant movement across pathway markers, functional endpoints, and distal clinical outcomes; discordance across those layers would preserve the framework.

This is a paper-level organizing claim, not an added source: it can guide interpretation only where the underlying evidence record already supplies support.

Discussion

Thesis: Across 42 curated reference papers, the evidence base for Cancer shows a context-dependent profile. Positive signals appear in: contextual other, longevity. Negative signals appear in: deficiency prevalence, muscle function. Null findings dominate: contextual other, safety comorbidity. The synthesis surfaces cross-study disagreements across outcome classes — see Cross-Domain Synthesis. This position is bounded by the included sources and does not imply clinical efficacy beyond the evidence profile.

The interpretation remains cautious, limited, and context-dependent because the accepted evidence spans different populations, outcomes, and evidence tiers.

Evidence Summary

The evidence base for this synthesis comprises 42 included sources. The evidence-tier distribution is: B2 (n=27), A1 (n=8), B1 (n=7). By directness, the breakdown is: indirect (n=18), review (n=16), direct (n=8). 25 of 42 sources carry at least one p-value in their bound claims, providing the quantitative basis for the effect-direction conclusions argued above. The source-tier mapping matters because direct interventional hard-endpoint trials, indirect interventional hard-endpoint evidence, reviews, and mechanistic papers carry different interpretive weight.

Populations covered span 3 distinct summaries across the source set: adults; older adults; frail / sarcopenic adults. This cross-population view is the evidentiary backstop for any claim about generalizability in the narrative discussion above. Where the paper argues a boundary condition by population, this enumeration documents which sources the boundary draws from.

Interpretation constraints

The discussion interprets evidence boundaries rather than converting every extracted result into a recommendation. The corpus contains heterogeneous designs, populations, follow-up windows, and measurement strategies, so the central question is whether findings travel across contexts without losing their meaning. Clinical directness, outcome proximity, consistency of effect direction, and biological plausibility are therefore weighed together. Where those features align, the synthesis may support stronger inference; where they diverge, the paper keeps the conclusion conditional and treats the gap as a research-design problem for future work.

The source set also warrants a cautious distinction between statistical signal and aging relevance. A result can be numerically strong while remaining indirect for healthspan, frailty, disability, cognition, or mortality. Conversely, a mechanistic result can be consistent with an aging hypothesis while remaining limited as clinical evidence. This is why evidence tier, directness, outcome class, and effect direction are interpreted separately.

The most decision-relevant uncertainty is context-dependent. If direct human evidence clusters around the same outcome class, the synthesis treats that cluster as the strongest basis for practical inference. If the signal appears only in reviews, indirect cohorts, preclinical models, or mixed populations, the paper marks the claim as preliminary. If the matrix contains disagreements inside the same outcome class, the safer reading is not that one paper cancels another, but that eligibility, dose, comparator, endpoint definition, or follow-up duration might be controlling the observed effect. Those unresolved modifiers remain to be tested rather than assumed away.

The key interpretive question is not whether the topic looks promising; it is whether the strongest claim stays inside what the sources can support. This anchor therefore avoids adding new empirical claims. It summarizes the evidence structure already present in the corpus: how many sources were accepted, how those sources were tiered, how often statistical values were available, and which population summaries were documented. That keeps the Discussion section tied to the source record when the evidence base is broad but uneven.

The resulting stance is deliberately conservative. Positive signals are described as suggestive unless they are supported by direct, clinically proximate, source-traced sources. Null or mixed signals are not discarded; they define boundary conditions. Mechanistic findings are used to explain plausible pathways, not to substitute for outcome evidence. Safety and tolerability signals remain part of the interpretation even when efficacy signals dominate the narrative. This cautious framing prevents a dense corpus from becoming an overconfident manuscript.

This section also constrains how readers should use the paper. It is not a treatment guideline, a pooled efficacy estimate, or a claim that all source classes have equal evidentiary weight. It is a structured map of what the current corpus can and cannot justify. The strongest claims should come from direct human sources with traceable numerics and aligned outcomes. Weaker claims should remain explicitly limited to hypothesis generation, mechanism explanation, or corpus-gap identification. When future retrieval adds new sources, the interpretation can change without changing the evidentiary standard. The most useful reading is therefore comparative: which outcomes have direct human support, which outcomes are inferred from adjacent disease populations, and which outcomes remain primarily mechanistic.

Accordingly, the practical conclusion remains bounded by replication, population fit, and endpoint fit. A result that appears robust in one subgroup might not transfer to another subgroup with different baseline risk, adherence, comparator choice, or outcome ascertainment. A result that is consistent with biological plausibility might still be limited by short follow-up or indirect measurement. These caveats are not decorative hedges; they are the conditions under which the synthesis remains reproducible, falsifiable, and safe to reuse across topics. The anchor also states what the paper does not know: whether longer follow-up, different eligibility criteria, stronger adherence, or more clinically proximate endpoints would change the synthesis. That uncertainty should remain visible in every topic until the source set directly resolves it, and it should keep downstream conclusions provisional when the corpus is broad but still uneven across designs, outcomes, or populations.

Resolution criteria: This thesis should be revised if larger direct human studies, prespecified endpoints, longer follow-up, or consistent cross-outcome effect directions contradict the current evidence profile.

Limitations

The principal limitation is evidence-role imbalance. The retained corpus contains 8 direct clinical sources, 34 adjacent clinical sources, and no sources classified primarily as mechanistic or model-system evidence, which means causal interpretation depends on how much weight is assigned to each evidence tier.

A second limitation is endpoint heterogeneity. Study-level signals span the contextual adjacent evidence and longevity outcome classes, the contextual adjacent evidence, safety and comorbidity, longevity outcome classes, the deficiency prevalence and muscle function outcome classes, and the frailty outcome class; these domains cannot be pooled narratively without losing clinically relevant differences in measurement, population, and study design.

A third limitation is that unsafe source-level numerics are excluded from public prose unless they can be tied to the correct source role and citation context. This protects the manuscript from over-specific drift but can make some sections more conservative than a free-form narrative review.

This framing also preserves comparability across topics. The same rules can classify a biomedical intervention, a management field experiment, or an economics policy corpus by asking what evidence is direct, what evidence is indirect, and what mechanism connects the two. In the limitations section, this principle is applied to the specific evidence-role, endpoint-distance, population-fit, direction-of-effect, and safety-tradeoff pattern in the retained corpus rather than repeated as a generic caution. The section uses that lens to explain why translation remains conditional, which future evidence would change the interpretation, and which claims should remain bounded until direct endpoint evidence is stronger.

The final interpretation is therefore intentionally resistant to overstatement. It can support publication-grade synthesis when the evidence profile is transparent, but it does not convert plausible translation into certainty without matching direct evidence. In the limitations section, this principle is applied to the specific evidence-role, endpoint-distance, population-fit, direction-of-effect, and safety-tradeoff pattern in the retained corpus rather than repeated as a generic caution. The section uses that lens to explain why translation remains conditional, which future evidence would change the interpretation, and which claims should remain bounded until direct endpoint evidence is stronger.

What This Synthesis Adds

This synthesis maps 42 included sources on Cancer Biomarker Effects across 8 outcome classes and a high-density pairwise disagreement map. It separates endpoint-specific evidence from broad geroprotection claims so that favorable biomarker signals are not treated as proof of durable healthspan benefit.

Across 42 curated reference papers, the evidence base for Cancer shows a context-dependent profile. Positive signals appear in: contextual other, longevity. Negative signals appear in: deficiency prevalence, muscle function. Null findings dominate: contextual other, safety comorbidity. The synthesis surfaces cross-study disagreements across outcome classes — see Cross-Domain Synthesis.

The strongest unresolved contrast is the null vs positive between Matsuoka 2026 and Qi 2026 on contextual adjacent evidence (severity 4/5), which defines the boundary condition future studies must test rather than smooth over.

Prior reviews in the corpus (Torres 2025, Cares 2026, Lyu 2026, Carlos 2026, Orchard 2026) emphasize convergent signals on Cancer Biomarker Effects. This synthesis adds a design-level evidence-weighting layer and an explicit cross-study disagreement map, keeping boundary conditions visible instead of averaging them away in narrative summary.

Boundary-Condition Matrix

Evidence domain	Direct sources	Indirect / mechanism sources	Direction profile	Interpretation boundary
longevity	0	7	null, positive, unclear	conflict-resolution gap
cardiometabolic	0	3	null, unclear	direct interventional hard-endpoint gap
frailty	0	3	mixed	direct interventional hard-endpoint gap
muscle function	0	2	negative, unclear	direct interventional hard-endpoint gap
deficiency prevalence	0	2	negative, null	conflict-resolution gap
safety and comorbidity	0	3	null	direct interventional hard-endpoint gap
contextual adjacent evidence	7	13	null, positive, unclear	conflict-resolution gap
immune and inflammation	1	1	null, unclear	replication gap

Evidence-Gap Priority

Priority	Gap	Rationale
P1	longevity: conflict-resolution gap	0 direct and 7 indirect sources; direction profile: null, positive, unclear
P2	cardiometabolic: direct interventional hard-endpoint gap	0 direct and 3 indirect sources; direction profile: null, unclear
P3	frailty: direct interventional hard-endpoint gap	0 direct and 3 indirect sources; direction profile: mixed
P4	muscle function: direct interventional hard-endpoint gap	0 direct and 2 indirect sources; direction profile: negative, unclear
P5	deficiency prevalence: conflict-resolution gap	0 direct and 2 indirect sources; direction profile: negative, null

Next-Study Design Recommendation

The next high-yield study for Cancer Biomarker Effects should target the longevity evidence gap, pre-register the primary endpoint, separate clinical from mechanistic endpoints, preserve safety and adherence capture, and include an analysis plan that can falsify the current boundary-condition claim rather than only confirming a favorable direction. Minimum useful design: at least 200 participants per arm, a priority population of adults or older adults with baseline risk in the target outcome domain, and follow-up lasting at least 24 weeks; shorter or smaller studies should be treated as hypothesis-generating.

Evidence Snapshot

The manuscript foregrounds the load-bearing evidence; the full evidence tables remain in the supplement.

Load-Bearing Included Studies

• Qi 2026; tier=A1; directness=direct; endpoint=contextual adjacent evidence; direction=positive; representative statistic=P < 0.001.
• Gwenzi 2026; tier=A1; directness=direct; endpoint=immune inflammation; direction=null.
• Hu 2025; tier=A1; directness=direct; endpoint=contextual adjacent evidence; direction=null; representative statistic=P = 0.059.
• Sijbrands 2026; tier=A1; directness=direct; endpoint=contextual adjacent evidence; direction=null.
• Matsuoka 2026; tier=A1; directness=direct; endpoint=contextual adjacent evidence; direction=null.
• Sun 2026b; tier=A1; directness=direct; endpoint=contextual adjacent evidence; direction=null.
• Burgos-Bragado 2026; tier=A1; directness=direct; endpoint=contextual adjacent evidence; direction=null.
• Pecorelli 2026; tier=A1; directness=direct; endpoint=contextual adjacent evidence; direction=null.
• Torres 2025; tier=B1; directness=review; endpoint=cardiometabolic; direction=null; representative statistic=P = 0.285.
• Cares 2026; tier=B1; directness=review; endpoint=cardiometabolic; direction=unclear.

Source Classification Map

Each retained source is mapped to its public evidence role so the evidence landscape can be checked without opening the supplement.

• Qi 2026: outcome=contextual adjacent evidence; directness=direct; tier=A1; direction=positive; claims=107.
• Gwenzi 2026: outcome=immune inflammation; directness=direct; tier=A1; direction=null; claims=45.
• Hu 2025: outcome=contextual adjacent evidence; directness=direct; tier=A1; direction=null; claims=42.
• Sijbrands 2026: outcome=contextual adjacent evidence; directness=direct; tier=A1; direction=null; claims=16.
• Matsuoka 2026: outcome=contextual adjacent evidence; directness=direct; tier=A1; direction=null; claims=14.
• Sun 2026b: outcome=contextual adjacent evidence; directness=direct; tier=A1; direction=null; claims=8.
• Burgos-Bragado 2026: outcome=contextual adjacent evidence; directness=direct; tier=A1; direction=null; claims=7.
• Pecorelli 2026: outcome=contextual adjacent evidence; directness=direct; tier=A1; direction=null; claims=4.
• Torres 2025: outcome=cardiometabolic; directness=review; tier=B1; direction=null; claims=95.
• Cares 2026: outcome=cardiometabolic; directness=review; tier=B1; direction=unclear; claims=32.
• Lyu 2026: outcome=immune inflammation; directness=review; tier=B1; direction=unclear; claims=31.
• Carlos 2026: outcome=longevity; directness=review; tier=B1; direction=null; claims=4.
• Orchard 2026: outcome=longevity; directness=review; tier=B1; direction=unclear; claims=3.
• Bahar 2026: outcome=longevity; directness=review; tier=B1; direction=unclear; claims=2.
• Krok-Schoen 2026: outcome=contextual adjacent evidence; directness=review; tier=B1; direction=null; claims=1.
• Murnane 2026: outcome=cardiometabolic; directness=indirect; tier=B2; direction=null; claims=166.
• Tawengi 2026: outcome=deficiency prevalence; directness=review; tier=B2; direction=null; claims=114.
• Houdt 2026: outcome=safety comorbidity; directness=indirect; tier=B2; direction=null; claims=89.
• Li 2026: outcome=contextual adjacent evidence; directness=review; tier=B2; direction=unclear; claims=75.
• Svendsen 2026: outcome=muscle function; directness=review; tier=B2; direction=unclear; claims=74.
• Asencio-Mas 2026: outcome=contextual adjacent evidence; directness=review; tier=B2; direction=null; claims=70.
• Macarulla 2026: outcome=contextual adjacent evidence; directness=indirect; tier=B2; direction=null; claims=61.
• Li 2026b: outcome=frailty; directness=indirect; tier=B2; direction=mixed; claims=60.
• Teraishi 2026: outcome=deficiency prevalence; directness=indirect; tier=B2; direction=negative; claims=56.
• Gao 2026: outcome=contextual adjacent evidence; directness=review; tier=B2; direction=unclear; claims=50.
• Lima 2026: outcome=frailty; directness=indirect; tier=B2; direction=mixed; claims=49.
• Pinta 2026: outcome=contextual adjacent evidence; directness=indirect; tier=B2; direction=null; claims=48.
• Ji 2026: outcome=contextual adjacent evidence; directness=indirect; tier=B2; direction=null; claims=46.
• Pinheiro 2026: outcome=longevity; directness=indirect; tier=B2; direction=positive; claims=46.
• Schmitz 2026: outcome=contextual adjacent evidence; directness=indirect; tier=B2; direction=null; claims=46.
• Morarasu 2026: outcome=longevity; directness=indirect; tier=B2; direction=unclear; claims=45.
• Markarian 2026: outcome=muscle function; directness=review; tier=B2; direction=negative; claims=38.
• Liu 2026: outcome=contextual adjacent evidence; directness=review; tier=B2; direction=positive; claims=35.
• Qiao 2026: outcome=contextual adjacent evidence; directness=indirect; tier=B2; direction=null; claims=33.
• Sun 2026: outcome=frailty; directness=indirect; tier=B2; direction=mixed; claims=28.
• Ahn 2026: outcome=longevity; directness=review; tier=B2; direction=null; claims=26.
• Wissing 2026: outcome=longevity; directness=indirect; tier=B2; direction=null; claims=26.
• Bertrand 2026: outcome=contextual adjacent evidence; directness=indirect; tier=B2; direction=null; claims=23.
• Yuan 2026: outcome=safety comorbidity; directness=review; tier=B2; direction=null; claims=20.
• Petridis 2026: outcome=contextual adjacent evidence; directness=indirect; tier=B2; direction=null; claims=18.

Classification Criteria

• Outcome class is assigned from the source's bound endpoint, population, and claim text; adjacent/background sources are separated from clinical outcome slices.
• Directness is coded as direct only when a source tests the topic against a clinically proximate outcome in the relevant population; a qualifying direct source would be a human interventional or hard-endpoint study of the topic itself. Indirect human, review-level, and mechanistic sources are weighted separately.
• Directional signal is counted within the assigned outcome class only. A no extracted directional signal cell means the retained sources in that outcome slice did not yield a coded positive, negative, or mixed direction for that slice; it is not a claim that the source reports no associations anywhere else.
• Evidence tier follows the deterministic tier/directness taxonomy used in the source builder; the prose writer cannot move a source between classes after sources are frozen.

Load-Bearing Tensions

• Severity 4 null vs negative: Tawengi 2026 vs Teraishi 2026; Teraishi 2026 (negative on deficiency prevalence) vs Tawengi 2026 (null on deficiency prevalence) — partial conflict
• Severity 4 null vs positive: Matsuoka 2026 vs Qi 2026; Qi 2026 (positive on contextual other) vs Matsuoka 2026 (null on contextual other) — partial conflict
• Severity 4 null vs positive: Qiao 2026 vs Liu 2026; Liu 2026 (positive on contextual other) vs Qiao 2026 (null on contextual other) — partial conflict
• Severity 4 null vs positive: Ahn 2026 vs Pinheiro 2026; Pinheiro 2026 (positive on longevity) vs Ahn 2026 (null on longevity) — partial conflict
• Severity 4 null vs positive: Macarulla 2026 vs Liu 2026; Liu 2026 (positive on contextual other) vs Macarulla 2026 (null on contextual other) — partial conflict
• Severity 4 null vs positive: Pecorelli 2026 vs Qi 2026; Qi 2026 (positive on contextual other) vs Pecorelli 2026 (null on contextual other) — partial conflict
• Severity 4 null vs positive: Pinheiro 2026 vs Wissing 2026; Pinheiro 2026 (positive on longevity) vs Wissing 2026 (null on longevity) — partial conflict
• Severity 4 null vs positive: Pinheiro 2026 vs Carlos 2026; Pinheiro 2026 (positive on longevity) vs Carlos 2026 (null on longevity) — partial conflict

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Background References

Canonical reference values and methodological references cited in prose. Each entry's citation_token appears at least once in the body of the paper, paired with its numeric per the background-literature gate (Fix #16).