Evidence map›Paper›PMID 28157190›Full record

ArticleBlood cancer journal2017

Familial associations of lymphoma and myeloma with autoimmune diseases.

K Hemminki, A Försti, K Sundquist, J Sundquist, X Li

Open access · goldAbstract read
In one paragraph

Article in Blood cancer journal, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.1field-weighted citation impact, top 24% 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

6 citing papers in PubMed, 11 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

5 authors at 1 institution in 3 countries.

K HemminkiDivision of Molecular Genetic Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany.
A FörstiDivision of Molecular Genetic Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany.
K SundquistCenter for Primary Health Care Research, Lund University, Malmö, Sweden.
J SundquistCenter for Primary Health Care Research, Lund University, Malmö, Sweden.
X LiCenter for Primary Health Care Research, Lund University, Malmö, Sweden.
Lund University · SE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Many B-cell neoplasms are associated with autoimmune diseases (AIDs) but most evidence is based on a personal rather than a family history of AIDs. Here we calculated risks for non-Hodgkin lymphoma (NHL), Hodgkin lymphoma (HL) and multiple myeloma (MM) when family members were diagnosed with any of 44 different AIDs, or, independently, risk for AIDs when family members were diagnosed with a neoplasm. A total of 64 418 neoplasms and 531 155 AIDs were identified from Swedish nationwide health care records. NHL was associated with a family history of five AIDs, all increasing the risk, HL was associated with one AID increasing and three AIDs decreasing the risk while MM had no association. A family history of NHL was associated with eight, HL with seven and MM with seven different AIDs, nine increasing and 13 decreasing the risk. The present family data on B-cell neoplasms and AIDs show an approximately equal number of associations for risk increase and risk decrease, suggesting that inherited genes or gene-environment interactions may increase the risk or be protective. These results differed from published data on personal history of AID, which only report increased risks, often vastly higher and for different AIDs compared with the present data.

Indexed as

FamilyAdolescentAdultAgedAged, 80 and overAutoimmune DiseasesChildChild, PreschoolHumansInfantInfant, NewbornLymphomaMiddle AgedMultiple MyelomaPopulation SurveillanceRisk Assessment

Identifiers

PMID28157190
PMCPMC5301032
OpenAlexW2585061907

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.