Correlation Between Peri-implantitis and Assumptions of Medications
Correlation Between Peri-implantitis and Assumptions of Medications
The aim of the study is to investigate the correlation between the assumption of systemic
 medications (such as SSRI, PPI, anti-inflammatory drugs and anti-hypertensive drugs) and the
 failure of dental implant therapy in terms of occurrence peri-implantitis and/or implant
 failure.

 The clinical records of all subjects treated with dental implants during the period between
 January 1st, 2005, and December 31st, 2020 in the Dental Clinic of the IRCCS Istituto
 Ortopedico Galeazzi (Milan, Italy) will be screened for inclusion.

 Inclusion criteria: i) subjects who were 18 years old or older at the time of intervention;
 ii) subjects who provided their informed consent for the intervention iii) patients with
 total or partial edentulism treated with dental implants; iv) patients with at least 6 months
 follow-up, beginning from the date of placement of the prosthesis.

 Exclusion criteria: i) incomplete data (e.g. absence of periapical radiographs) Descriptive
 statistics will be provided by means of mean values and standard deviations. Correlation
 between baseline parameters and outcomes will be provided through logistic regression.
 Survival tables and Kaplan-Meier analysis will be elaborated for survival analysis,
 considering the occurrence of implant failure and the diagnosis of peri-implantitis as
 events. Cox regression analysis will be used in order to evaluate the influence of the use of
 each drug on survival curves.

 The level of significance was set at p<0.05. The sample size was calculated in order to
 evaluate the hazard risk of patients exposed to each specific drug (SSRI, PPI,
 Anti-inflammatory drugs or anti-hypertensive) compared to non-exposed patients. The ratio of
 exposed/non-exposed patients is expected to be 1:4 in the cohort. On the basis of a
 hypothesized 5-year incidence of peri-implantitis of 0.16, HR = 2, and a 10% dropout rate,
 the sample should be made of 358 subjects (72 exposed + 286 not exposed).
Global demographic trends clearly show the increase in life expectancy and, as a direct
 consequence of progressive aging, the prevalence of disabling diseases with the relative
 intake of drugs. The impact of certain systemic diseases on the health of peri-implant
 tissues, especially if uncontrolled, has been described by various authors (Mombelli and
 Cionca, 2006; Donos and Calciolari, 2014). Furthermore, the intake of drugs such as thiazide
 diuretics, beta-blockers, anti-inflammatories, proton pump inhibitors and serotonin re-uptake
 inhibitors has been shown to be able to modulate bone metabolism with different mechanisms
 (Vestergaard, 2008). Thus, they may be able to influence peri-implant health.

 Some drugs, such as anti-hypertensive medications have a proved effect on bone metabolism by
 influencing the renin-angiotensin system (Brater et al. 2011).

 In the national report for the year 2019, AIFA (Italian Medicines Agency) has drawn up the
 ranking of the 30 substances with the highest spending rate (The Medicines Utilisation
 Monitoring Centre. National Report on Medicines use in Italy. Year 2019): among these we can
 note fourteen anti-hypertensive drugs, four PPIs, the first of which is pantoprazole (fourth
 place) one SSRI (escitalopram, twenty-fifth place), and one non-steroidal anti-inflammatory
 drug (diclofenac, twentieth place).

 Proton pump blockers (PPIs) are a class of gastric acid secretion inhibitors that are
 currently among the best-selling drugs worldwide. The main clinical uses of PPIs include the
 treatment of gastroesophageal reflux disease (GERD), peptic ulcer, non-ulcer dyspepsia as
 well as in other hypersecretory states including gastrinoma (Gasiorowska & Fass 2008). The
 use of PPIs, especially at high doses and/or in long-term treatments, has been associated to
 an increased risk of hip, wrist and spine fractures (Ye et al. 2011). Different mechanisms
 have been suggested to explain the effects of PPIs on bone metabolism, which include:
 reduction of calcium absorption due to an increased pH in the small intestine (Yu et al.
 2008); reduction of the osteoclastic resorption activity due to the modulation of vacuolar
 ATPase (V-ATPase) at the membrane level in the vesicles of osteoclasts (Mattsson et al 1991);
 inhibition of non-specific alkaline phosphatase (ALP) and FOSFO1 in the vesicles of the bone
 matrix, increasing the expression of osteocalcin and the osteoprotegerin/RANKL ratio (Roberts
 et al. 2007, Delomenede 2009). Regarding in vivo studies and possible interference of PPIs
 with osteoclastic activity, omeprazole was found to modify urinary bone resorption markers in
 humans such as hydroxyproline and calcium levels (Mizunashi et al 1993). Costa-Rodrigues et
 al. (2013) analyzed the concentration- and time-dependent effects of omeprazole, esomeprazole
 and lansoprazole in human osteoclastic and osteoblastic cells, suggesting how they could
 induce direct non-specific cytotoxicity, further amplified by specific inhibitory effects on
 functional parameters such as osteoclastic resorption activity and the osteoblastic ability
 to form a mineralized matrix. However, it is worth remembering that any decrease in bone
 turnover caused by PPIs may be desirable in the context of disorders associated with a high
 rate of osteolysis, such as osteoporosis, Paget's disease and inflammatory conditions such as
 rheumatoid arthritis and periodontal disease, in which a decrease in osteoclast activity can
 lead to a significant improvement in overall bone quality (Rodan & Martin 2000).

 Selective serotonin reuptake inhibitors (SSRIs) are currently among the most common
 antidepressants and their main indications are major depression, generalized anxiety
 disorder, post-traumatic stress disorder, obsessive compulsive disorder, panic attack
 syndrome and bulimia. Their mechanism of action includes primarily the inhibition of the
 serotonin transporter (SERT). The action of selective serotonin reuptake inhibitors (SSRIs)
 on certain receptors and transporters such as 5-HT1B, 5-HT2B or 5-HT2C can result in impaired
 bone metabolism through increased differentiation and activation of osteoclasts (Haney &
 Warden, 2008). Reductions in bone mineral density (BMD) have been described, among others, in
 patients suffering from depressive syndromes which appear to be related to alterations in
 serotonin function (Schweiger et al. 2000). These findings suggest the hypothesis that SSRIs
 may have an impact also on the osseointegration process.

 Anti-hypertensive drugs medications have been proven to interfere with bone metabolism
 through different mechanisms. For example, beta-blockers and angiotensin-converting enzyme
 inhibitors are able to inhibit osteoclasts activity by blocking the surface β-2 adrenergic
 receptors, which affects the renin-angiotensin system (Brater 2011), while thiazides may
 enhance bone formation by increasing calcium absorption at the distal convoluted tubule.

 Systemic corticosteroids such as prednisone, prednisolone, methylprednisolone and
 dexamethasone have anti-inflammatory, immunomodulatory, and antineoplastic effects, therefore
 they are commonly used in the treatment of numerous conditions. However, they are also
 associated to various adverse reactions, especially when used at high doses or for long
 periods. Fracture and osteoporosis are among the most common corticosteroid-related adverse
 events (21-30%, Rice et al. 2017). The mechanism of action of NSAIDs is associated with the
 inhibition of cyclooxygenase (COX) enzyme activity. Two forms of COX enzyme are isolated:
 COX-1 and COX-2. The mechanism through which NSAIDs may negatively affect bone healing has
 not been fully explained, but it seems to be mostly related to the COX-2 blockade. Actually,
 it was proven that COX-2 is necessary for mesenchymal cells to differentiate into osteoblasts
 during fracture healing, while cele-coxib and other COX-2 blockers were reported to have a
 negative effect on the healing process by limiting osteogenesis and decreasing the osteogenic
 potential of mesenchymal stem cells (Lisowska et al. 2018).

 The main aim of the study is to investigate if the systemic assumption of medications (such
 as SSRIs, PPIs, anti-inflammatory drugs, and anti-hypertensive drugs) could imply an
 increased risk of developing peri-implantitis.

 Secondary aims will be to evaluate:

 -  the augmented risk of implant failure correlated to the assumption of drugs

 -  the correlation between the use of drugs and implant cumulative survival rate (CSR%)

 -  the relationship between drug dosage and the development of peri-implantitis

 -  relationship between drug dosage and implant failure The present will be a
 single-center, retrospective, observational, comparative study.

 The primary outcome was the measure of the risk of incurring in peri-implantitis in subjects
 assuming systemic medications (SSRIs, PPIs, anti-inflammatory drugs, and anti-hypertensive
 drugs).

 The secondary outcomes include:

 -  estimation of how the assumption of systemic medications could influence survival curves
 and the occurrence of peri-implantitis;

 -  to establish if a relationship exists between the dosage of systemic medications and the
 risk of incurring in peri-implantitis

 -  to establish if a relationship exists between the dosage of systemic medications and the
 risk of incurring in implant failure

 The definition of implant survival will be based on the fact that the implant is still in
 situ, stable, and supporting a functional prosthesis. An implant that was removed or
 spontaneously lost due to failed osseointegration will be considered an implant failure.
 Peri-implantitis will be defined according to the following parameters: 1) presence of
 bleeding and/or suppuration on gentle probing; 2) presence of radiographic bone loss of at
 least 2 mm, beyond crestal bone level changes due to initial bone remodeling, evaluated
 through comparison of baseline (one year after surgical intervention) and follow-up
 periapical radiographs; in absence of baseline periapical radiographs, presence of bone level
 located ≥ 3 mm apical to the most coronal portion of the intraosseous portion of the implant;
 3) presence of an increased probing depth as compared to previous observations.

 The following parameters will be collected from clinical records:

 -  Patient's age and sex at the time of surgical intervention

 -  description of systemic diseases (if any) at the time of surgical intervention

 -  description of pharmacological therapy (if any) at the time of surgical intervention

 -  smoking status (number of cigarettes (if reported)) at the time of surgical intervention

 -  history of periodontal disease before the surgical intervention or at the time of
 surgical intervention

 -  date of surgery

 -  implant position

 -  implant brand and type, diameter, length, diameter of the prosthetic platform

 -  characteristics of the bone regeneration procedure (if performed)

 -  description of surgical complications (if any)

 -  characteristics and timing of prosthetic rehabilitation (provisional and definitive)

 -  date of the last clinical control

 -  date of the last radiographic control

 -  failure occurrence date (if any); the diagnosis of failure was based on the procedure
 described in paragraph 3.1

 -  peri-implantitis occurrence date (if any); the diagnosis of peri-implantitis was based
 on the procedure described in paragraph 3.1

 -  oral hygiene level

 -  frequency of maintenance recall sessions

 Data collection will be performed in a maximum period of 5 months. Data analysis will take a
 maximum of 4 months, for a total duration of 9 months. The collected data refer to clinical
 records of patients treated with implants from January 1st, 2005 to June 30th, 2020 (last
 follow-up included: 6 month visit on December 2020).

 The sample size was calculated in order to evaluate the hazard risk of patients exposed to a
 specific drug (SSRI, PPI, Anti-inflammatory drugs or anti-hypertensive) compared to
 non-exposed patients. The ratio of exposed/non-exposed patients is expected to be 1:4 in the
 cohort. The 5-year incidence in non-exposed patients in a previous series of cases resulted
 0.16, and an HR=2 is expected in the exposed patients. On the basis of these assumptions,
 considering a 10% dropout rate, the sample should be made of 358 subjects (72 exposed + 286
 not exposed ).

 Therefore, will be included a total of 358 patients who was exposed at least to one of the
 study drugs: each subject will be evaluated both in the test group of the exposure drug (vs
 the group of subjects who did not take that drug), and in the control group for the drugs
 that he/she has not taken.

 The calculation was performed using the method proposed by Schoenfeld (Schoenfeld 1983).

 Descriptive statistics will be provided by means of mean values and standard deviations.
 Correlation between baseline parameters and outcomes will be provided through the use of
 logistic regression. Survival tables and Kaplan-Meier analysis will be elaborated for
 survival analysis, considering the occurrence of implant failure and the diagnosis of
 peri-implantitis as events. Cox regression analysis will be used in order to evaluate the
 influence of the use of SSRI and/or PPI on survival curves.

 For all the analysis, the level of significance was set at p<0.05.
Inclusion Criteria:

 -  subjects who were 18 years old or older at the time of intervention

 -  subjects who provided their informed consent for the intervention

 -  patients with total or partial edentulism treated with dental implants

 -  patients with at least 6 months follow-up, beginning from the date of placement of the
 prosthesis.

 Exclusion Criteria:

 -  Incomplete data (e.g. absence of periapical radiographs)