Evidence map›Paper›PMID 39677417›Full record

ArticlemedRxiv : the preprint server for health sciences2025

Modeling early-onset cancer kinetics to study changes in underlying risk, detection, and impact of population screening.

Navid Mohammad Mirzaei, Chin Hur, Mary Beth Terry, Piero Dalerba, Wan Yang

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Navid Mohammad MirzaeiDepartment of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York, USA.ORCID 0000-0002-0971-0514
Chin HurDepartment of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York, USA.
Mary Beth TerryDepartment of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York, USA.
Piero DalerbaCenter for Discovery and Innovation (CDI), Hackensack Meridian Health (HMH), Nutley, New Jersey, USA.
Wan YangDepartment of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York, USA.

Funding

Tumor Biology and Microenvironment ProgramP30CA013696 · NCI · COLUMBIA UNIV NEW YORK MORNINGSIDE · PI Anil K Rustgi · 1985 to 2026
$115.3M
Clinical and Translational Science AwardUL1TR001873 · NCATS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI REILLY, MUREDACH P · 2016 to 2025
$99.0M
Institutional Career Development CoreKL2TR001874 · NCATS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI GENKINGER, JEANINE M., SHIMBO, DAICHI · 2016 to 2025
$13.6M
UNCOVER: underlying novel causes of onset of very early cancer researchR01CA257971 · NCI · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI YANG, WAN · 2021 to 2025
$2.0M
Multidisciplinary Training in Gastrointestinal CancersT32CA285274 · NCI · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI Julian Abrams, Anil K Rustgi · 2024 to 2026
$897k
NCATS NIH HHS KL2 TR001874NCATS NIH HHS UL1 TR001873NCI NIH HHS P30 CA013696NCI NIH HHS R01 CA257971NCI NIH HHS T32 CA285274
6 · The paper itself

Abstract

Recent studies have reported increases in early-onset cancer cases (diagnosed under age 50) and raised questions about whether the increase is related to earlier diagnosis from non-specific medical tests as reflected by decreasing tumor-size-at-diagnosis (apparent effects) or actual increases in underlying cancer risk (true effects), or both. The classic Multi-Stage Clonal Expansion (MSCE) model assumes cancer detection at the first malignant cell's emergence, although later modifications have included lag-times or stochasticity in detection to represent the delay in tumor detection. Here, we introduce an approach to explicitly incorporate tumor-size-at-diagnosis in the MSCE framework accounting for improvements in cancer detection over time to distinguish between apparent and true increases in early-onset cancer incidence. We demonstrate that our model is structurally identifiable and provides better parameter estimation than the classic model. Applying this model to colorectal, breast, and thyroid cancers, we examine changes in cancer risk while accounting for detection improvements over time in three representative birth cohorts (1950-1954, 1965-1969, and 1980-1984). Our analyses suggest accelerated carcinogenic events and shorter mean sojourn times (the average time from the first malignant cell emergence to cancer detection) in more recent cohorts. We further use this model to examine the screening impact on the incidence of breast and colorectal cancers, both having established screening protocols. Our results align with well-documented differences in screening effects between these cancers. These findings underscore the importance of incorporating tumor-size-at-diagnosis in cancer modeling and support true increases in early-onset cancer risk in recent years for breast, colorectal, and thyroid cancer.

Indexed as

Cancer kineticsEarly-onset cancerScreening impactSojourn timeTumor size

Identifiers

PMID39677417
PMCPMC11643252

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.