Evidence map›Paper›PMID 27895435›Full record

ArticleHippokratia

Optimal MRI interval for detection of asymptomatic recurrence in surgically treated early cervical cancer by use of a mathematical model.

A Laios, K Gubbala, R Lampe, A Tolis

Open access · greenAbstract read
In one paragraph

Article in Hippokratia. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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, 0 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

4 authors at 2 institutions in 2 countries.

A LaiosGynecologic Oncology Firm, Churchill Hospital, Oxford University Hospitals NHS Trust, Oxford, UK.
K GubbalaGynecologic Oncology Firm, Churchill Hospital, Oxford University Hospitals NHS Trust, Oxford, UK.
R LampeDepartment of Obstetrics and Gynecology, University of Debrecen, Hungary.
A TolisSchool of Mechanical Engineering, Sector of Industrial Management and Operational Research, National Technical University of Athens, Athens, Greece.
National Technical University of Athens · GRUniversity of Debrecen · HU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionApplications of mathematical modeling may provide an insight into the timing of surveillance modalities. We aimed to determine the optimal magnetic resonance imaging (MRI) interval for the detection of surgically treated early cervical cancer asymptomatic recurrence by using a mathematical model for volumetric tumor growth time.

methodsWe assumed that tumor volume increases by a factor equal to the basis of natural logarithms (e~2.718) at constant time intervals. Using a mathematical formula, the tumor volume (V) was converted to diameter (D), which could be expressed as a function of time (t), given an initial diameter Di (corresponding to initial volume Vi) and a constant DT, where DT is the time required for volumetric tumor growth by a factor (e). Three different DTs were used for demonstration of the model, i.e. 20, 100 and 400 days.

resultsAssuming complete surgical clearance, a worst-case scenario for a 20-day DT indicated that a 20 μm cervical tumor would need at least 12 months to reach 10 mm in diameter, which would be detected with an annual surveillance interval MRI. Over a 5-year (60 months) follow-up, nearly five surveillance MRIs would be required if the threshold of 10 mm was desired. For a 100-day DT over a 5-year (60 months) follow-up, a single only MRI would be required, if the threshold of 10 mm was desired. In the case of an indolent tumor (DT is 400 days), the model would not recommend a surveillance MRI to detect asymptomatic recurrence. A positive linear association between optimal MRI intervals and volumetric tumor DTs was demonstrated.

conclusionIn the absence of evidence, we postulate annual MRI scanning is probably the shortest interval, which can be clinically useful for optimization of routine surveillance follow-up protocols in surgically treated early cervical cancer. This mathematical model requires proper verification in prospective clinical studies. Hippokratia 2016, 20(1): 4-8.

Indexed as

Cervical cancermathematical modeloptimal MRI intervaltumor growth

Identifiers

PMID27895435
PMCPMC5074396
OpenAlexW2560387789

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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.