Review: Site-specific Cancer Burden in China and the United States, 1990–2023: A Pre-registered Decomposition of Between-country Differences into Modifiable Risk Factors · CheckPaper
Review by CheckPaper · Reviewed 10 Nov 2026
Site-specific Cancer Burden in China and the United States, 1990–2023: A Pre-registered Decomposition of Between-country Differences into Modifiable Risk Factors
The numbers are right: every GBD, GLOBOCAN and IARC input and every decomposition table reproduces from the public sources. But the main pre-registration deviation (nine risk clusters cut to four) rests on a data-gap claim that the named source contradicts, and the title and plain-language summary claim more than the accounting analysis supports.
Soundness
2/4
Presentation
3/4
Contribution
2/4
Confidence
4/5
✓ 13 confirmed✕ 6 discrepancy
Summary
The paper compares age-standardized cancer incidence, mortality and DALY rates for seven sites (stomach, liver, oesophagus, lung, colorectum, breast, prostate) in China and the United States from 1990 to 2023, using GBD 2023 as re-published by Our World in Data (OWID), with GLOBOCAN 2022/2024 and IARC Cancer Causes estimates for sex-specific rates, infection-attributable incidence and a cross-source check.
Its main methodological contribution is to split the China minus US difference in age-standardized mortality (ASMR) for each site into components for GBD risk clusters (tobacco, dietary risks, high BMI, air pollution, a residual 'other GBD-assessed risks') and a component not attributed to GBD-assessed risks. It does this by Shapley allocation of the joint attributable fraction (Eqs 2–6) and adds a Kitagawa split of each component into a fraction part and a rate part (Eq 7). Headline findings: tobacco (5.2) and air pollution (4.2) together exceed the 7.2 per 100 000 lung gap; tobacco accounts for 48% of the oesophageal gap; 75% of the stomach gap and most of the breast and prostate gaps are not attributed to GBD risks.
The study is presented as pre-registered (plan frozen and hashed on 9 Nov 2026), with 16 deviations and 12 data gaps logged. All three primary analyses were run in reduced form.
Strengths
Fully reproducible numbers from public data
Tables 1–13, 15–17, 19; checks 01–08, 12, 14, 19
We re-downloaded the GBD 2023 series from the OWID indicator API and the GLOBOCAN/IARC values from GCO, then rebuilt the tables independently. Every printed cell we compared matched within half a unit of the last digit: 96/96 rate cells (Tables 1–3), 48/48 EAPCs with CIs (Table 4), 56/56 count cells (Table 5), 36/36 joint shares (Table 6), 30/30 Shapley components (Table 7), 150/150 Kitagawa cells (Table 8), 111/111 change cells (Table 9), 56/56 liver aetiology cells (Table 11), 102/102 GLOBOCAN 2024 cells (Table 12), 192/192 IARC Cancer Causes values (Table 13) and 69/69 allocation-rule cells (Table 16). This level of agreement is unusual and is the paper's strongest asset.
Exact, well-specified gap decomposition
Sec 3.4, Eqs (2)–(7); Sec 4.3; Tables 7–8
Eqs (2)–(7) define a decomposition whose components sum exactly to the observed gap. We confirmed this for all seven sites and all years. Negative joint fractions are kept rather than truncated, and the Kitagawa split separates differences in attributable share from differences in base rate (e.g. lung air pollution 3.59 share part vs 0.58 rate part). This moves beyond the side-by-side PAF tables of earlier China–US comparisons.
Rule dependence reported openly
Sec 3.6 SA2/SA4; Sec 4.7.2; Tables 16–17
SA2 (Table 16) reports proportional and sequential allocations next to Shapley. SA4 (Table 17) prints the raw unallocated cluster differences. Together they let a reader see that, for lung, the tobacco/air-pollution split depends on the rule (tobacco 4.2–7.3, air pollution 2.0–4.9), while their sum exceeds the 7.19 gap under all three rules (9.33, 9.18, 9.29; check 04).
Careful handling of age standards and cross-source comparison
Sec 3.2.2; Sec 3.6 SA1; Table 15
Rates on the GBD world standard and the Segi standard are never subtracted from each other. Cross-source comparisons use ratios only, under an explicit concordance rule (ratio of ratios in [0.67, 1.5], same side of 1). We could apply the rule mechanically to the printed values, and it reproduces all seven labels (check 14).
Transparent deviation and status ledger
Sec 3.8 (D1–D16, G1–G12); Table 21
Sec 3.8 lists 16 deviations and 12 data gaps. Table 21 gives the final status of every pre-specified analysis, and these statuses agree with the Sec 3.8 summary (0 mismatches, check 10). The post hoc check X5 is labelled as such. Few observational papers are this explicit about what was and was not run.
Weaknesses
Main pre-registration deviation (D8) rests on a data gap the named source contradicts
major · Sec 3.8 D8 and G6 (p.6); Sec 3.4 before Eq (6); Table 7; Table 21 (P2, P3)
Both primary decompositions (P2, P3) and every analysis built on them were reduced from the nine pre-registered clusters to four plus an 'other' residual. The justification is G6: per-site percentages were 'available only for all risks, tobacco, dietary risks (five sites), high BMI (three sites) and air pollution (lung)'. The source named in D1, the OWID gbd_risk_cancer dataset (version 2026-02-07, so available before the stated freeze), contradicts this. It publishes dietary risks for six sites (including lung and prostate), high alcohol use for six sites, high fasting plasma glucose for four, low physical activity for two, drug use (liver), and occupational and other environmental risks (lung), all on both age bases (checks 10, 11).
The omitted clusters matter. Alcohol accounts for 22.1% (China) and 23.2% (US) of 2023 oesophageal deaths; occupational risks account for 9.2% and 19.6% of lung deaths. When we include them, the lung 'other GBD-assessed risks' component (−1.68) becomes almost entirely occupational risk (−1.60), and the oesophageal 'other' component (0.90) becomes alcohol (1.15). The headline tobacco and air-pollution numbers move little. Still, the paper's most-cited departure from its plan is not justified as stated, and the 'other' rows of Table 7 hide identifiable risks.
Fix: run the decomposition with the pre-registered clusters, or explain why the available series were excluded, and correct G6/D8.
Pre-registration cannot be verified, and its label is stronger than what was done
major · Title; Sec 3.1 (p.3); Sec 3.8; Table 21 (p.27); Code and data availability and plain-language summary (p.29)
The plan is identified only by a SHA-256 hash, with no public registry entry (OSF, PROSPERO, AsPredicted) and no third-party timestamp. The frozen plan, deviation log and code ('experiment/analysis/', 'experiment/code/') were not supplied, so neither the freeze nor 'written before any estimate was extracted' can be checked. The PDF was created 2 h 44 min after the stated freeze (16:18:24 → 19:02:46 UTC, 9 Nov 2026), so all data access, analysis and writing fell in that window. All three primary analyses ran in reduced form, and only S9 ran as planned (Table 21).
For a system whose prior knowledge may already include GBD and GLOBOCAN China–US figures, 'Before looking at any numbers, we wrote down and locked our analysis plan' (plain-language summary) does not mean the analysis was blind.
Fix: deposit the plan with a public timestamp, publish the package, and qualify the 'pre-registered' label in the title and abstract.
Questions for the authors
OWID's gbd_risk_cancer dataset (2026-02-07) publishes per-site alcohol, high FPG, low physical activity, occupational, other environmental, drug use and lung/prostate dietary fractions on both age bases. Which series did your download scripts query, and why were these not found (G6, D8, X5)?
Can you deposit the frozen plan, the deviation log with timestamps and the data manifest publicly, so the hash and the statement that the plan was 'written before any estimate was extracted' can be verified?
With all nine pre-registered clusters included, how do Tables 7–9 change, in particular the lung and oesophageal 'other' components and the liver decomposition?
Can GBD 2023 uncertainty intervals (GHDx) be obtained, and which decomposition components keep their sign within them?
Why were high-BMI and air-pollution fractions taken on the age-standardized basis and the others on the all-ages basis (D9), given that both bases exist for all series?
Verification
We ran 19 scripted checks. Using the OWID indicator API (GBD 2023, dataset ihme_gbd/2026-02-07), the IARC GCO Cancer Today API, the IARC Cancer Causes apps and an archived GLOBOCAN 2022 fact sheet, we independently rebuilt the inputs and re-implemented the Shapley, proportional, sequential and Kitagawa decompositions. Every numerical table we rebuilt reproduces within rounding: Tables 1–13, 15–17 and 19, several hundred cells in total. The analysis is therefore arithmetically sound, and its data provenance (GBD 2023 via OWID; GLOBOCAN 2024; IARC Cancer Causes) is genuine. Six checks found discrepancies. Two matter for the requester's questions. (i) The data-gap statements used to justify the main pre-registration deviation (G6/D8, X5) and G3 are contradicted by the named source, which publishes the omitted clusters and both age bases (checks 10, 11, 15). (ii) The title overstates what was decomposed (check 16). The remaining discrepancies are minor: a rounding mismatch (check 09), a wrong ordering statement (check 15) and causal wording in the Discussion and plain-language summary (check 17). The pre-registration itself, the code and the deviation log could not be examined.
[16] de Martel C, et al. Global burden of cancer attributable to infections in 2018: a worldwide incidence analysis. Lancet Glob Health 8(2):e180-e190, 2020.
Cited for claims it does not directly support. At L1704 ('the IARC H. pylori-attributable incidence was more than three times higher in China [16, 18]') the 'more than three times' figure is the 2024 IARC Cancer Causes ratio from Table 10 (13.20 vs 2.99 male, 5.71 vs 2.53 female). [16] reports 2018 estimates, [18] is a prevalence meta-analysis, and the actual source [26] is not cited there. At L170, [16] is also listed as a source for the '2024' infection-attributable estimates. Cite [26] (with version and access date) for the 2024 values, and keep [16] only for methods and background.
[25] Force LM, Kocarnik JM, May ML, et al. The global, regional, and national burden of cancer, 1990-2023, with forecasts to 2050: a systematic analysis for the Global Burden of Disease Study 2023. Lancet 406(10512):1565-1586, 2025.
Could not be verified bibliographically. Crossref bibliographic, Lancet-ISSN/year-filtered and full-citation queries returned no record with this title, volume or pages; the closest matches were GBD 2023 conference abstracts in JCO. The same Lancet issue 406(10512) contains a linked comment, 'Global cancer burden: progress, projections, and challenges' (pp.1536-1537, doi 10.1016/s0140-6736(25)01570-3), so the article very probably exists. No DOI is given. Add the DOI so the primary GBD 2023 source can be checked.
[53] Our World in Data. Cancer: data series republished from the Global Burden of Disease study of the Institute for Health Metrics and Evaluation. Global Change Data Lab, Oxford, 2026.
Incomplete for the paper's primary data source. There is no URL, dataset/version identifier or access date. The GBD values in Tables 1-11 match the OWID re-publication dataset ihme_gbd/2026-02-07 (checks 01-08, 12), but the paper never names this version. OWID re-publications are revised, so without the version the decomposition cannot be reproduced exactly.
[26] International Agency for Research on Cancer. Global Cancer Observatory: Cancer Causes (infections, alcohol and excess body weight subsites). IARC, Lyon, 2026.
Web resource without URL, data version or access date. The values used (Tables 10, 11, 13) are reproducible from gco.iarc.who.int/causes (check 19), but the alcohol and excess-body-weight modules are 2022-based while the infection module is 2024-based, and the single 2026 citation does not distinguish them.
[54] Ervik M, Laversanne M, Lam F, et al. Global Cancer Observatory: Cancer Today (2024 estimates, version 1.0). IARC, Lyon, 2026.
Suggestions
Re-run P2/P3 with the pre-registered clusters that OWID publishes per site (alcohol, high FPG, low physical activity, occupational, other environmental, drug use, full dietary coverage). Report the four-cluster version as a sensitivity analysis and correct G6, D8 and X5.
Use one age basis consistently: age-standardized fractions applied to ASMR, which are available for every site. Drop or reframe X5 accordingly.
Register the plan publicly with a third-party timestamp (e.g. OSF). Release the analysis package with the paper, and soften 'pre-registered' in the title given that all three primary analyses were run in reduced form.
Retitle to reflect that mortality, not 'burden', is decomposed into GBD risk-attributable and unattributed components, and add the liver result to the abstract.
Obtain GBD 2023 UIs from GHDx and propagate them by Monte Carlo as planned. At minimum, flag components whose magnitude is below plausible uncertainty.
Report the lung tobacco/air-pollution split as a range across allocation rules (4.2–7.3 and 2.0–4.9) in the abstract, alongside the robust statement that their sum exceeds the gap.
Replace causal verbs in Sec 5.1 and the plain-language summary ('underlie', 'caused by', 'a likely part of that is') with accounting language consistent with Sec 3.4.1.
Give the OWID dataset version (ihme_gbd/2026-02-07), URLs and access dates for [26], [53] and [54]. Identify the archived GLOBOCAN 2022 US sheet, add a DOI for [25], and cite [26] instead of [16]/[18] for the 2024 IARC values.
Fix the minor errors: the crude-vs-ASMR ordering sentence in Sec 4.1, the NMSC definition of the Table 5 total row, 20.3 vs 20.2, 29.5 vs 29.4, and the scale (absolute vs ratio) of the 'larger among males' statement.
Ethics and integrity
The requester states that the study was produced end to end by an AI system (IterSCI), and the paper lists IterSCI as sole author. Readers should know this, together with the facts that no human author takes responsibility and that the pre-registration cannot be independently verified (see weaknesses). We found no text in the paper that tries to instruct reviewers, and no fabricated data or references: every value we checked matches its public source, and all references except [25] resolved, with [25] probably real. Data use is consistent with the providers' terms: the IHME series are not redistributed. The requester's notes were treated as context only.
Scope of this review
Only the PDF was supplied. The research package cited on p.29 (code in experiment/code/, data manifest, frozen analysis plan, its hash target and the timestamped deviation log in experiment/analysis/) was not available. We therefore could not rerun the authors' code, verify the plan hash or freeze time, or check that deviations were logged before the affected analyses. All GBD comparisons use the OWID re-publication (point estimates only) as accessed in November 2026; GBD uncertainty intervals (GHDx, registration required) were not examined. The GLOBOCAN 2022 US values were checked against an Internet Archive snapshot. The IARC infection values in Table 10 were checked for internal consistency only, not against the IARC source.
Interpretation rule and hedged discussion of the not-attributed component
Sec 3.4.1; Sec 5.3; Sec 5.4
Sec 3.4.1 defines the components as accounting quantities relative to the TMREL counterfactual. Sec 5.3 does not equate 'not attributed' with 'non-modifiable', and calls the H. pylori link 'consistent with, but does not demonstrate'. Most of the text keeps to this rule (check 17).
The title promises a decomposition of 'Cancer Burden' 'into Modifiable Risk Factors'. In fact, only ASMR is decomposed (the DALY decomposition S2 was not assessable). The named modifiable clusters account for only 46.3% of the summed absolute site gaps (19.6 of 42.3 per 100 000, check 16). The not-attributed component is 75.1% of the stomach gap, 142.3% of liver, 61.7% of breast and 93.5% of prostate. The abstract reports the stomach, breast and prostate cases but omits the liver result (not attributed 142.3%, 'other' −53.3%).
Fix: retitle to something like 'Decomposition of between-country mortality differences into GBD risk-attributable and unattributed components', and add the liver result to the abstract.
No uncertainty for any decomposition component
major · Sec 3.7; D11; Tables 7–9, 16
All GBD-based results are point estimates (Sec 3.7, D11). Some components are reported to two significant figures although they are far smaller than plausible GBD uncertainty, e.g. colorectal components on a −1.2 gap, liver high BMI −0.29, lung not attributed −0.83. The lung split itself varies by a factor of 1.7–2.5 across allocation rules. GBD 2023 UIs are available from GHDx to registered users, and the plan's Monte Carlo intervals relied on them.
Fix: obtain the GBD UIs, or at least propagate a stated relative uncertainty, and report which components keep their sign.
D9 says high-BMI and air-pollution fractions are age-standardized and the other fractions all-ages. We confirmed this mix: Table 7 reproduces 30/30 only on that mixed basis, against 26/30 all-ages and 16/30 age-standardized. Sec 3.6 X5, however, says per-site percentages 'are published for all ages rather than on the age-standardized basis', and X5 checks only the total-cancer series. Both bases are published for every site. On a consistent age-standardized basis the largest change is small (lung tobacco 5.17 → 4.83, 4.6% of the gap; check 11), so conclusions survive, but the method description is inconsistent and the check was unnecessary.
Fix: use a single basis throughout (age-standardized fractions on ASMR) and correct X5/D9.
Causal wording creeps into the Discussion and plain-language summary
Sec 5.1 says tobacco and air pollution 'underlie much of the present lung cancer contrast' (p.27). The plain-language summary says 'A likely part of that is a common stomach infection, Helicobacter pylori' and 'cancers caused by this infection'. No stomach-specific H. pylori fraction was derived (D13; X1 not assessable), and the IARC figure is an all-site agent total for a different measure, year and standard. This goes beyond the interpretation rule of Sec 3.4.1 and the hedged Sec 5.3.
Fix: use 'is accounted for by the attributable components of' and 'consistent with'.
Further data-gap statements contradicted by the source
minor · Sec 3.8 G3; Sec 4.1; Table 5
G3 says GBD incidence and DALY counts were not available. OWID publishes both (e.g. stomach incidence China 2023 575,712, US 28,163; DALYs 8,875,657 / 362,364; check 15). This affects S7 and the count-based summaries.
Incorrect ordering statement and undeclared change of 'total' definition
minor · Sec 4.1 (p.9); Table 5 (p.10)
Sec 4.1 says the 2023 crude rates (China 178.6 < US 206.8) are 'the reverse of the ordering of age-standardized rates'. However, 2023 ASMR is also lower in China (112.4 vs 114.2, Table 1), so the ordering is the same; the reversal holds only in 1990. In addition, the Table 5 'Total cancers' row (2,554,679 / 693,795 deaths) is GBD total cancers including NMSC, whereas Tables 1–4 and the abstract exclude NMSC (excl.-NMSC deaths 2,539,824 / 688,288; check 15).
Sign-flip artefact of the rescaling when J < 0
minor · Sec 3.4 Eq (4); Table 7 footnote (prostate)
For prostate in China the joint fraction is −0.6% while the tobacco fraction is positive, so the rescaling in Eq (4) gives a tobacco allocation of the opposite sign (Table 7, footnote). The effect is small, but it should be explained in the text rather than only in a footnote, or avoided by allocating the negative and positive parts separately.
Lung gap change: 'grew by 20.3' (Sec 4.4) vs Table 9 20.2 (exact 20.2468; check 09). Infection-attributable ASR: abstract 29.5, Table 10 29.4, text 29.45 (check 12). The text says the lung ASMR difference rose 'to 7.19 in 2023', but it peaked at 7.77 in 2022 (check 06). 'Mainly from H. pylori and hepatitis B virus' (abstract) holds for China but not for the US, where HPV (7.71) is the largest agent. 'Differences larger among males' holds on the absolute scale only; for oesophagus the female ratio is larger (2.84 vs 2.47; check 13). The seven-site 'death-weighted mean' of Sec 4.2 combines crude death weights with age-standardized analyses and is dominated by China's lung deaths (the unweighted means are 42.0% vs 49.4%; check 08).
Citations of web data sources lack versions, and some claims cite the wrong source
The primary data source [53] (OWID) has no URL, dataset version or access date. The values match OWID dataset ihme_gbd/2026-02-07, which the paper never names. [26] and [54] also lack URLs and versions, and the archived GLOBOCAN 2022 US fact sheet (D3) is not identified. At L170 and L1704, [16] (2018 estimates) and [18] are cited for 2024 IARC values that come from [26]. [25], the GBD 2023 cancer paper, could not be resolved on Crossref and has no DOI.
Pre-registration: plan frozen 9 Nov 2026 16:18:24 UTC with SHA-256 hash, written before any estimate was extracted; 16 deviations and 12 data gaps; Table 21 status of each analysis matches the Sec 3.8 summary; the deviations were forced by data availability.
Internally consistent: hash 'fa2b8a6f0fcecef4'+'9eb3216fbe2df737ffd88ca4b51aa3f9527173ffa7903ece' is 64 hex chars (valid SHA-256 format); D1-D16 = 16 and G1-G12 = 12 as stated; Table 21 statuses agree with the Sec 3.8 sentence (0 mismatches): 1 as planned (S9), 17 reduced (+S6 item 1), 4 not assessable (S2, SA3, UI, X1), plus X5 post hoc. Not verifiable: the frozen plan, its hash target and the deviation log are not supplied (p.29 points to an 'experiment/analysis/' folder that was not provided), so neither the freeze nor 'written before any ... estimate was extracted' can be checked; PDF CreationDate is Mon Nov 9 19:02:46 2026 UTC, 2 h 44 min after the stated freeze, so all extraction, analysis and writing would have occurred in that window. Discrepancy: the data-gap justification of the main deviation D8 (both primary analyses P2/P3 reduced from nine pre-registered clusters to four plus 'other') is contradicted by the named source. G6 says per-site percentages were available only for all risks, tobacco, dietary risks (five sites), high BMI (three sites) and air pollution (lung); OWID gbd_risk_cancer publishes dietary risks for six of the seven sites (incl. lung), plus high alcohol use (6 sites), high fasting plasma glucose (4), low physical activity (2), drug use (liver), occupational risks (lung), other environmental risks (lung); all 39 (cluster, site) pairs are published on both all-ages and age-standardized bases, contradicting X5 ('published for all ages rather than on the age-standardized basis'), which also contradicts D9 in the same paper. Check 11 shows the effect on results is moderate (e.g. lung 'other' -1.681 becomes mostly occupational -1.595). The plain-language claim 'Before looking at any numbers, we wrote down and locked our analysis plan' cannot be verified.
Parsed paper.txt and pdfinfo metadata; computed the freeze-to-PDF interval; validated the hash format; enumerated D/G items; tabulated Table 21 statuses against the Sec 3.8 sentence; compared the G6/X5 data-gap statements with the OWID gbd_risk_cancer index (the source named in D1).
Age-basis approximation (D9, X5): per-site attributable percentages are published only for all ages, and applying all-age fractions to age-standardized rates changes shares by at most 1.3 percentage points (Table 19, all cancers); alcohol, high FPG, low physical activity, occupational and environmental risks are 'not published per site in the series used' (Sec 3.4, D8).
The 1.3-point figure for all cancers is correct (check 03), and the quantitative impact of the age basis on Table 7 is small: on a consistent age-standardized basis the largest 2023 change is lung tobacco 5.166 -> 4.834 (-0.33, 4.6% of the 7.19 gap); 1990 lung tobacco -9.296 -> -9.722. Per-site all-ages vs age-standardized differences reach 1.63 points (oesophagus alcohol, China 1990) and 1.31 points for a series the paper uses (prostate joint share, China 1990: -2.12 vs -3.43). However, the stated data limitation is factually wrong: OWID publishes per-site shares on BOTH bases for all seven sites, and also publishes alcohol (stomach, liver, oesophagus, colorectum, breast, prostate), high FPG (liver, lung, colorectum, breast), low physical activity (colorectum, breast), occupational and other environmental risks (lung), drug use (liver) and dietary risks for prostate. These are material: in 2023 alcohol is 22.1% (China) / 23.2% (US) of oesophageal deaths and occupational risks 9.2% / 19.6% of lung deaths. Including them (all-ages basis) turns the lung 'other GBD-assessed risks' component -1.681 into occupational -1.595 plus residual -0.035, and the oesophageal 'other' 0.895 into alcohol 1.151 with residual 0.000. Prostate diet (China -8.0%, US -0.2%) is also omitted. D9 (BMI and air pollution taken age-standardized) also contradicts Sec 3.6 X5 ('published for all ages rather than on the age-standardized basis').
From the OWID gbd_risk_cancer dataset (the series the paper says it used) listed every per-site death-share series available and downloaded both age bases. (1) Compared all-ages vs age-standardized shares for every site/risk/country/year. (2) Re-ran the 1990 and 2023 decompositions on a consistent age-standardized basis. (3) Re-ran 2023 with every additional per-site cluster OWID publishes.
IARC infection-attributable incidence (Table 10, Sec 4.5, abstract): 29.45/29.4/29.5 vs 15.83 per 100 000; agent rates and case counts; 'eighteen-fold' HBV and 'more than three times' H. pylori differences; GBD liver aetiology split (Table 11).
Table 10: ASR differences 18/18 within combined rounding; male+female=both cases 12/12; implied total new cancer cases are mutually consistent across the six agent rows for every country-sex cell (e.g. China both sexes [5,066,081, 5,099,967], US both [1,923,647, 1,929,697]); 5-agent sums are below 'All infections' by 774-2,920 cases (other agents), as expected. Ratios: HBV 9.15/0.50 = 18.3 ('eighteen-fold', Sec 5.2) and H. pylori 9.32/2.74 = 3.40 ('more than three times') confirmed. Text values (Sec 4.5/4.6) agree with the table within rounding. Minor inconsistency: the abstract gives 29.5 while Table 10 gives 29.4 for the same quantity (text 29.45, an exact rounding tie; HBV 9.15 is rounded up to 9.2 in the same table, so the table's rounding is not uniform). Table 11: 56/56 cells match OWID within half a unit of the last printed digit (e.g. 2023 HBV 4.7415 vs 0.7493, gap +3.9922 = 250.26% of a +1.5953 gap; paper 4.7/0.75/4.0/250.3; 1990 HBV share 81.59% vs paper 81.6). The IARC source values themselves could not be checked against IARC (see check 19).
Table 10 internal arithmetic (ASR differences, male+female=both for cases, implied all-cancer case totals from each agent's case count and % share, agent sum vs all infections); text/abstract vs table rounding; ratio recomputation. Table 11 recomputed from the OWID GBD 2023 re-publication (gbd_incidence age-standardized rates, indicators 1181709/10/14/16/18/19).
Sex-specific GLOBOCAN 2024 differences for stomach, liver, oesophagus and lung are larger among males (abstract; Table 12); age-band contributions (Table 14): 96% of the male stomach and 93% of the male lung ASMR difference at ages >=50.
Table 12 ratio cells 34/34 consistent with printed rates; Sec 4.6 two-decimal values 28/28 consistent with Table 12. Absolute ASMR differences are larger in males for all four sites (stomach +10.37 vs +3.60; liver +12.01 vs +2.79; oesophagus +5.54 vs +1.53; lung +19.89 vs -0.39), so the abstract statement holds as written. On the ratio scale it does not hold for oesophagus (ASMR ratio male 2.47 < female 2.84; ASIR 2.17 < 2.49); the paper does not say which scale, and the absolute male excess partly reflects higher male base rates in both countries. Table 14: band sums = 'Reconstructed' 34/34 and 'Published difference' = Table 12 China-US 34/34 within rounding; largest reconstruction gaps (70+ open group) are prostate ASIR -71.1 vs -71.7 and breast/prostate ASMR 0.4. 96%: (4.64+5.36)/10.42 = 96.0% of band sum (96.4% of the published 10.37); 93%: (10.01+8.38)/19.74 = 93.2% (92.5% of the published 19.89); both round to the stated values.
Recomputed Table 12 ratios from printed rates (interval arithmetic over rounding); compared male vs female ASMR differences on the absolute and ratio scales using the Sec 4.6 two-decimal rates; checked Table 14 band sums against 'Reconstructed' and 'Published difference' against Table 12; recomputed the 96%/93% shares.
SA1 source concordance (Table 15): liver and colorectum source-dependent and the other five sites consistent under the rule 'same side of 1 and ratio of ratios in [0.67, 1.5]'; abstract: 'Liver and colorectal ratios depended on the data source'.
Ratio-of-ratios cells 14/14 consistent with the printed ratios; labels reproduced 7/7. GBD columns 21/21 match OWID within 0.005 (e.g. stomach ASMR ratio 6.2385 vs 6.24; liver 1.5141 vs 1.51; colorectum 0.9294 vs 0.93). Fragility: liver incidence ratio of ratios 1.30/1.93 = 0.6736 sits on the 0.67 band edge (rounding interval 0.669-0.678), but liver is source-dependent through mortality anyway (0.59). Colorectum is labelled source-dependent only because its mortality ratios straddle 1 (GBD 0.93 vs GLOBOCAN 1.07; ratio of ratios 0.87, well inside the band), so the abstract's 'colorectal ratios depended on the data source' rests on two ratios within 7% of 1 compared across different metrics (GBD age-standardized rate vs GLOBOCAN cumulative risk 0-74, D14; GBD breast/prostate on whole-population denominators). GLOBOCAN 2022 columns were not checked against the source (see check 19).
Applied the stated rule mechanically to the printed Table 15 ratios (with rounding intervals); recomputed the GBD 2022 ASIR, ASMR and crude mortality ratios from the OWID GBD 2023 re-publication (cached rate series and gbd_cause_deaths all-ages rate indicators 1165299-1165550).
Counts and crude rates (Table 5; Sec 4.1): 2,554,679 cancer deaths in China and 693,795 in the US in 2023, 763,723 from lung cancer in China; crude rates 178.6 vs 206.8, 'the reverse of the ordering of age-standardized rates'; incidence and DALY counts not available from the source (G3).
Site rows: 56/56 cells match OWID (deaths within 1, rates within 0.05; e.g. lung China 2023 763,722.7 vs 763,723). Implied populations are consistent within each country-year (2023: China [1430.6, 1430.8] M, US [335.4, 335.6] M). The 'Total cancers' row (2,554,679 / 693,795; 178.6 / 206.8) matches GBD total cancers INCLUDING non-melanoma skin cancer (OWID 2,554,678.8 / 693,794.6; 178.568 / 206.847), whereas Tables 1-4 and the abstract use all cancers EXCLUDING NMSC (excl.-NMSC deaths 2,539,823.5 / 688,288.1; crude 177.530 / 205.205); the total definition switches between tables without a label (minor). Discrepancy: Sec 4.1 says the crude rates (China 178.6 < US 206.8) are 'the reverse of the ordering of age-standardized rates', but 2023 ASMR is also lower in China (112.4 vs 114.2, Table 1), so the ordering is the same; a reversal holds only in 1990 (ASMR 197.7 > 169.3, crude 144.9 < 212.8). G3 is contradicted by the named source: OWID publishes all-ages incidence counts (indicator 1178061, stomach: China 2023 575,712.4, US 28,163.2) and DALY counts (indicator 1157040, stomach: 8,875,657 / 362,363.5).
Implied population = deaths / crude rate for each row with rounding intervals; all 64 Table 5 cells compared with OWID GBD 2023 gbd_cause_deaths all-ages number and rate indicators; ordering claim compared with Table 1 ASMR; G3 tested by fetching OWID incidence and DALY count indicators.
Abstract and title match the results: every abstract number is supported by a table; the title promises a pre-registered decomposition of between-country differences in 'cancer burden' into modifiable risk factors.
19/20 abstract numbers match their tables exactly (e.g. 112.4/114.2, stomach 16.5 vs 2.8, lung -13.1 to +7.2, tobacco 5.2 and air pollution 4.2, oesophageal tobacco 48.0%, stomach not attributed 75.1%); the qualitative statements (lower colorectal/breast/prostate mortality in China; males larger; liver and colorectal source-dependent) are supported (checks 13, 14). Minor mismatch: abstract 'IARC infection-attributable incidence was 29.5' vs Table 10 '29.4' (text 29.45). Title scope: named modifiable clusters account for +23.4% (stomach), +10.9% (liver), +44.8% (oesophagus), +134.9% (lung), -132.4% (colorectum, gap -1.217), -23.3% (breast) and -4.9% (prostate) of the signed gap; summed over sites |named| / sum|gap| = 19.605/42.349 = 46.3%; not-attributed parts are 75.1% stomach, 142.3% liver, 61.7% breast, 93.5% prostate of |gap|. The title's 'Cancer Burden' and 'Decomposition ... into Modifiable Risk Factors' overstate what was done: only ASMR is decomposed (ASDR decomposition S2 not assessable), into four clusters plus residual components that are not risk factors, and the abstract itself reports that most of the stomach, breast and prostate gaps lie outside the decomposed risks. 'Pre-registered' is qualified by all three primary analyses being run in reduced form (check 10). The abstract omits the liver result (not-attributed 142.3% of gap, 'other' -53.3%).
Mapped all 20 abstract numbers to table values (and earlier checks 02, 03, 06, 12-14); from the full-precision reproduction of Table 7 (check 03 module, D9 basis, OWID GBD 2023) computed the share of each site's 2023 ASMR gap assigned to the four named clusters (tobacco, diet, high BMI, air pollution) vs 'other GBD-assessed risks' vs 'not attributed'.
Causal language is restricted to accounting/association, per the interpretation rule (Sec 3.4.1: components 'are accounting quantities and are not interpreted as the effect of changing exposure') and Limitations ('they describe association').
Mostly adhered to: 170 lines use attribut*/contribut* in the PAF accounting sense; design and limitations state 'no causal effect was estimated' (line 141) and 'they describe association and are not estimates of what would change if exposure changed' (line 1732); Sec 5.3 says the stomach result is 'consistent with, but does not demonstrate, a role for H. pylori'; 'because'/'reflects' hits in Sec 4.1/5.1 (e.g. line 401, line 1676) describe arithmetic of rates, not causes. Exceptions (minor, wording only): (1) Sec 5.1 line 1683 'consistent with the view that tobacco and air pollution underlie much of the present lung cancer contrast' uses a causal verb, though hedged; (2) Abstract Conclusions line 27 'contrasts align with tobacco and air pollution' is acceptable association language; (3) the plain-language summary (lines 1786-1789) goes further than the analysis: 'A likely part of that is a common stomach infection, Helicobacter pylori' for the not-attributed stomach gap, although no stomach-specific H. pylori fraction was derived (X1 and S6 item 2 not assessable, D13) and the IARC figure is an all-site agent total; it also says that 'the difference matched smoking and air pollution' and 'Most of the higher breast and prostate cancer rates ... were also not explained by the measured risks; things like screening, child-bearing patterns and treatment may play a part'. The summary does add 'These numbers describe patterns. They do not prove that changing one risk would change cancer rates' (line 1791). The title's 'into Modifiable Risk Factors' frames the accounting components as risk-factor effects.
Regex scan of work/paper.txt (body, references excluded) for causal and explanatory vocabulary (caus*, underl*, explain*, driv*, due to, because, reflect*, likely, effect*, align*, consistent with, account for, ...), listing each hit with line, page and section; each non-accounting hit was classified by reading the sentence.
References exist and match their citations (56 entries, several dated 2026, e.g. [2] GLOBOCAN 2024 in CA Cancer J Clin 76(4):e70090).
51/56 citations contain >=80% of the Crossref best-match title tokens. Of these, [12] matched a 2021 JCO abstract, but a DOI lookup (10.1016/S0140-6736(22)01438-6) returns Tran et al., 'The global burden of cancer attributable to risk factors, 2010–19', Lancet 400(10352):563–591, 2022, exactly as cited. [13] (containment 0.65) was confirmed by DOI 10.1016/S0140-6736(24)00933-4: Brauer et al., Lancet 403(10440):2162–2203, 2024, as cited. All 2026-dated entries checked resolve with matching title, journal, volume and pages: [2] Sung et al. CA 76(4) doi 10.3322/caac.70090; [7] Chin Med J Pulm Crit Care Med 4(3):267–277; [30] Discover Oncology 17(1); [31] iScience 29(5):115718. [36] resolves to Eur J Cancer Prev 35(2):151–159 with Crossref issue date 2025 against the cited 2026 (online-first vs issue year; one-year offsets of the same kind occur for [17], [19], [37], [45], [51]). Not resolved: [25] (Force et al., GBD 2023 cancer, Lancet 406(10512):1565–1586, 2025). Crossref returns no such article, although the same issue 406(10512) contains the linked comment 'Global cancer burden: progress, projections, and challenges' (pp.1536–1537, doi 10.1016/s0140-6736(25)01570-3), so the article is plausible but unverified here. [26], [53] and [54] are web resources that Crossref cannot index; their matches (1991, 2023, 1969 items) are irrelevant. Support issue: at L1704 the 2024 IARC H. pylori ratio ('more than three times', Table 10) is attributed to [16] (de Martel et al., 2018 estimates) and [18] (prevalence meta-analysis) rather than to [26], the Cancer Causes source of the 2024 values; at L170 [16] is likewise listed as a source for '2024' infection estimates. No fabricated reference was found.
tools/check_refs.py (Crossref bibliographic query per entry) summarised in 18_refs.py: title-token containment of the best match in the full citation (threshold 0.8), then targeted Crossref queries (title, Lancet ISSN + year filter, full citation) and DOI lookups for entries whose automatic match was a different work.
GLOBOCAN 2024 / IARC Cancer Causes values (Tables 12, 13, 15) are as published.
Table 15: 21/21 GLOBOCAN cells reproduced, e.g. stomach incidence ratio 1.7/0.47 = 3.617 vs paper 3.62, mortality 1.1/0.18 = 6.111 vs 6.11, crude mortality ratio 5.626 vs 5.63, breast crude 0.428 (female populations) vs 0.43. Every cell also agrees to the printed 2 d.p., not only within the looser tolerance. Table 12: 102/102 cells match the GLOBOCAN 2024 API, e.g. lung male ASMR China 37.70 vs 37.7, breast ASMR ratio 5.66/12.17 = 0.465 vs 0.47, colorectum both ASIR 20.65/27.04 = 0.764 vs 0.76. Table 13: 192/192 values match IARC Cancer Causes, including all 95% UIs for alcohol (e.g. China oesophagus male 45.4 (24.8-63.3), ASR 6.00) and excess-body-weight shares/ASRs (e.g. US postmenopausal breast 14.37%, ASR 25.61 vs 14.4, 25.6). The source has no interval fields for excess body weight, which confirms the caption's 'no published interval'. Provenance note: the Table 12 caption says no uncertainty intervals are published for these rates; the 2024 API publishes UIs for counts only (e.g. China lung incidence 1175915, UI 1167026-1184872), so the caption is accurate for rates.
19_globocan_provenance.py. (A) Downloaded the GLOBOCAN 2022 v1.1 population fact sheets: China from IARC GCO (still live) and the United States from the Internet Archive snapshot 20250530032810, because the live US sheet is now GLOBOCAN 2024, which matches D3. Recomputed the Table 15 GLOBOCAN columns from cumulative risk (0-74) and from deaths/population. (B) Queried the GCO Cancer Today API used by the website (gco-api.iarc.fr/api/globocan/v3/2024, China = 156, US = 840) for ASIR/ASMR by sex and recomputed every Table 12 cell. (C) Extracted the country tables embedded in the IARC Cancer Causes alcohol and obesity web apps (2022 reference) and compared every Table 13 value. Tolerance: half a unit in the last printed digit; ratios ±0.005 (Table 15 cumulative-risk ratios ±(0.005+6%) because the sheets print cumulative risk to 2 s.f.).
Shapley decomposition of the 2023 China-US ASMR gap (Table 7; abstract): lung tobacco 5.2 and air pollution 4.2 (sum exceeds the 7.2 gap), oesophagus tobacco 3.5 (48.0%), stomach not-attributed 10.3 (75.1%), liver not-attributed 3.0 (142.3%), breast -3.4 (-61.7%), prostate -4.9 (-93.5%).
With full-precision inputs all 30 components, all 60 country allocated rates and all 30 '% of |gap|' values reproduce within rounding: stomach NA 10.3403 (75.09%, paper 10.3/75.1%); oesophagus tobacco 3.5277 (48.01%, paper 3.5/48.0%); liver NA 2.9826 (142.32%, paper 3.0/142.3%); breast NA -3.4086 (-61.73%, paper -3.4/-61.7%); prostate NA -4.8659 (-93.54%, paper -4.9/-93.5%); lung tobacco 5.1656 (71.81%) + air pollution 4.1667 (57.92%) = 9.332 > gap 7.194, as stated. Arithmetic of the method is therefore correct. Reproducibility caveat: from the paper's printed inputs alone (Table 17 is given to two significant figures) only 21/30 components are recovered within 3% (e.g. stomach other 0.1413 vs printed 0.21; lung other -1.6156 vs -1.7; breast diet -0.6026 vs -0.64), so a reader cannot reproduce Table 7 from the paper without re-downloading the data, and no code is released.
Independent re-implementation of Eqs (3), (4), (6) (exact Shapley over all orderings of published clusters + 'other'). (a) Inputs taken from the paper's own printed Tables 1, 6 and 17 (p = attributable/ASMR). (b) Full-precision inputs from OWID (check 03, D9 age basis). Compared components, country allocated rates and the '% of |gap|' column; tolerance half a unit of the last printed digit (0.05 for percentages).
GBD 2023 input data are as reported: ASMR, ASIR and ASDR for the seven sites and all cancers excl. NMSC, China and US, 1990 and 2023 (Tables 1-3), from the Our World in Data republication of GBD 2023.
All 96 cells match within 0.05. Examples: stomach ASMR China 2023 paper 16.5; lung ASMR China 2023 32.9 and US 25.7; total ASIR US 1990 paper 428.0 vs OWID 427.9759; stomach ASDR China 1990 paper 1314.7 vs OWID 1314.6912; prostate ASIR US 2023 47.2 vs 47.1819. Mismatches 0, missing 0. The data provenance claim (GBD 2023 via OWID) holds for Tables 1-3.
Independently downloaded the 24 age-standardized rate series (deaths, incidence, DALYs; 7 sites + total excl. NMSC) from the OWID indicator API (dataset ihme_gbd 2026-02-07 = GBD 2023; China entity 171, US 13) and compared each of the 96 printed cells (4 per row) with tolerance half a unit of the last printed digit (0.05).
GBD 2023 joint and cluster-specific attributable death shares (Table 6, Table 17, Table 19) are as published, and the Table 7 decomposition reproduces from independently downloaded inputs.
Table 6: 36/36 joint shares match OWID all-ages values (e.g. liver China 2023 paper 41.3 vs 41.269; prostate China 2023 -0.6 vs -0.601). Table 19: 20/20 match (e.g. all risks China 50.1/48.8 vs 50.143/48.847). Table 7: 30/30 components reproduced within rounding only when high-BMI and air-pollution fractions are taken on the age-standardized basis and all other fractions (and J) on the all-ages basis, as stated in D9 (all-ages throughout: 26/30; age-standardized throughout: 16/30). Reproduced values: stomach not-attributed 10.3403 (paper 10.3), tobacco 2.2615 (2.3); lung tobacco 5.1656 (5.2), air pollution 4.1667 (4.2), sum 9.332 vs gap 7.194; oesophagus tobacco 3.5277 (3.5); liver not-attributed 2.9826 (3.0); prostate not-attributed -4.8659 (-4.9). Components sum exactly to the gap for all seven sites. Table 17: 29/32 cells match with all-ages fractions; the three misses are the high-BMI cells (colorectum China 0.661 vs 0.65, breast China 0.191 vs 0.18, breast US 0.965 vs 0.87), which match on the age-standardized basis, i.e. the same mixed basis. Side finding (see check 11): OWID publishes per-site fractions on BOTH age bases for every site, and additional clusters (alcohol for 6 sites, high FPG, low physical activity, occupational and other environmental risks, drug use, prostate diet), contradicting D8 and the X5 rationale in Sec 3.6; D9 ('age-standardized for high BMI and air pollution') also contradicts Sec 3.6 X5 ('published for all ages rather than on the age-standardized basis').
Downloaded every per-site 'share of deaths attributed to <risk>' series (both sexes, both age bases) from OWID gbd_risk_cancer (GBD 2023) and the ASMR series of check 02; compared Table 6 (36 cells), Table 19 (20 cells, excl. alcohol) and Table 17 (p x ASMR, 32 cells) within half a unit of the last printed digit; re-implemented Eqs (3), (4), (6) (Shapley over published clusters + 'other') and ran the 2023 decomposition under three age-basis combinations.
Allocation-rule sensitivity (SA2, Table 16): lung tobacco ranges 4.2-7.3 and air pollution 2.0-4.9 across Shapley, proportional and sequential (tobacco, BMI, diet, air pollution, other) rules; other sites change little.
69/69 cells reproduced. Lung: Shapley tobacco 5.166 / air 4.167; proportional 4.243 / 4.933; sequential 7.311 / 1.982 (paper 5.2/4.2, 4.2/4.9, 7.3/2.0). Tobacco + air pollution exceeds the 7.194 gap under all three rules (9.332, 9.177, 9.293). The split between tobacco and air pollution for lung is strongly rule-dependent (tobacco 4.2 to 7.3, a factor of 1.7; air pollution 2.0 to 4.9, a factor of 2.5), whereas their sum is stable; the abstract quotes only the Shapley values. Liver high BMI also varies by a factor of ~2 (-0.29 to -0.56).
Implemented the proportional rule (phi* proportional to p_k including p_O, rescaled to J) and the sequential rule (marginal increments of Eq 3 in the order tobacco, BMI, diet, air pollution, other) with full-precision OWID inputs on the D9 basis (check 03); compared all 69 non-trivial Table 16 cells within half a unit of the last printed digit.
Trends: percent change 1990-2023 and EAPC with 95% CI of the log-linear fit (Table 4), e.g. stomach ASMR China -67.5%, EAPC -3.85 (-4.11 to -3.58); liver ASIR US +127.9%, EAPC +2.54 (2.34 to 2.74).
48/48 percent changes and 48/48 EAPCs with both CI bounds reproduced (e.g. stomach ASMR China -67.5 / -3.85 (-4.11 to -3.58); liver ASIR US 127.9 / 2.54 (2.34 to 2.74); all-cancer ASMR China -43.2 / -2.06). The apparently contradictory lung ASIR China row (+1.0% change but EAPC -0.13) is genuine: the series rose to 39.24 in 2000, fell to 33.24 in 2020 and rebounded to 37.28 in 2023, so the endpoint change and the log-linear trend disagree; the 2020 dip-and-rebound is worth a sentence in the paper, which instead reports only the 2020 minima of the ratios.
Recomputed percent change and EAPC = 100(e^b - 1) with a t(32) 95% CI on the OLS slope of ln(rate) on year, using the 34 annual (1990-2023) OWID values of each of the 48 series (8 sites x 3 measures x 2 countries) downloaded in check 02. Tolerance 0.05 for % change, 0.006 for EAPC and CI bounds.
Table arithmetic for levels: differences and ratios in Tables 1-3; abstract: stomach and oesophageal differences narrowed by about 70%, lung difference changed from -13.1 to +7.2; Sec 4.1 annual-series values (lung ASMR difference first positive in 2016 at 1.86, 1.54 in 2020, 7.19 in 2023; lung ASIR differences -0.04/0.34/-0.51/-1.39 in 2017-2020 and 5.50 in 2023; 2020 minima of the stomach, liver, oesophagus ASMR ratios 5.45, 1.37, 2.74).
96/96 differences and ratios match. ASMR gap narrowing 1990-2023: stomach 45.54 -> 13.77 (69.8%), oesophagus 24.70 -> 7.35 (70.2%), liver 8.11 -> 2.10 (74.2%), so 'about 70%' holds. Lung ASMR difference: 2015 -0.68, 2016 1.86, 2020 1.54, 2023 7.19, positive every year from 2016. Lung ASIR difference: 2017 -0.04, 2018 0.34, 2019 -0.51, 2020 -1.39, 2021 2.87, 2023 5.50. Minimum ASMR ratios all fall in 2020: stomach 5.448, liver 1.375, oesophagus 2.740 (paper 5.45, 1.37, 2.74). Minor wording point: the lung ASMR difference peaked at 7.77 in 2022, so 'rising to 7.19 in 2023' omits a 2022-2023 decline.
Recomputed every Difference and Ratio cell of Tables 1-3 (96 values) and the annual statements from the full-precision OWID annual series (check 02). Tolerance 0.05 for differences, 0.005 for ratios.
Kitagawa split of each 2023 gap component (Table 8, Eq 7), e.g. stomach tobacco share part 0.40 + rate part 1.86; oesophagus tobacco 0.53/3.00; lung tobacco 1.36/3.80; lung air pollution 3.59/0.58; liver other -2.01/0.90; breast not-attributed 0.17/-3.58.
150/150 Table 8 cells and all six text values reproduced; the two parts sum exactly to each component. E.g. stomach tobacco shares 15.6/11.4%, fraction part 0.404, rate part 1.857 (text 0.40/1.86); lung air pollution shares 14.2/1.9%, parts 3.587/0.579 (text 3.59/0.58); liver other 24.1/61.4%, parts -2.012/0.895; breast not-attributed parts 0.171/-3.580.
Computed each country's component share (allocated rate / ASMR) from the full-precision reproduction of Table 7 (check 03) and applied Eq (7); compared all 150 Table 8 cells (2 shares, component, two parts for 30 components) and the six text values. Tolerance half a unit of the last printed digit.
Joint attributable share and attributed/not-attributed ASMR (Table 6, Eq 2): e.g. stomach China 2023 24.0% -> attributed 4.0 and not attributed 12.6; seven-site death-weighted mean 56.9% vs 56.5% (2023) and 49.4% vs 58.7% (1990).
56/56 attributed and not-attributed cells match (e.g. stomach China 2023 attributed 4.0, not attributed 12.6). Death-weighted means: 1990 China 49.392 / US 58.748, 2023 China 56.890 / US 56.547 (paper 49.4/58.7, 56.9/56.5). Interpretive note: the weights are all-age death counts, so the near-equal 2023 'seven sites combined' share is dominated by China's 763,723 lung deaths (lung J 81.1%); the unweighted site mean is 42.0% (China) vs 49.4% (US). Combined with age-standardized rates elsewhere, this summary mixes crude and age-standardized bases, which Sec 4.2 does not point out.
Recomputed J*R and (1-J)*R for 7 sites x 2 countries x 2 years from full-precision OWID values (56 cells) and the death-weighted mean of the seven all-age joint fractions with Table 5 death counts as weights, using both printed and full-precision J. Tolerance half a unit of the last printed digit.
Change in components 1990-2023 (Table 9, Sec 4.4): stomach gap -31.8, of which not-attributed -24.8 (35.15 -> 10.34), tobacco -4.13 (6.39 -> 2.26), diet -2.25; oesophagus -17.35; liver -6.02; lung gap +20.3 in text vs +20.2 in Table 9, tobacco -9.30 -> 5.17 (+14.46), air pollution 5.27 -> 4.17; annual lung tobacco -5.52 (2000), -1.46 (2010), 2.45 (2019).
All 111 Table 9 cells reproduce, as do 18 of 19 text values (stomach NA 35.145 -> 10.340, change -24.81; stomach tobacco 6.392 -> 2.261 (-4.13); lung tobacco -9.296 -> 5.166 (+14.46); air pollution 5.268 -> 4.167; oesophagus -17.35; liver -6.02; annual lung tobacco 2000/2010/2019 = -5.52/-1.46/2.45). One minor inconsistency: Sec 4.4 says the lung difference 'grew by 20.3', but the exact change is 20.2468 (Table 9: 20.2); 20.3 is what you get by subtracting the rounded endpoints (7.2 - (-13.1)). This does not affect any conclusion.
Re-ran the decomposition for 1990, 2000, 2010, 2019 and 2023 with full-precision OWID inputs on the D9 basis (check 03); compared all 111 Table 9 cells and 19 text values within half a unit of the last printed digit.
No URL or access date. In addition, deviation D3 (L308) says the GLOBOCAN 2022 United States fact sheet was read from an archived copy, because the live sheet has been replaced by GLOBOCAN 2024. No reference or footnote identifies that archive, e.g. Internet Archive snapshot 20250530032810, which reproduces the Table 15 values (check 19).
[42] Arnold M, Pandeya N, Byrnes G, et al. Global burden of cancer attributable to high body-mass index in 2012: a population-based study. Lancet Oncol 16(1):36-46, 2015.
Minor support mismatch. At L170, [42] (2012 estimates) and [41] (alcohol, 2020 estimates) are cited as sources for the IARC alcohol and excess-body-weight fractions 'for 2022'. The 2022 values in Table 13 come from the current Cancer Causes database [26]. [41] and [42] describe the methods, not the numbers reported.