Evidence map›Paper›PMID 25943685›Full record

ArticlePharmacoEconomics2015

Calculating the Baseline Incidence in Patients Without Risk Factors: A Strategy for Economic Evaluation.

Scott D Nelson, Daniel Malone, Joanne Lafleur

Abstract read
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In one paragraph

Article in PharmacoEconomics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Cost-effectiveness of training rural providers to identify and treat patients at risk for fragility fractures.Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA · 2014
    Article
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

3 authors.

Scott D NelsonDepartment of Veterans Affairs, Salt Lake City, UT, USA, Scott.Nelson@pharm.utah.edu.
Daniel Malone
Joanne Lafleur

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Economic and epidemiological models need various inputs to estimate the occurrence of events in different subsets of the population, such as the incidence of events for patients with risk factors compared with those without. However, the baseline event incidence for patients without risk factors (incidence_no_risk) may not be reported in the literature, therefore the event incidence in the population (incidence_pop) is commonly used in its place as the baseline. However, this is problematic because incidence_pop is a weighted average of a heterogeneous population. We therefore developed a method for deriving the incidence for persons without risk factors (incidence_no_risk) by adjustment of incidence_pop. We calculated incidence_no_risk using the relative risk for events due to risk factors (RR_risk), incidence_pop, and the prevalence of the risk factor (pRF), which are typically available in the literature. Since the incidence for patient with risk factors (incidence_risk) can be expressed as incidence_risk = incidence_no_risk × RR_risk, we found that incidence_no_risk = incidence_pop/((RR_risk × pRF) + (1 - pRF)). We validated the equation by modeling the fracture incidence in high-risk patients in an osteoporosis transition-state model. With incidence_pop used as the baseline fracture incidence, the model overestimated hip fractures in the study population (10.72 fractures/1000 patient-years). After adjustment of incidence_pop using incidence_no_risk as the baseline incidence, the model accurately predicted hip fractures (2.27/1000 patient-years). Therefore, incidence_no_risk can be calculated using this method based on the event incidence for the study population, the relative risk increase associated with the risk factor, and the prevalence of the risk factor.

Indexed as

Fractures, BoneModels, EconometricOsteoporosisAgedAged, 80 and overComputer SimulationHumansIncidenceMaleRisk Factors

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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.