Phichayut Phinyo1,2,3, Titinat Maihom3, Areerak Phanphaisarn3, Pakorn Kerdsinchai3, Ekarat Rattarittamrong4, Jayanton Patumanond2, Dumnoensun Pruksakorn5,6,7,8. 1. Department of Family Medicine, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand. 2. Center for Clinical Epidemiology and Clinical Statistics, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand. 3. Musculoskeletal Science and Translational Research (MSTR), Chiang Mai University, Chiang Mai, Thailand. 4. Department of Internal Medicine, Faculty of Medicine, Division of hematology, Chiang Mai University, Chiang Mai, Thailand. 5. Musculoskeletal Science and Translational Research (MSTR), Chiang Mai University, Chiang Mai, Thailand. dumnoensun.p@cmu.ac.th. 6. Biomedical Engineering Institute, Chiang Mai University, Chiang Mai, Thailand. dumnoensun.p@cmu.ac.th. 7. Omics Center for Health Sciences (OCHS), Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand. dumnoensun.p@cmu.ac.th. 8. Department of Orthopedics, Faculty of Medicine, Orthopedic Laboratory and Research Network (OLARN), Chiang Mai University, Chiang Mai, Thailand. dumnoensun.p@cmu.ac.th.
Correction: BMC Primary Care 21, 215 (2020)10.1186/s12875-020-01283-xFollowing publication of the original article [1], the authors identified some errors in the published equation on Table 2, the published Fig. 3 (the estimated odds and likelihood ratio were incorrect due to our mistake in specifying the equation within the calculator), and the discussion part (related to the figure) in the manuscript. The correction details are stated as follows:
Table 2
Multivariable fractional polynomial logistic regression model for diagnostic prediction of multiple myeloma. (imputed dataset with a total n = 586)
Predictor
Covariate transformation
ß
95% CI
P-value
Terms
df
Formula
Intercept
-2.28
-2.63, -1.93
<0.001
Hemoglobin
Out
0
-
-
-
-
Log serum creatinine
Linear
1
Log creatinine-0.0237
1.28
0.80, 1.75
<0.001
Log serum globulin
Linear
4
Log globulin-0.5-0.8714
-92.64
-114.80, -70.49
<0.001
FP2
Log globulin-0.5*Log (Log globulin)-0.2400
-48.14
-60.13, -36.15
<0.001
Log alkaline phosphatase
Linear
1
Log ALP-4.9318
-0.97
-1.38, -0.56
<0.001
Serum calcium
Out
0
-
-
-
-
Fig. 3
The web application interface of the MM-BM DDx model. Three clinical laboratory parameters can be used for prediction of the presence of multiple myeloma
Log (Log globulin) of the 4th entry under Formula column should not be superscripted.Multivariable fractional polynomial logistic regression model for diagnostic prediction of multiple myeloma. (imputed dataset with a total n = 586)Our previous equation embedded within the online web calculator was incorrect. After correction, the model estimated the predicted odds of MM at 0.436 with a positive likelihood ratio of 1.429 (suspected MM) (Fig. 3). Figure 3 was corrected accordingly. The suggestion in the following sentence was also corrected to follow the model’s estimates. The 9th and 10th sentence of the 3rd paragraph on page 9 should read:The model predicted the odds of MM at 0.436 with a positive likelihood ratio of 1.429 (suspected MM) (Fig. 3). Based on that, this patient should have been considered for referral to a hematologist for further work-up and a definitive diagnosis.The web application interface of the MM-BM DDx model. Three clinical laboratory parameters can be used for prediction of the presence of multiple myeloma