Evidence map›Paper›PMID 23365693›Full record

ArticlePloS one2013

Nationwide registry-based analysis of cancer clustering detects strong familial occurrence of Kaposi sarcoma.

Eevi Kaasinen, Mervi Aavikko, Pia Vahteristo, Toni Patama, Yilong Li, Silva Saarinen, Outi Kilpivaara, Esa Pitkänen, Paul Knekt, Maarit Laaksonen and 4 more

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.3field-weighted citation impact, top 20% of its field
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

7 citing papers in PubMed, 24 citations in OpenAlex.

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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

14 authors at 4 institutions in 1 country.

Eevi KaasinenGenome-Scale Biology Research Program, and Department of Medical Genetics, Faculty of Medicine, University of Helsinki, Helsinki, Finland.
Mervi Aavikko
Pia Vahteristo
Toni Patama
Yilong Li
Silva Saarinen
Outi Kilpivaara
Esa Pitkänen
Paul Knekt
Maarit Laaksonen
Miia Artama
Rainer Lehtonen
Lauri A Aaltonen
Eero Pukkala
University of Helsinki · FIFinnish Cancer Registry · FIFinnish Institute for Health and Welfare · FITampere University · FI

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Many cancer predisposition syndromes are rare or have incomplete penetrance, and traditional epidemiological tools are not well suited for their detection. Here we have used an approach that employs the entire population based data in the Finnish Cancer Registry (FCR) for analyzing familial aggregation of all types of cancer, in order to find evidence for previously unrecognized cancer susceptibility conditions. We performed a systematic clustering of 878,593 patients in FCR based on family name at birth, municipality of birth, and tumor type, diagnosed between years 1952 and 2011. We also estimated the familial occurrence of the tumor types using cluster score that reflects the proportion of patients belonging to the most significant clusters compared to all patients in Finland. The clustering effort identified 25,910 birth name-municipality based clusters representing 183 different tumor types characterized by topography and morphology. We produced information about familial occurrence of hundreds of tumor types, and many of the tumor types with high cluster score represented known cancer syndromes. Unexpectedly, Kaposi sarcoma (KS) also produced a very high score (cluster score 1.91, p-value <0.0001). We verified from population records that many of the KS patients forming the clusters were indeed close relatives, and identified one family with five affected individuals in two generations and several families with two first degree relatives. Our approach is unique in enabling systematic examination of a national epidemiological database to derive evidence of aberrant familial aggregation of all tumor types, both common and rare. It allowed effortless identification of families displaying features of both known as well as potentially novel cancer predisposition conditions, including striking familial aggregation of KS. Further work with high-throughput methods should elucidate the molecular basis of the potentially novel predisposition conditions found in this study.

Indexed as

Genetic Predisposition to DiseaseRegistriesCluster AnalysisDatabases, FactualFemaleFinlandHerpesvirus 8, HumanHumansMalePedigreeRisk FactorsSarcoma, KaposiSeroepidemiologic StudiesSkin Neoplasms

Identifiers

PMID23365693
PMCPMC3554690
OpenAlexW2019312853

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

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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.