Predicting Implant Failure and Complications Using Cluster Analysis After Variable Selection: A Retrospective Study

IF 3.7 2区医学 Q1 DENTISTRY, ORAL SURGERY & MEDICINE

Clinical Implant Dentistry and Related Research Pub Date : 2025-06-24 DOI:10.1111/cid.70063

Jinlin Zhang, Yufeng Gao, Yannan Cao, Zhuang Ding, Bo Chen, Fangyong Zhu

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引用次数: 0

Abstract

Background

Uneven data distribution (due to rare outcomes) and repeated measurements (from multiple implants per patient) hinder the creation of a precise oral implant failure risk model.

Purpose

The aim of this study was to explore variable selection methods suitable for oral implant data, assess risk factors of early failure and postoperative complications, and apply the two-step cluster analysis to establish a risk prediction model for oral implant failure, providing a reference for clinical practice.

Materials and Methods

This study was a retrospective analysis, with early failure and postoperative complications serving as the outcome indicators. Given the repeated measurements and uneven distribution in oral implant data, our study conducted a comparative analysis between GEE and GEE with Firth penalization. This study evaluated the influencing factors screened by a more suitable model and utilized them for subsequent risk prediction. A two-step cluster analysis was applied to identify different subgroups of early failure and postoperative complications; their clinical characteristics were compared, and relevant risk prediction models were developed.

Results

Among a total of 677 patients and 1200 implants, 21 implants were lost prior to loading, and postoperative complications occurred in 74 patients involving 94 implants. The GEE model with Firth's penalty term indicated that non-submerged healing (p < 0.001), shorter implant length (p < 0.001), and thinner diameter (p = 0.007) were risk factors for early failure. The GEE model showed that non-submerged healing (p = 0.039) was a protective factor against postoperative complications, whereas unhealed extraction sockets at the implant site (p = 0.048), the use of bone substitutes (p = 0.008), and a history of periodontal disease (p = 0.009) were risk factors. Additionally, the use of bovine tendon-derived absorbable biomembranes (p = 0.036) may elevate the risk of postoperative complications. The two-step cluster analysis identified two patient subgroups, categorized as high-risk and low-risk, and the prediction model demonstrated good discrimination ability.

Conclusions

Early failure data were highly imbalanced, and the incorporation of the Firth penalty term provided significant benefits. However, its effectiveness in managing postoperative complication data remained limited. Thus, a one-size-fits-all approach to variable screening may not have suited all types of imbalanced data. The analysis conducted in this study, using specific screening techniques, yielded more reliable influencing factors. Additionally, the developed two-step clustering model was capable of predicting high-risk patients for early failures and postoperative complications before surgery, aiding clinicians in devising personalized preventive measures to reduce incidence rates.

Trial Registration: Clinical trial registration number: ChiCTR2300070420

查看原文本刊更多论文

变量选择后使用聚类分析预测种植体失败和并发症：一项回顾性研究

不均匀的数据分布（由于罕见的结果）和重复的测量（来自每个患者的多个种植体）阻碍了精确口腔种植体失败风险模型的建立。目的探讨适合口腔种植体数据的变量选择方法，评估口腔种植体早期失败及术后并发症的危险因素，应用两步聚类分析建立口腔种植体失败的风险预测模型，为临床实践提供参考。材料与方法本研究为回顾性分析，以早期失败和术后并发症为预后指标。考虑到口腔种植体数据的重复测量和不均匀分布，我们的研究对GEE和带有Firth惩罚的GEE进行了比较分析。本研究通过筛选更合适的模型对影响因素进行评估，并将其用于后续的风险预测。采用两步聚类分析确定早期失败和术后并发症的不同亚组；比较两组患者的临床特点，建立相应的风险预测模型。结果677例患者1200颗种植体中，21颗种植体在装填前丢失，74例患者94颗种植体出现术后并发症。带有Firth惩罚项的GEE模型显示，非浸没愈合（p < 0.001）、较短的种植体长度（p < 0.001）和较细的直径（p = 0.007）是早期失败的危险因素。GEE模型显示，未浸没愈合（p = 0.039）是预防术后并发症的保护因素，而种植体部位拔牙槽未愈合（p = 0.048）、骨替代物的使用（p = 0.008）和牙周病史（p = 0.009）是危险因素。此外，使用牛肌腱来源的可吸收生物膜（p = 0.036）可能会增加术后并发症的风险。两步聚类分析将患者分为高危和低危两个亚组，预测模型具有较好的判别能力。结论早期失败数据高度不平衡，合并第5个惩罚项有显著的好处。然而，其在处理术后并发症方面的有效性仍然有限。因此，一刀切的变量筛选方法可能不适合所有类型的不平衡数据。本研究采用特定筛选技术进行分析，得出了更可靠的影响因素。此外，开发的两步聚类模型能够在手术前预测高危患者的早期失败和术后并发症，帮助临床医生制定个性化的预防措施以降低发病率。试验注册：临床试验注册号：ChiCTR2300070420

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来源期刊

Clinical Implant Dentistry and Related Research 医学-牙科与口腔外科

CiteScore

6.00

自引率

13.90%

发文量

103

审稿时长

4-8 weeks

期刊介绍： The goal of Clinical Implant Dentistry and Related Research is to advance the scientific and technical aspects relating to dental implants and related scientific subjects. Dissemination of new and evolving information related to dental implants and the related science is the primary goal of our journal. The range of topics covered by the journals will include but be not limited to: New scientific developments relating to bone Implant surfaces and their relationship to the surrounding tissues Computer aided implant designs Computer aided prosthetic designs Immediate implant loading Immediate implant placement Materials relating to bone induction and conduction New surgical methods relating to implant placement New materials and methods relating to implant restorations Methods for determining implant stability A primary focus of the journal is publication of evidenced based articles evaluating to new dental implants, techniques and multicenter studies evaluating these treatments. In addition basic science research relating to wound healing and osseointegration will be an important focus for the journal.