Title:New regression equations for predicting human teeth sizes.

Transcription

1 Author's response to reviews Title:New regression equations for predicting human teeth sizes. Authors: Vanessa V Paredes (vanessa.paredes@uv.es) Vera V Paulino (vera.paulino@uv.es) Beatriz B Tarazona (beatriz.tarazona@hotmail.com) Rosa R Cibrian (rosa.m.cibrian@uv.es) Jose Luis JL Gandia (jose.l.gandia@uv.es) Version:4Date:31 December 2014 Author's response to reviews: see over

2 COVER LETTER Mr. John Arvin Failma Journal Editorial Office Biomed Central December 31 th, 2014 Dear Mr. John Arvin Failma; We have revised our article along the lines suggested and deal with the comments of the reviewers. I provided you an annotated list of our replies to the report and all the changes that have been made prior to publication: Yours sincerely Dr. Beatriz Tarazona Corresponding author

3 New regression equations for predicting human tooth sizes. Vanessa V Paredes, Vera V Paulino, Beatriz B Tarazona, Natalia N Zamora, Rosa R Cibrian and Jose Luis JL Gandia Head & Face Medicine We have mistaken the name of an author, I beg you please correct it and change it for the right one. ENGLISH HAS BEEN REVISED. REFEREE 1: MAJOR COMPULSORY REVISIONS: 1. The inclusion criteria does not mention about previous orthodontic treatment. Were all pre-treatment records taken? ANSWER. We have added new inclusion criteria about previous orthodontic treatment. 2. Secondly, there is no information regarding crowding/spacing present in the dental casts. ANSWER. We have added new inclusion criteria about arch discrepancy. 3. The validity of the equations developed has not been tested on a similar but independent sample from the same population. ANSWER. We consider it is a interesting suggestion and we have worked on it. For every 4 regression models, each of the four regression models (UCPM males, UCPM females, males, females) was re- estimated NOT ON TOTAL SAMPLE, BUT ON A PART OF IT (75% approx.). The reestimated equations have been 'tested ' on the unused sample (25%) to verify that the difference between reality and what is predicted by the equation is acceptable. Next table summarizes obtained results; SD residual R 2 Estimated Equation 100% sample Estimated Equation 75% sample 75% sample 25% Sample (Validation) 75% sample 25% sample (Validation) UCPM LI LI males UCPM LI LI females LI LI males females LI LI It can be concluded that: - The re-estimated regression equations for the 75% of the sample are very similar to those obtained for the total sample and developed in the article. - Not surprisingly, the residual SD tends to increase, except for the women, where the setting is even better in the validation sample. - Explicability for loss or decrease in R 2 is only notable for UCPM male, (already is quoted in the article that it was for the lower R 2 ). In short, the estimated equations seem robust, with a reasonable loss when applied to a validation sample, which has not served for its calculation. REFEREE 2: MAJOR COMPULSORY REVISIONS: METHODS 1. A brief description about the digitizing and measuring methods should be provided; do not only refer to the articles Paredes et al and Paredes et al ANSWER. I have better described our digital and measuring method.

4 2. I am not clear exactly how the right and left side values were used in the statistical analyses. ANSWER. Since right and left side values are highly correlated (and non-independent) within individuals, mean of right and left sides was chosen in our statistical comparisons. 3. No information about tests of normality and homogeneity of variance were provided in the text or tables. The Student t-test is a robust statistical tool but is based on a model that makes several assumptions about the data that must be met prior to analysis. The data meet the assumptions of the Student t-test? These assumptions need to be evaluated because the accuracy of the interpretation of the data depends on whether assumptions are violated. Thus, provide the results of normality and homogeneity of variance analyses. Student t-test should be used when the normality and homogeneity of variance are fulfilled, and nonparametric tests should be used when it are not. ANSWER. This sentence has been added Assumptions regarding normality of parameters and homogeneity of variances were checked by means of Kolmogorov- Smirnov and Levene s test respectively. EXPLANATION Despite being a large sample (n = 359), which could ensure the robustness of the results obtained even with deviations from normality, we have performed the checks suggested by the reviewer. We add to the manuscript that has been conducted with the confirmatory result of adjustment to normality and homogeneity of variances (p> 0.05 Kolmogorov- Smirnov and Levene respectively). Next tables (male and female) represent Kolmogorov-Smirnov normality tests for LI, UCPM,, differences between them and Moyers predictions for different percentiles and differences with Tanaka predictions: Prueba de Kolmogorov-Smirnov para una muestra Prueba de Kolmogorov-Smirnov para una muestra N Z de Kolmogorov- Smirnov Sig. asintót. (bilateral) N Z de Kolmogorov- Smirnov Sig. asintót. (bilateral) LI 169,542,931 LI 190,447, ,452, ,514,954 UCPM 169,584,885 UCPM 190,841,479 DIFUCPM_MOY05 161,658,780 DIFUCPM_MOY05 187,713,690 DIFUCPM_MOY15 161,592,875 DIFUCPM_MOY15 187,650,791 DIFUCPM_MOY25 161,592,875 DIFUCPM_MOY25 187,651,790 DIFUCPM_MOY35 161,683,740 DIFUCPM_MOY35 187,651,790 DIFUCPM_MOY50 161,629,823 DIFUCPM_MOY50 187,651,790 DIFUCPM_MOY65 161,592,875 DIFUCPM_MOY65 187,692,724 DIFUCPM_MOY75 161,728,664 DIFUCPM_MOY75 187,675,753 DIFUCPM_MOY85 161,728,664 DIFUCPM_MOY85 187,649,793 DIFUCPM_MOY95 161,649,793 DIFUCPM_MOY95 187,674,755 DIF_MOY05 161,445,989 DIF_MOY ,041,228 DIF_MOY15 161,445,989 DIF_MOY ,232,096 DIF_MOY25 161,376,999 DIF_MOY ,066,206 DIF_MOY35 161,500,964 DIF_MOY ,220,102 DIF_MOY50 161,407,996 DIF_MOY ,060,211 DIF_MOY65 161,551,922 DIF_MOY ,034,235 DIF_MOY75 161,445,989 DIF_MOY ,041,229 DIF_MOY85 161,461,984 DIF_MOY ,197,114 DIF_MOY95 161,450,987 DIF_MOY ,100,178 DIFUCPM_TAN 169,560,912 DIFUCPM_TAN 190,575,896 DIF_TAN 169,377,999 DIF_TAN 190 1,057,214

5 All values p >0,05. To test homoscedasticity assumption, Levene tests have provided the following results. All p- values > 0.05, homogeneity of variances is accepted. Prueba de homogeneidad de la varianza Estadístico de Levene Sig. LI UCPM DIFUCPM_MOY05 DIFUCPM_MOY15 DIFUCPM_MOY25 DIFUCPM_MOY35 DIFUCPM_MOY50 DIFUCPM_MOY65 DIFUCPM_MOY75 DIFUCPM_MOY85 DIFUCPM_MOY95 DIF_MOY05 DIF_MOY15 DIF_MOY25 DIF_MOY35 DIF_MOY50 DIF_MOY65 DIF_MOY75 DIF_MOY85 DIF_MOY95 DIFUCPM_TAN DIF_TAN,659,417,013,910,269,604,008,930,013,908,002,965,002,962,005,941,000,988,016,899,041,840,022,883,163,686,096,757,128,721,184,668,159,691,154,695,134,715,173,678,162,688,004,950,206,650

6 The assumption regarding the validity of the regression models have also been made. For example, regarding the normality of residuals, this has been the result obtained for the 4 models (UCPM male, UCPM female, male, female): Prueba de Kolmogorov-Smirnov para una muestra Z de KolmogorovSmirnov N Sig. asintót. (bilateral) UCPM male Unstandardized Residual 169,584,884 UCPM female Unstandardized Residual 190,378,999 male Unstandardized Residual 169,415,995 female Unstandardized Residual 190,932,350 In the following graphs shows that the variability of the residue is independent of the level predictions UCPM and in the previous 4 models. No problems of heteroscedasticity. It was also estimated for each model, the Durbin-Watson, to ensure the independence of the observations (hypothesis of no autocorrelation). The values obtained varied in the range from 1.88 to 1.99, which is consistent with the acceptance of this hypothesis. RESULTS The results of the coefficient of determination (the values showed in Table 4 are between to 0.379) are very low, as well as are lower compared to other studies (see Table 6). Thus, what impact has these

7 equations in the sample study? ANSWER. This consideration is true. However, in Table 6 studies can be grouped into two blocks according to quality level fit. First, Turkish and Indian populations studies and secondly, other studies, where our study, in fact, doesn t especially noted for its degree of fit. OTHER COMMENTS: The approach to develop nation-specific standards is not theoretically sound and from a practical perspective the approach results in methods that are almost impossible to apply and of limited utility. Theoretically: Because the method is developed using a sample from Spain does not mean the method is a meaningful representation of genotypic or phenotype variation. In fact, Spanish is a geo-political category and not a category that has any specific phenotypic or genotypic characteristics. Practically: How does one assess if the unknown in question is Spanish? Considering the ease of which people can travel within the European Union, an unknown individual could be of any European nationality, which in and of itself is meaningless. For example: a sample from North American Whites does not necessarily mean the methods are useful on Americans in particular at the exclusion of citizens from other countries. Or useful at all on anyone for that matter without further testing. ANSWER. On of the inclusion criteria was; Spanish ancestors from at least 1 previous generation (Spanish means people living in Spain, Europe with at least 1 previous generation of Spanish ancestors). According the abstract and the Introduction, the principal aim of the study was to evaluate the applicability of the Moyers and Tanaka-Johnston methods in the study sample, and if these methods produce significant errors in this sample, develop new regression equations. However, the paper does not provide any evidence that the equations developed could be odontometric standards in Spanish population. ANSWER. This has been provided as we show in this paper. The paragraph Among people of various racial and ethnic origins, tooth size differ. Some of the most used methods to predict tooth size of unerupted posterior permanent teeth were developed for North Americans, so the applicability and the effectiveness of these methods in others group are inadequate, hence the need to draw up tables for reach population is completely wrong. As discussed above, Spanish or English or American are a geo-political categories, not biological categories. The authors state that their equations are specific to their sample, but the reason why it is specific is not only due to population differences (biological differences, not ethnic or racial differences; the terms race ethnia etc. does not exist in anthropology. Use more correct terms as ancestry, population group, etc.), but also because the equations are truly specific to the sample given that they are being tested on the same sample that was used to developed them. ANSWER. Terms as Spanish or English or American have been changed for ancestry. MINOR COMPULSORY REVISIONS: METHODS The sections "Methods" and "Statistical analysis" of the manuscript should be a single section called "Material and Methods". ANSWER. The sections "Methods and Statistical analysis" have been changed to Material and Methods. Page 4, last paragraph. The Spanish sample... similar for both genders. Change the term gender by the term sex. ANSWER. The term gender has been changed by the term sex. Move the inter- and inter-examiner results (first paragraph of Statistical analysis ) to the Results section. ANSWER. Inter- and inter-examiner results (first paragraph of Statistical analysis ) has been moved to the Results section. RESULTS According to the Instructions for Authors, each table should be numbered and cited in sequence using Arabic numerals (i.e. Table 1, 2, 3 etc.). ANSWER. Tables are now numbered and cited in the right way according to the instructions for authors. OTHER COMMENTS: I suggest the authors to avoid the use of first-person pronouns (such as We choose..., We decided... or We compare... ). ANSWER. The use of first-person pronouns has been avoided.