Evidence map›Paper›PMID 27476170›Full record

ArticleTumour biology : the journal of the International Society for Oncodevelopmental Biology and Medicine2016

A guide for the analysis of long-term population growth in cancer.

Andrew O Silva, Karina B Felipe, Emilly S Villodre, Patricia L C Lopez, Guido Lenz

Abstract read
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In one paragraph

Article in Tumour biology : the journal of the International Society for Oncodevelopmental Biology and Medicine, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Andrew O SilvaDepartment of Biophysics, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil.
Karina B FelipeDepartment of Clinical Analysis, Universidade Federal do Paraná (UFPR), Curitiba, Brazil.
Emilly S VillodreDepartment of Biophysics, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil.
Patricia L C LopezHospital de Clínicas de Porto Alegre (HCPA), Porto Alegre, RS, Brazil.
Guido LenzDepartment of Biophysics, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil. lenz@ufrgs.br.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Although cancer is a chronic disease, most of the in vitro experiments to assess the effectiveness of intervention are performed in hours or a few days. Moreover, none of the available methodologies to measure cell proliferation are adapted to provide information about the growth kinetic during and after treatment. Thus, the objective of this work is to provide a guide to assess long-term changes in cell population size to be used mainly in cancer research. Cumulative population doubling (CPD) graphs based on cell counting for in vitro or tumor volume for in vivo assays were used to calculate four parameters: relative end CPD (RendCPD), to quantify the end point analysis of proliferation; relative area under curve (rAUC), to describe the global chronic effect of a treatment; relative time to cross a threshold (RTCT), to indicate the delay in cell population recovery produced by a treatment; and relative proliferation rate (RPR), to describe the relative regrowth velocity of the cells that survived after treatment. These parameters describe not only the acute and chronic effects of a treatment but also the behavior of cells that are not eliminated by the treatment, providing crucial information about the growth kinetic of the surviving population. Moreover, the proposed analysis allowed the grouping of independent CPD experiments quantified at different time points and even the direct comparison of in vitro and in vivo experiments. Therefore, this new way to analyze long-term outcomes provides a global view of the effectiveness of an intervention, as an important tool for long-term studies.

Indexed as

Guidelines as TopicAnimalsAntineoplastic AgentsArea Under CurveCell ProliferationGliomaHumansMaleMiceMice, Inbred BALB CMice, NudeModels, TheoreticalTime FactorsTumor Cells, CulturedXenograft Model Antitumor AssaysAntineoplastic AgentsCancer resistanceCell proliferationCell regrowthChronic effectsCumulative population doublingLong-term analysis

Identifiers

What OpenQuestion holds

Textmetadata
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.