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Olof Nyrén

Researcher at Karolinska Institutet

Publications -  274
Citations -  24232

Olof Nyrén is an academic researcher from Karolinska Institutet. The author has contributed to research in topics: Population & Cancer. The author has an hindex of 78, co-authored 274 publications receiving 23034 citations. Previous affiliations of Olof Nyrén include Vanderbilt University Medical Center & Harvard University.

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Relation of vagotomy to subsequent risk of lung cancer: population based cohort study

TL;DR: It is analyzed to what extent such potential relief would affect the subsequent risk of lung cancer in patients who had had a vagotomy for peptic ulcer disease, compared with patients with the disease who were treated without surgery.
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An internet-based hearing test for simple audiometry in nonclinical settings: preliminary validation and proof of principle.

TL;DR: It is possible to assess hearing with reasonable accuracy using an Internet-based hearing test on a personal computer with headphones, and the practical viability of self-administration in participants' homes needs further evaluation.
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A long-term follow-up study on the natural course of oral leukoplakia in a Swedish population-based sample.

TL;DR: Smoking cessation was associated with an increased disappearance of OL, and at least one-fourth of individuals with OL had lesions that could be classified as tobacco-related, which prohibited firm conclusions about a possible excess risk of developing oral cancer.
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Risk of Hodgkin's disease subsequent to tonsillectomy : A population-based cohort study in Sweden

TL;DR: The data suggest a small increase in HD among all patients undergoing T/A and a significant excess for those under age 12 at surgery, and cannot exclude the possibility that the excess may be due to factors underlying the disorders that led to surgery.
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Comparing Different Strategies for Timing of Dialysis Initiation Through Inverse Probability Weighting

TL;DR: It is demonstrated that recently developed methods in the causal inference literature can be used to avoid both types of bias and accurately estimate the ideal time for dialysis initiation from observational data.