Effects of the Prior Use of Statins on Head and Neck Cancer Risk: A Hospital-Based Case-Control Study.

Mechanisms related to the potential beneficial effects of statins on cancer are mainly related to the inhibition of the mevalonate pathway. The purpose of this study was to assess the association between prior use of statins and the risk of head and neck cancer. A hospital-based case-control study was conducted at the Dentistry Hospital of the University of Barcelona, including 101 incident cases of head and neck cancer and 101 controls matched to cases by age and sex. Multivariate logistic regression models were used to assess the association between prior statin exposure and head and neck cancer risk. Of the 202 patients included in total, 28.2% had previously received prescriptions for statins. Prior use of statins was found in 25.7% of cases and 30.7% of controls. Exposure to statins was not associated with head and neck cancer risk (OR = 0.72; 95% CI 0.28-1.84; p = 0.49). There was also no time- or dose-dependent association. Similar trends were observed when analyzed by subsites of cancer and recurrence rate. Our findings do not support a beneficial effect of prior statin exposure on head and neck cancer risk. Future research relying on observational data should emulate randomized clinical trials before clinical implications for repurposing drugs can be drawn.

Attributable fractions, modifiable risk factors and risk stratification using a risk score for peri-implant pathology.

PURPOSE: This study aimed to estimate the impact of risk factors for peri-implant pathology, to identify potentially modifiable factors, and to evaluate the accuracy of the risk algorithm, risk scores and risk stratification. METHODS: This retrospective case-control study with 1275 patients (255 cases; 1020 controls) retrieved a model according to the predictors: history of Periodontitis, bacterial plaque, bleeding, bone level, lack of passive fit or non-optimal screw joint, metal-ceramic restoration, proximity to other implants/teeth, and smoking habits. Outcome measures were the attributable fraction; the positive and negative likelihood ratios at different disease cut-off points illustrated by the area under the curve statistic. RESULTS: Six predictors may be modified or controlled directly by either the patient or the clinician, accounting for a reduction in up to 95% of the peri-implant pathology cases. The positive and negative likelihood ratios were 9.69 and 0.13, respectively; the area under the curve was 0.96; a risk score was developed, making the complex statistical model useful to clinicians. CONCLUSIONS: Based on the results, six predictors for the incidence of peri-implant pathology can be modified to significantly improve the outcome. It was possible to stratify patients per risk category according to the risk score, providing a tool for clinicians to support their decision-making process.

Risk factors of peri-implant pathology.

This study aimed to identify risk factors for the incidence of peri-implant pathology. One-thousand, two-hundred and seventy-fifty patients (255 cases and 1020 controls), rehabilitated with dental implants, were included. Peri-implant pathology was defined as the presence of peri-implant pockets ≥ 5 mm, bleeding on probing, vertical bone loss, and loss of attachment ≥ 2 mm. Cases and controls were matched for age, gender, and duration of follow-up. A logistic regression model was used, with estimation of the OR for each variable and interaction, with a level of significance of 5%. The risk factors for peri-implant pathology were: history of periodontitis (OR = 19), bacterial plaque (OR = 3.6), bleeding (OR = 2.9), bone level on the medium third of the implant (OR = 13.9), lack of prosthetic fit or non-optimal screw joint (OR = 5.9), metal-ceramic restorations (OR = 3.9), and the interaction between bacterial plaque and the proximity of other teeth or implants (PROXI) (OR = 4.3). PROXI (OR = 0.44) exerted a protective effect when independent. Based on the results, peri-implant pathology represents a group of multifactorial situations with interaction of biological and biomechanical components in its pathogenesis. It was possible to model the condition and to assess, with high precision, the risk profile of each patient.