Evidence map›Paper›PMID 38236934›Full record

ArticlePloS one2024

Development and validation of a multi-dimensional diagnosis-based comorbidity index that improves prediction of death in men with prostate cancer: Nationwide, population-based register study.

Marcus Westerberg, Sandra Irenaeus, Hans Garmo, Pär Stattin, Rolf Gedeborg

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In one paragraph

Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

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3 · Its place in the literature

Who cites it

15 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.

Marcus WesterbergDepartment of Surgical Sciences, Uppsala University, Uppsala, Sweden.ORCID 0000-0002-8906-6967
Sandra IrenaeusDepartment of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden.
Hans GarmoDepartment of Surgical Sciences, Uppsala University, Uppsala, Sweden.
Pär StattinDepartment of Surgical Sciences, Uppsala University, Uppsala, Sweden.
Rolf GedeborgDepartment of Surgical Sciences, Uppsala University, Uppsala, Sweden.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Assessment of comorbidity is crucial for confounding adjustment and prediction of mortality in register-based studies, but the commonly used Charlson comorbidity index is not sufficiently predictive. We aimed to develop a multidimensional diagnosis-based comorbidity index (MDCI) that captures comorbidity better than the Charlson Comorbidity index. The index was developed based on 286,688 men free of prostate cancer randomly selected from the Swedish general population, and validated in 54,539 men without and 68,357 men with prostate cancer. All ICD-10 codes from inpatient and outpatient discharges during 10 years prior to the index date were used to define variables indicating frequency of code occurrence, recency, and total duration of related hospital admissions. Penalized Cox regression was used to predict 10-year all-cause mortality. The MDCI predicted risk of death better than the Charlson comorbidity index, with a c-index of 0.756 (95% confidence interval [CI] = 0.751, 0.762) vs 0.688 (95% CI = 0.683, 0.693) in the validation cohort of men without prostate cancer. Men in the lowest vs highest MDCI quartile had distinctively different survival in the validation cohort of men with prostate cancer, with an overall hazard ratio [HR] of 5.08 (95% CI = 4.90, 5.26). This was also consistent within strata of age and Charlson comorbidity index, e.g. HR = 5.90 (95% CI = 4.65, 7.50) in men younger than 60 years with CCI 0. These results indicate that comorbidity assessment in register-based studies can be improved by use of all ICD-10 codes and taking related frequency, recency, and duration of hospital admissions into account.

Indexed as

Prostatic NeoplasmsComorbidityHumansMaleProportional Hazards ModelsRetrospective StudiesSweden

Identifiers

PMID38236934
PMCPMC10796041

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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.