Evaluaci\'on del Cambio en la Musculatura y Adiposidad y su Relaci\'on con la Recurrencia del Carcinoma de Cabeza y Cuello mediante PET/CT y MRI

Iker Malaina; Virginia del Campo

REVIEW 5 major objections 5 minor 6 references

Evaluaci\'on del Cambio en la Musculatura y Adiposidad y su Relaci\'on con la Recurrencia del Carcinoma de Cabeza y Cuello mediante PET/CT y MRI

T0 review · 5 major / 5 minor · reviewed 2026-08-12 · deepseek-v4-flash

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Pith's one-line read The paper claims that post-radiotherapy gains in body fat predict higher recurrence and death in head and neck cancer patients.

desk verdict A preliminary reanalysis of a public HNSCC dataset with a plausible but not novel association, undermined by missing sample definition, omitted baseline confounders, and an imaging claim with no imaging analysis. read the letter →

arxiv 2411.16264 v1 pith:L2RVSTEF submitted 2024-11-25 q-bio.TO

Virginia del Campo , Iker Malaina This is my paper · ORCID

classification q-bio.TO

keywords headandnecksquamouscellcarcinomabodycompositionadiposityindexskeletalmusclelossradiotherapytumorrecurrencesurvivalanalysisPET/CTMRIfollow-up

verification ladder T0 review T1 audit T2 compute T3 formal

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The reading

The paper sets out to establish that body-composition changes after radiotherapy predict which head and neck squamous cell carcinoma (HNSCC) patients relapse and die. Using the HNSCC-MDA cohort, it reports that an increase in the L3 adiposity index after radiotherapy is significantly associated with higher recurrence and mortality, after adjusting for age, sex, and tumor stage. The combined muscle-and-adipose analysis finds that patients with muscle loss plus adipose gain have the lowest survival probabilities and the highest recurrence risk. The authors explicitly call the work preliminary, so the value of the claim is as a testable prognostic signal rather than a settled clinical rule.

What carries the argument

The central machinery is the change in the L3 adiposity index, measured at the third lumbar vertebra before and after radiotherapy, together with the binary change in skeletal muscle status at the same level. The argument runs through two statistical engines: multivariate logistic regression for recurrence and Cox proportional hazards models for mortality and group-wise recurrence risk. The combined analysis uses a four-group classification of muscle and adipose change, with muscle gain plus adipose loss as the reference group; the hazard coefficients for the remaining groups translate each body-composition trajectory into a recurrence-risk estimate. That set-up is what lets the paper turn routine L3-level measurements into prognostic comparisons.

What would settle it

A direct test would be to obtain the full HNSCC-MDA cohort with explicit inclusion and exclusion criteria and missing-data handling, reproduce the L3 measurements, and re-run the same multivariable logistic and Cox regressions; if the adiposity-change coefficient falls to near zero or changes sign when any missing scans are excluded, the central association fails.

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Extended reading notes

Core claim

The central discovery, stated in the abstract, is that an increase in the adiposity index post-radiotherapy is significantly associated with higher recurrence and mortality rates in HNSCC. In the multivariate logistic regression, the coefficient for change in adiposity index is 0.045 ($p < 0.001$); in the Cox proportional hazards model it is 0.038 ($p < 0.001$), both adjusted for age, sex, and tumor stage. When skeletal muscle and adipose changes are combined into four groups, patients with muscle loss and adipose gain show the lowest survival probabilities and the highest recurrence risk, with a Cox group coefficient of 1.567 ($p < 0.001$) relative to the muscle-gain with adipose-loss reference group. The paper frames itself as a preliminary analysis and calls for larger, longer-term studies to confirm the findings.

Load-bearing premise

The load-bearing assumption is that the HNSCC-MDA cohort provides complete, accurately measured L3 muscle and adiposity values before and after radiotherapy, along with reliable recurrence and survival follow-up for a well-defined analytic sample.

Editorial extensions

If this is right

If the claim is correct, follow-up imaging that already covers the L3 level can flag rising adiposity as a warning sign during post-radiotherapy surveillance.
Patients who lose muscle while gaining fat would be the group most deserving of nutritional or rehabilitative interventions after treatment.
The reported independence from age, sex, and stage IVA suggests body-composition change adds prognostic information beyond standard staging.
Stable or reduced adiposity after radiotherapy would identify a lower-risk trajectory, informing how intensely a patient is monitored.
Body-composition monitoring could be formalized as part of routine response assessment after radiotherapy for HNSCC.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

Editorial inference: the paper's design is associative, so the ordering of adiposity gain and recurrence is untested; a longitudinal analysis of the same cohort could check whether fat gain precedes or follows recurrence.
Editorial inference: imaging modality is discussed but not included as a covariate, so a natural extension is to test whether PET/CT, MRI, or CT follow-up changes the measured association.
Editorial inference: because all results come from one public cohort, an independent replication with explicitly reported inclusion criteria and missing-data handling would be the decisive next validation.
Editorial inference: the clinical payoff, if confirmed, is that body composition becomes an early image-derived warning signal available before recurrence is visible on conventional scans; that would need prospective testing.

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Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Desk Editor's Note

read the letter

Quick take: this is a preliminary reanalysis of the public HNSCC-MDA cohort that finds post-RT adiposity gain associates with worse recurrence and survival. The association is plausible and internally consistent, but the manuscript is not yet a complete paper: no sample size, no baseline table, no survival curves, and no imaging analysis despite the abstract promising one.

What's actually new: not much. The main result echoes the same group's 2016 JAMA Oncology paper (ref [2], also the dataset source). The four-group muscle/adipose categorization is a mild reformulation, not a new biomarker. The authors do deserve credit for two things: they are upfront that this is preliminary, and they cite the prior study rather than ignoring it.

The soft spots are real and load-bearing. First, the abstract emphasizes PET/CT, MRI, and CT, but the methods and results sections contain zero imaging analysis. That's a mismatch between claims and content. Second, the core logistic and Cox models adjust only for age, sex, and stage IVA. Baseline L3 muscle and adiposity indices are never included. Since body-composition change is correlated with baseline, the coefficient on change may simply capture baseline cachexia or nutritional risk. The stress-test note is right. Third, there is no reported sample size, event count, or missing-data handling, so we can't even check for sparse-data bias. The paper also omits KM curves and proportional-hazards diagnostics, which the methods imply should be there.

The citation pattern is fine: they cite Grossberg 2016 and the dataset. No sign of self-citation inflation or invented entities.

Bottom line: this reads like a work-in-progress report, not a submittable manuscript. The clinical question is fine, but the value added over ref [2] is small and the reporting gaps are too big. I would not send this to peer review in its current form. I'd desk reject with an invitation to resubmit once the authors state the analytic sample, include baseline composition in the models, and either present the imaging analysis or remove that claim from the abstract. The four-group survival result could be a useful addition if properly framed.

Referee Report

5 major / 5 minor

Summary. This manuscript analyzes the HNSCC-MDA public dataset to examine whether changes in the L3 adiposity index and skeletal muscle status after radiotherapy are associated with recurrence and survival in head and neck squamous cell carcinoma. Using multivariable logistic regression, Cox proportional-hazards models, and Kaplan-Meier analyses, the authors report that an increase in the adiposity index after radiotherapy is significantly associated with higher recurrence and mortality, and that patients with muscle loss and adipose gain have the lowest survival and the highest recurrence risk. The Discussion and Conclusions label the work as preliminary and call for larger confirmatory studies.

Significance. The clinical question is relevant: body-composition changes are potentially modifiable and could inform follow-up in HNSCC. The modeling strategy on a public dataset is transparent, and the regression tables are internally consistent. However, the current manuscript cannot support the abstract's central claim because essential design information is missing and the main analyses omit baseline body-composition covariates. If the authors supply the missing reporting and the association survives adjustment for baseline composition, the finding would be a useful preliminary prognostic signal; as written, the contribution is an unverifiable preliminary analysis.

major comments (5)

[Section 2.1] The Methods state that data come from HNSCC-MDA but do not report the number of patients included, the number of recurrence and death events, inclusion/exclusion criteria, the version of the dataset, or how missing scans or measurements were handled. Without these, the coefficients in Sections 3.1.1, 3.1.3, and 3.2.2 cannot be checked for overfitting or sparse-data bias, and the reader cannot know the analytic sample. This is a load-bearing reporting gap.
[Sections 3.1.1 and 3.1.3] The logistic and Cox models for adiposity change adjust only for age, sex, and stage IVA. Baseline L3 adiposity index and baseline L3 skeletal-muscle index, both available in the data and both prognostic in prior HNSCC work (ref. [2]), are not included. Since change from baseline is biologically and mathematically correlated with baseline level, the reported coefficient on adiposity change may be capturing baseline nutritional risk or reverse causation rather than an independent effect of adiposity gain. The authors should present models that include baseline composition, or at least a stratified analysis, and should report the correlation between baseline values and change scores.
[Sections 3.1.2 and 3.2.1] The Kaplan-Meier results are described only in words; the text states 'Estas curvas no están disponibles en esta versión preliminar' and 'no mostradas aquí.' No log-rank tests, numbers at risk, or censoring details are given, and the grouping cutpoint for 'significant increase' in adiposity is not defined. The survival claims are therefore not verifiable.
[Section 3.2.2] The four-group Cox model uses only the group indicator, with no covariate adjustment, and the reported hazard ratios may be confounded by age, sex, stage, and baseline body composition. The conclusion that patients with muscle loss and adipose gain have the highest recurrence risk is not robust without adjustment or at least a sensitivity analysis.
[Abstract and Introduction vs. Results] The abstract and introduction promise conclusions about the relative effectiveness of PET/CT, MRI, and CT in follow-up, and the Discussion repeats this. However, no analysis of imaging modality is presented in the Results; Section 2.1 mentions recording imaging type and detection time, but no model or table uses these variables. This unsupported claim should be removed or an actual analysis should be provided.

minor comments (5)

[Throughout] There are numerous typographical errors (e.g., 'prelimiar' in Section 4, 'larigne' in the Figure 1 caption) and inconsistent accent usage; the manuscript needs careful proofreading.
[Figure 1] The figure is taken from radiopedia.org without a license or attribution beyond the URL; this should be clarified and permission or a proper CC license should be documented.
[Section 2.2.2] The definition of 'estado muscular' and the thresholds used to classify patients into muscle/adipose gain or loss groups are not stated, so the four-group analysis is not reproducible.
[Methods] The text should state the statistical software and packages used for the regressions and survival analyses.
[Discussion] The Discussion says that sample size and follow-up may be insufficient and that diet, physical activity, and comorbidity data are unavailable, but no actual numbers or quantitative sensitivity checks are provided; these limitations should be connected to specific reported results.

Circularity Check

0 steps flagged · score 0.0 of 10

No circularity: the logistic/Cox associations are fitted in-sample, not derived from their own outputs, and no load-bearing self-citation is used.

full rationale

No step in this paper reduces to its own inputs. The analyses in Sections 3.1.1, 3.1.3, and 3.2.2 fit logistic and Cox regression coefficients to the HNSCC-MDA cohort and report the fitted associations; the abstract describes these in-sample associations rather than validating an out-of-sample prediction. The change in L3 adiposity index is defined independently of recurrence and survival outcomes in Section 2.1, and the reported coefficient estimates are not constructed so that the association holds by definition. The citation to prior work [2] is contextual ('un estudio similar fue llevado a cabo en [2]') and is not used to justify the present coefficients or to import a uniqueness result. Confounding, missing-data, and generalizability limitations—acknowledged in Section 4—are validity concerns, not circularity. Ordinary model fitting is not circular reasoning, and the paper makes no predictive claim that is statistically forced by its own fitting procedure.

Assumptions & free parameters 4 free parameters · 3 assumptions · 0 invented entities

The central claim rests entirely on the public HNSCC-MDA dataset and on standard statistical models. The main unstated choices are the exact patient subset, the numerical thresholds used to define muscle/adipose loss or gain, and the handling of missing imaging data. No new entities or physical mechanisms are postulated.

free parameters (4)

Adiposity-change slope in logistic model = beta = 0.045, SE 0.012
Fitted to the HNSCC-MDA data; the significance of this coefficient is the paper's main recurrence claim.
Adiposity-change slope in Cox model = beta = 0.038, SE 0.011
Fitted to the same data and used to claim higher mortality risk.
Combined-group Cox coefficients = 1.567, 0.789, 0.456
Fitted hazard ratios for the muscle/adipose groups relative to the reference group.
Categorization thresholds for muscle/adipose change groups = not reported
The four groups are defined by gains and losses, but the paper gives no numerical cutoffs for loss versus gain, a researcher choice that affects all group results.

assumptions (3)

domain assumption L3-level CT body-composition measurements are valid proxies for overall adiposity and muscle status
Invoked in Section 2.1 when using the adiposity index and muscle status at L3 before and after radiotherapy; the paper does not validate this measurement approach.
domain assumption The HNSCC-MDA dataset provides reliable recurrence and survival follow-up
Invoked in Section 2.1; recurrence is defined as a binary variable and survival time in months, but no data-quality or ascertainment details are given.
standard math Standard statistical models (logistic, Kaplan-Meier, Cox) apply without violations
Used in Sections 2.2 and 3; no proportional-hazards or linearity diagnostics are reported.

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Cite this review

Pith. "Pith review of Evaluaci\'on del Cambio en la Musculatura y Adiposidad y su Relaci\'on con la Recurrencia del Carcinoma de Cabeza y Cuello mediante PET/CT y MRI." pith.science (2026). https://pith.science/paper/L2RVSTEF

@misc{pith2026241116264,
  author       = {Pith},
  title        = {Pith review of: Evaluaci\'on del Cambio en la Musculatura y Adiposidad y su Relaci\'on con la Recurrencia del Carcinoma de Cabeza y Cuello mediante PET/CT y MRI},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/L2RVSTEF}},
  note         = {Machine review of arXiv:2411.16264}
}

read the original abstract

This study investigates the impact of changes in body composition and follow-up imaging modalities on recurrence and prognosis in patients with head and neck squamous cell carcinoma (HNSCC). The results indicate that an increase in the adiposity index post-radiotherapy is significantly associated with higher recurrence and mortality rates. Additionally, the combined evaluation of muscle and adipose status reveals that patients with muscle loss and adipose gain have the lowest survival probabilities and the highest risk of recurrence. These findings underscore the importance of monitoring adiposity and muscle status, as well as the strategic use of advanced imaging techniques such as PET/CT, MRI, and CT. However, this work represents a preliminary analysis, and further detailed studies are necessary to confirm these results and develop more effective strategies.

Figures

Figures reproduced from arXiv: 2411.16264 by the authors.

Discussion (0). Continue with ORCID to comment.

Reference graph

Works this paper leans on

6 extracted references · 2 canonical work pages

[2]

J., Chamchod, S., Fuller, C

Grossberg, A. J., Chamchod, S., Fuller, C. D., Mohamed, A. S., Heukelom, J., Eichelberger, H., ... and Rosenthal, D. I. (2016). Association of body composition with survival and locoregional control of radiotherapy-treated head and neck squamous cell carcinoma. JAMA oncology, 2(6), 782-789

work page 2016
[1]

Grossberg, A., Elhalawani, H., Mohamed, A., Mulder, S., Williams, B., White, A. L., ... and Fuller, C. (2020). MD Anderson Cancer Center head and neck quantitative imaging working group. HNSCC [Dataset]. The Cancer Imaging Archive

work page 2020
[3]

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Pith tools

Reviewed August 12, 2026 · model on record in the stance chip above.

[1] [2]

J., Chamchod, S., Fuller, C

Grossberg, A. J., Chamchod, S., Fuller, C. D., Mohamed, A. S., Heukelom, J., Eichelberger, H., ... and Rosenthal, D. I. (2016). Association of body composition with survival and locoregional control of radiotherapy-treated head and neck squamous cell carcinoma. JAMA oncology, 2(6), 782-789

work page 2016

[2] [1]

Grossberg, A., Elhalawani, H., Mohamed, A., Mulder, S., Williams, B., White, A. L., ... and Fuller, C. (2020). MD Anderson Cancer Center head and neck quantitative imaging working group. HNSCC [Dataset]. The Cancer Imaging Archive

work page 2020

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