Clinical, Radiographic and Histomorphotmetric Analysis of Healing Dynamics in Human Extraction Sockets Grafted With Bio-Oss Collagen®: A Prospective 3-year Post-loading Study
Phase: NA
Conditions: Tooth Loss
Sponsor: University of Iowa

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Official Title: Clinical, Radiographic and Histomorphotmetric Analysis of 
Healing Dynamics in Human Extraction Sockets Grafted With Bio-Oss Collagen®: A 
Prospective 3-year Post-loading Study 
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NCT Number: NCT03659617 
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Document Date: November 18, 2025 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Objective: The purpose of this study is to clinically, radiographically and 
histologically evaluate the healing sequence of post-extraction sockets grafted with 
Bio-Oss Collagen® at 3, 6 and 9 months following tooth extraction in single-rooted 
tooth sites. 
Design: This is a randomized clinical trial (NCT03659617). The study population 
consists of adult subjects (ages 18-95) that a single-rooted tooth (except the 
incisors of the lower jaw) indicated for extraction. Subjects cannot have signiﬁcant 
heart, stomach, liver, kidney, blood, immune system disease, or other organ 
impairment or systemic diseases that would prevent undergoing the proposed 
treatment or may result in compromised healing (e.g. poorly controlled diabetes, 
active heavy tobacco use [>10 cigarettes/day])  
Methods: Consented subjects will be randomized to one of three groups.  
Randomization will be done as 1:1:1. Therefore, subjects will have a 33% chance of 
being randomized to a group where they will have implant placement either after 
three, six, or nine months after implant placement. 
Statistical Analysis Plan: The distribution of the data intergroup is expected to 
exhibit normality, and for this reason the statistical tests that will be utilized for data 
analysis are parametric. Nevertheless, prior to the conduction of any parametric 
test, Wilcoxon Signed Rank tests will be performed to verify the normal distribution 
of the data.  Histomorphometric data will be expressed as the percentage of vital 
bone, remaining xenograft particles and non-mineralized connective tissue 
respective to the total sample area. The statistical analyses for these three different 
compartments will be performed independently: One-way Analysis of Variance 
(ANOVA) test will be performed to evaluate the differences in the percentage of 
each speciﬁc compartments between the three time points (3, 6 and 9 months). 
The percentage of each compartment evaluated will be the dependent variable and 
the time will be the independent variable. This test will probe the null hypothesis 
that is established as ‘no difference in percentage of vital bone, remaining xenograft 
particles and non-mineralized connective tissue at the different harvesting time 
points’. The signiﬁcance level will be set at 0.05 and the Bonferroni method for 
correction will be applied. False positive rate will be calculated, as well.  The 
volumetric and linear data obtained from the CBCT scans will be analyzed using the 
same test utilized for the histomorphometric data analyses, setting the signiﬁcance 
level at 0.05, the Bonferroni method will be applied and the false positive rate will 
be calculated.  WHI values obtained at the three different time points (3, 6 and 9 
months) will be analyzed using the Kruskal-Wallis test. The null hypothesis states 
that no differences in WHI will be found at different time points. Likewise, the self-

reported level of discomfort will be compared using the Kruskal-Wallis test. The 
level of discomfort and the post-op visits will be the dependent and independent 
variable respectively. The signiﬁcance level will be set at 0.05.  Other variables 
recorded in this study will be expressed as a percentage (i.e. implant survival rate) 
or presented using descriptive statistics (i.e. marginal bone level). These variables 
are not expected to be representative of meaningful changes and, consequently, no 
analytical statistics are initially planned. However, the data will be assessed upon 
collection and suitability of appropriate analyses will be determined upon data 
distribution.