Introduction
The cervical vertebral maturation (CVM) method comprises 6 stages reported to be prepubertal (1 and 2), pubertal (3 and 4) and postpubertal (5 and 6), and its use has been recommended for planning treatment timing in orthodontics. Reliable use of the method implies that pubertal stages have to mature into postpubertal as soon as the growth peak is terminated. The present study was aimed at determining whether postpubertal CVM stages 5 or 6 are attained in all subjects.
Methods
A total of 450 adult subjects (270 females and 180 males; mean age, 30.4 ± 27.3 years; range, 20-45 years) seeking orthodontic treatment and having a lateral head film were included in the study. Customized cephalometric analysis was used, and each recording was converted into an individual CVM code according to the concavities of the C2 to C4 and shapes of C3 and C4. The retrieved CVM codes, either falling within the reported norms (regular cases) or not (exception cases), were also converted into the CVM stages and a newly introduced CVM score (0-9) capable of defining intermediate stage.
Results
The most frequent CVM stage was 5, while the CVM stage 6 was attained in only one third of the sample. Up to about 11% of adult subjects showed the pubertal CVM stage 4. Irrespective of the CVM stage or CVM score, no significant differences were seen between the sexes or across ages. The C4 showed a rectangular vertical shape in only 16.4% of the cases.
Conclusions
The percentage of adult population maintaining a pubertal CVM stage 4 is not high, but still relevant from a clinical standpoint. In light of this finding, planning treatment timing-based only on CVM appears not fully reliable.
Highlights
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Only one third of adult subjects showed the most mature cervical vertebral maturation (CVM) stage 6.
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About 11% of adult subjects still showed a pubertal CVM stage 4.
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Age and sex showed no significant associations with the persistence of the pubertal CVM stages.
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A CVM score has been introduced to the benefit of future investigations.
In orthodontics, determination of the timing of intervention for interceptive and functional treatments has been reported to be a critical issue to determine the success or failure in the treatment of several types of malocclusions. , Treatments for constricted maxilla, skeletal Class III malocclusion, , and even interception of palatially displaced canines should be provided at an early stage, such as during the prepubertal growth phase. On the contrary, skeletal Class II malocclusion should be treated at a later stage during puberty. Optimal timing for orthodontic treatment thus relies on the identification of specific growth phases (prepubertal, pubertal and postpubertal), through the assessment of skeletal maturity according to various growth indicators.
The cervical vertebral modifications in growing subjects have gained increasing interest, especially during the last 2 decades, as a growth indicator of individual skeletal maturity. Thus, a cervical vertebral maturation (CVM) method was initially proposed by Lamparski, while more recent versions , , including 6 stages have gained popularity, both in clinical practice and research. In particular, mandibular growth peak has been reported to occur in coincidence with CVM stages 3 and 4, , while CVM stage 5 would be attained soon after the end of the pubertal growth spurt, and the subsequent CVM stage 6 would be attained about 1 year later. According to this evidence, the CVM stages 1 and 2 have been referred to as prepubertal , CVM stages 3 and 4 have been referred to as pubertal , and CVM stages 5 and 6 have been defined as postpubertal .
Fundamental requisites to properly plan treatment timing in orthodontics is that pubertal CVM stages are reliable indicators of the growth peak, but also that these stages have to mature into postpubertal stages as soon as growth peak is terminated. Available investigations to date have focused on the capability of the CVM stages 3 and 4 to correlate , or to identify in individual subjects the mandibular growth peak. However, very scarce data has been reported to date how often these pubertal stages mature into postpubertal stages (ie, whether postpubertal CVM stages are attained by all the subjects), while relevant longitudinal studies missed this relevant information. , , Accordingly, the attainment of postpubertal stages in adult subjects has been considered to happen as a dogma.
An objective and transparent CVM code system has been developed to clarify the reasons for controversial results among investigations. Therefore, through the use of the CVM code system, the present study was aimed at determining whether postpubertal CVM stages 5 or 6 are attained in adult subjects.
Material and methods
The database of the Section of Orthodontics of the Department of Medical, Surgical and Health Sciences, University of Trieste (Italy), between January 2008 and December 2018, was screened. The sample for this study included subjects seeking orthodontic treatment whose signed informed consent was obtained before entry into the study; the protocol was reviewed and approved by the local Ethical Committee. In each subject, a lateral cephalogram was taken as part of the routine clinical recording. The following inclusion criteria were applied: (1) age between 20 and 45 years; (2) absence of anomalies of the vertebrae; (3) good general health; (4) no history of trauma at the cervical region; and (5) white Italians. Exclusion criteria were radiographs of poor diagnostic quality, subjects with known craniofacial (or other) conditions, or syndromes. Because orthodontic treatment is not expected to influence the maturational process of the cervical vertebrae, 46 subjects with previous orthodontic treatments were also included. A total of 450 subjects (270 females and 180 males) were included in the study (mean age, 30.4 ± 27.3 years; range, 20-45 years).
In the present study, the CVM method, according to Baccetti et al including 6 stages has been applied with minor modifications as previously reported. A quantitative cervical vertebral maturation assessment, based on a customized digitization regimen and analysis with cephalometric software (Viewbox, version 4.0; dHAL Software, Kifissia, Greece) was used for all cephalograms examined in this study. All cephalograms were traced by an operator and checked for accuracy by a second investigator. Moreover, individual CVM codes were retrieved according to the concavities of C2 to C4 and shapes of the C3 and C4, as previously reported. More specifically, lower borders of C2 to C4 were reported as flat (F) or concave (C), whereas the shapes of the C3 and C4 were reported as trapezoidal (T), rectangular horizontal (H), squared (S) and rectangular vertical (V). Each case was defined by a five-letter code; for example, CCF-HS indicates concave C2 and C3, flat C4, rectangular horizontal C3, and square C4. The retrieved CVM codes, either falling within the reported norms (regular cases) or not (exception cases) were also converted into the CVM stages as previously reported. Briefly, the codes CCC-HT, CCC-TH, and CCC-HH were converted into the CVM stage 4, codes CCC-HS, CCC-SH, CCC-SS were converted into the CVM stage 5 and the codes CCC-VS, CCC-SV, CCC-VV were converted into CVM stage 6 (no stages <4 were retrieved, see below).
With the aim of increasing the capability to detect differences in the cervical vertebral maturity, the CVM code was also converted into a CVM score obtained by the sum of individual scores assigned to each concavity or shape of the cervical vertebrae as follow: flat (0), concave (1), trapezoidal (0), rectangular horizontal (1), squared (2) and rectangular vertical. (3) For example, the code CCF-HS was converted into 110-12, accounting for a summative CVM score of 5. From the most immature stage (FFF-TT or 000-00) to the most mature (CCC-VV or 111-33), the CVM score ranges from 0 to 9. As an example, the CVM stage 5 is assumed when at least one of the C3 or C4 has a square shape with the other square too or even less mature (CCC-SH or CCC-HS or CCC-SS). According to the CVM score, when only one is squared and the other rectangular horizontal (CCC-SH or CCC-HS) the score is 6, when both are squared (CCC-SS) the score is 7, when one is squared and the other trapezoidal (CCC-SH or CCC-HS, an exception case) the score would be 5 and so on. Both the .vbr file (for tracing) and the .xls file (for subsequent conversion into the CVM code) used herein are available upon request to the corresponding author.
With the aim of quantifying the full method error of the recordings for each cephalometric parameter, the method of moments variance estimator was used. This variance estimator has the advantages of not being affected by any unknown bias, ie, systematic errors, between pairs of measurements. This analysis was performed on 30 pairs of recordings randomly selected and expressed as mean (95% confidence interval [CI]). The repeatability in both the CVM stage and score assignments in the same pairs of measurements was evaluated using the percentage of agreement, and by both unweighted and linear weighted kappa coefficients presented as mean and 95% CI. The kappa coefficient ranges from 0 for no agreement to 1 for perfect agreement.
Statistical analysis
The SPSS software, version 20 (SPSS Inc, Chicago, Illinois), was used, and exception cases were included in all the analyses. Between the sexes, the significance of the differences in ages, and CVM stages and scores were evaluated by an independent-samples t test and a Mann-Whitney U test, respectively. In the whole sample, the significance of the difference in the degree of maturation between the C3 and C4 (as ordinal data) was evaluated by a Wilcoxon rank-sum test.
Moreover, the adjusted associations of age and sex with either CVM stage or CVM score (separately) were evaluated by multiple ordered logistic regression, which is a regression model for ordinal dependent variables. In particular, the following explanatory variables (categories) were entered in the model: age, sex (females, males). For the CVM stage, 4 was the reference category; for the CVM score, ≤5 was the reference category. The female sex was also considered as a reference category. Briefly, the beta coefficients retrieved by this ordinal regression model are the ordered log odds of being in a more mature CVM stage and score for a single year increase in age or being female as compared with males.
Finally, the significance of the difference between the sexes in the distribution of the different C3 and C4 shapes (taken individually) was evaluated by a chi-square test. A P value <0.05 was used for rejection of the null hypothesis.
Results
The greatest method errors were 0.18 mm (range, 0.14-0.24), 0.55 mm (range, 0.44-0.74), and 4.56° (range, 3.63-6.13), for the concavities and linear and angular measurements, respectively. The overall percentage of agreement for the CVM stages was 88% (22 cases out of 25). The unweighted kappa coefficient was 0.83 (range, 0.65-1.00), and the weighted kappa coefficient was 0.86 (range, 0.70-1.00). The overall percentage of agreement for the CVM scores was 72% (18 cases out of 25). The unweighted kappa coefficient was 0.70 (range, 0.51-0.89), and the weighted kappa coefficient was 0.84 (range, 0.73-0.94).
The ages of females and males (as mean ± standard deviation) were 30.1 ± 6.9 and 30.9 ± 7.8 years, respectively, with no significant difference between the sexes ( P = 0.283). Clinical examples of 6 subjects with full tracings of the C2 to C4 shown in the Figure (cases A to F). In particular, cases A and B show a CVM stage 4, cases C and D show a CVM stage 5, and cases E and F show a CVM stage 6. On the contrary, the CVM scores are all different from 4 to 9.
The frequencies of the cervical vertebral morphology combinations, reported as CVM codes and according to the corresponding CVM stage, are summarized in Table I . Overall, CVM stages from 4 to 6 were retrieved with the CCC-SS combination as the most frequent (38% of the whole sample). More specifically, CVM stage 4, 5 and 6 were seen in 48 (10.7%), 248 (55.1%) and 154 (34.2%) cases. Regular and exception cases were 443 (98.4%) and 7 (1.6%), respectively. The most frequent combinations for CVM stage 4 were CCC-HH (44 cases), for CVM stage 5 was CCC-SS (171 cases), and for CVM stage 6 was CCC-VS (75 cases). In the whole sample, the CVM stage (as median [25th; 75th]) was 5.0 (5.0; 6.0), whereas the median CVM stages were similar between the sexes without significant differences ( P = 0.132), with frequencies summarized in Table II .
CVM | CVM stage | ||
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4 (n = 48) | 5 (n = 248) | 6 (n = 154) | |
Regular cases (n = 443) ∗ | CCC-HH (44) | CCC-SH (67) | CCC-VS (75) |
CCC-TH (1) | CCC-HS (9) | CCC-SV (10) | |
CCC-HT (2) 1 | CCC-SS (171) | CCC-VV (64) | |
Exception cases (n = 7) † | CCC-TT (1) 1 | CCC-ST (1) | CCC-VH (3) |
CCF-VS (1) | |||
CFC-VS (1) |
Sex | CVM stage | Diff | ||
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4 | 5 | 6 | ||
Females | 11.5% (31) | 57.0% (154) | 31.5% (85) | 0.132 ∗ |
Males | 9.4% (17) | 52.2% (94) | 38.3% (69) |
Overall, CVM scores from 4 to 9 were retrieved. More specifically, CVM score ≤5, 6, 7, 8 and 9 were seen in 49 (10.9%), 76 (16.9%), 176 (39.1%), 85 (18.9%) and 64 (14.2%) cases, respectively. With only 1 exception, the CVM score ≤5, was equivalent to the CVM stage 4. In the whole sample, the CVM score [as median (25th; 75th)] was 7.0 (6.0; 8.0), whereas the median CVM scores were similar between the sexes without significant differences ( P = 0.419), with frequencies summarized in Table III .
Sex | CVM score | Diff | ||||
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≤5 | 6 | 7 | 8 | 9 | ||
Females | 11.5% (31) | 15.9% (43) | 41.9% (113) | 17.8% (48) | 13.0% (35) | 0.419 ∗ |
Males | 10.0% (18) | 18.3% (33) | 35.0% (63) | 20.6% (37) | 16.1% (29) |
The results of the ordered multiple regression models are summarized in Table IV . For each of the CVM stages and CVM score neither age nor sex yielded a statistically significant interaction ( P = 0.130, at least).
Dependent variable | Parameter | β (SE) | 95% CI | Significance |
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CVM stage | Age | 0.001 (0.013) | −0.025 to 0.024 | 0.995 ∗ |
Sex (females) | −0.284 (0.188) | −0.653 to 0.084 | 0.130 ∗ | |
CVM score | Age | −0.006 (0.012) | −0.029 to 0.017 | 0.617 ∗ |
Sex (females) | −0.149 (0.174) | −0.490 to 0.191 | 0.391 ∗ |