# Developing a LASSO Regression-Based Nomogram to Predict Outcomes in Abdominal Aortic Aneurysm Patients Post-Endovascular Aneurysm Repair

Researcher: Ge Zhang
Chinese name: 张格
ORCID identity anchor: https://orcid.org/0000-0002-3116-3246
Canonical researcher: https://drgezhang.com/#person

Journal: Clinical Interventions in Aging
Year: 2025
Type: Article
DOI: 10.2147/cia.s493841
Canonical page: https://drgezhang.com/papers/doi-10-2147-cia-s493841.html
Markdown record: https://drgezhang.com/papers/doi-10-2147-cia-s493841.md

## Full Authors

1. Fengyi Yu
2. Dexin Shen
3. Yan Lv
4. Ge Zhang
5. Peiyu Yuan
6. Chenxi Cao
7. Yu Yang
8. Junnan Tang
9. Jinying Zhang

## About this record

This is an author-controlled publication record in the Ge Zhang Academic Hub. It identifies this work as part of Ge Zhang’s publication record via ORCID; the publisher version remains the version of record.

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## Research context and source limits

Limited evidence note. Only the source material identified below has been reviewed; this is not a complete Paper GEO V2 assessment.

Published exploratory Cox estimates with an unspecified analytical denominator; prediction performance remains unverified.

### Cohort and endpoint

This single-centre retrospective study follows 304 patients after elective endovascular abdominal aortic aneurysm repair. The article describes an internal random split into 213 training and 91 validation patients, all-cause mortality as the endpoint, and median follow-up of 24 months (interquartile range 16–33). Emergency repair for ruptured aneurysms was excluded.

Source: [Methods: Study Population and Endpoint and Follow-Up (s0002-s2001–s0002-s2002); Results Patient Characteristics; Table 1](https://pmc.ncbi.nlm.nih.gov/articles/PMC12673264/)

### Reported exploratory associations

Table 3 and its accompanying Results agree on adjusted associations for the article’s large-AAA variable (hazard ratio 3.09, 95% CI 1.43–6.72), stroke history (3.59, 1.67–7.70), and common iliac artery atherosclerosis (4.48, 1.92–10.49). They do not establish causality or the benefit of changing treatment, and their analytic sample size remains unspecified.

Source: [Table 3 multivariable rows; Variable Analysis and Selection (s0003-s2002)](https://pmc.ncbi.nlm.nih.gov/articles/PMC12673264/#t0003)

### Why this is not a validated risk tool

The supplement runs Cox regression on an object named datacox without defining its membership, so the audit does not assign these estimates to 213 or 304 patients. Inconsistent time-specific AUCs and validation mortality percentages remain unresolved. Continuous-variable hazard ratios are omitted because scaling is unclear; no individual risk calculator, clinical utility, or externally validated performance is endorsed.

Source: [Supplementary Table 1, survival/Cox analysis script](https://www.dovepress.com/article/supplementary_file/493841/493841%20Revised%20Supplementary%20Table%201.docx)

### Evidence limits

- The Table 3 Cox analytic denominator is not specified.
- AUC and validation mortality percentage conflicts remain open.
- Reported associations do not demonstrate causality or clinical utility.

### Provenance

- [Article source](https://pmc.ncbi.nlm.nih.gov/articles/PMC12673264/) — Official publisher or PMC full text reviewed locally. Methods: Study Population and Endpoint and Follow-Up (s0002-s2001–s0002-s2002); Results Patient Characteristics; Table 1
- [Article source](https://pmc.ncbi.nlm.nih.gov/articles/PMC12673264/#t0003) — Official publisher or PMC full text reviewed locally. Table 3 multivariable rows; Variable Analysis and Selection (s0003-s2002)
- [Official supplementary material](https://www.dovepress.com/article/supplementary_file/493841/493841%20Revised%20Supplementary%20Table%201.docx) — Publisher-hosted supplementary document. Supplementary Table 1, survival/Cox analysis script

Source review: 2026-10-27.

## Cite this paper

Fengyi Yu, Dexin Shen, Yan Lv, Ge Zhang, Peiyu Yuan, Chenxi Cao, Yu Yang, Junnan Tang, Jinying Zhang. Developing a LASSO Regression-Based Nomogram to Predict Outcomes in Abdominal Aortic Aneurysm Patients Post-Endovascular Aneurysm Repair. Clinical Interventions in Aging. 2025. https://doi.org/10.2147/cia.s493841

- [BibTeX](https://drgezhang.com/citations/doi-10-2147-cia-s493841.bib)
- [RIS / EndNote](https://drgezhang.com/citations/doi-10-2147-cia-s493841.ris)
- [CSL JSON](https://drgezhang.com/citations/doi-10-2147-cia-s493841.csl.json)

## Links

- DOI: https://doi.org/10.2147/cia.s493841
- HTML page: https://drgezhang.com/papers/doi-10-2147-cia-s493841.html
- Google Scholar query: https://scholar.google.com/scholar?q=%22Developing%20a%20LASSO%20Regression-Based%20Nomogram%20to%20Predict%20Outcomes%20in%20Abdominal%20Aortic%20Aneurysm%20Patients%20Post-Endovascular%20Aneurysm%20Repair%22
- ORCID: https://orcid.org/0000-0002-3116-3246