Osteoporosis Internationalhttps://doi.org/10.1007/s00198-026-08180-6

LETTER TO THE EDITOR

A rebuttal letter: Author response to: OSIN-D-26-00862: Letter to the Editors: REMS is not just an age and weight calculator

Nicholas Pocock, Maryan Bobelyak, Jan Vaculik, Jan J. Stepan

Received: 23 July 2026 / Accepted: 29 July 2026
© The Author(s), under exclusive licence to the International Osteoporosis Foundation and the Bone Health and Osteoporosis Foundation 2026

Dear Editors,

We thank N Birch and colleagues for their interest in our studies and for contributing additional data on the distribution of REMS-derived measurements within age- and BMI-reference database populations [1].

In our volunteer experiments [2, 3], altering only the entered age or weight, while the underlying skeleton remained unchanged, produced predictable and clinically meaningful changes in REMS-derived BMD. These observations show that demographic inputs materially influence the reported REMS-BMD and Fragility Score. Increasing the number of observations within demographic strata would not change this result.

We agree that studies examining the contribution of the Osteoporosis Score to REMS-derived BMD should include sufficiently large and representative populations. The Osteoporosis Score, derived from proprietary spectral analysis of ultrasound backscatter, is combined with age, sex, and body weight in proprietary equations to generate REMS-BMD values [4-6]. In both our study of 209 clinical subjects [2] and the earlier hip arthroplasty study [3], about 10% of the variability in the REMS-BMS was explained by the Osteoporosis Score. However, the strength of this relationship may vary between populations, as referred to in the large clinical datasets [1, 7, 8], which is therefore of considerable interest. Such variability, however, is expected and does not quantify either the contribution of the ultrasound-derived spectral signal or the weighting assigned to demographic variables within the proprietary algorithm.

Furthermore, it cannot be assumed that the residual variability of the REMS output, not explained by demographic parameters, necessarily represents information derived from bone mass or microarchitecture. Distinguishing other contributions to interindividual variability of BMD determination is fundamental to understanding the relative importance of the ultrasound signal in the REMS algorithm. We therefore continue to believe that greater transparency regarding the relative contributions of demographic modeling and ultrasound-derived spectral information is essential for the appropriate clinical interpretation of REMS-BMD and Fragility Score measurements.

Further independent research, particularly studies with access to the raw ultrasound-derived spectral data and underlying algorithms, will be required to determine the relative contributions of demographic parameters and ultrasound-derived information, related to bone or otherwise, to REMS outputs.

Declarations

Conflicts of interest

None.

References

1. Birch N, Tognarini D, McCloud P, Button P. Letter to the Editors: REMS is not just an age and weight calculator. Osteoporos Int. 2026;OSIN-D-26-00862.
2. Chan D, Chen W, Yabsley E, Pocock N (2026) Demographic determinants of REMS-derived BMD and fragility score. Osteoporos Int. https://doi.org/10.1007/s00198-026-07960-4
3. Bobelyak M, Vaculik J, Stepan JJ (2025) Bone mineral density assessment using radiofrequency echographic multispectrometry (REMS) in patients before and after total hip replacement. Osteoporos Int 36(11):2237-2244. https://doi.org/10.1007/s00198-025-07685-w
4. Conversano F, Franchini R, Greco A, Soloperto G, Chiriaco F, Casciaro E et al (2015) A novel ultrasound methodology for estimating spine mineral density. Ultrasound Med Biol 41(1):281-300. https://doi.org/10.1016/j.ultrasmedbio.2014.08.017
5. Casciaro S, Peccarisi M, Pisani P, Franchini R, Greco A, De Marco T et al (2016) An advanced quantitative echosound methodology for femoral neck densitometry. Ultrasound Med Biol 42(6):1337-56. https://doi.org/10.1016/j.ultrasmedbio.2016.01.024
6. Di Paola M, Gatti D, Viapiana O, Cianferotti L, Cavalli L, Caffarelli C et al (2019) Radiofrequency echographic multispectrometry compared with dual X-ray absorptiometry for osteoporosis diagnosis on lumbar spine and femoral neck. Osteoporos Int 30(2):391-402. https://doi.org/10.1007/s00198-018-4686-3
7. Conversano F, Pisani P, Casciaro S (2026) Methodological clarification and analysis of demographic and anthropometric determinants in the calculation of REMS bone mineral density. Calcif Tissue Int 117(1):85. https://doi.org/10.1007/s00223-026-01547-1
8. Liu RY, Liu E (2026) Correlation between radiofrequency echographic multi-spectrometry (REMS) and dual-energy X-ray absorptiometry (DXA): a systematic review and meta-analysis. Bone 206:117820. https://doi.org/10.1016/j.bone.2026.117820

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Corresponding author

Jan J. Stepan
stepan@revma.cz

Nicholas Pocock
n.pocock@unsw.edu.au

Maryan Bobelyak
mariobobelyak@gmail.com

Jan Vaculik
jan-vaculik@volny.cz

Affiliations

1. Department of Nuclear Medicine, St Vincent’s Hospital, Darlinghurst, Sydney, Australia
2. Orthopedic Department, First Faculty of Medicine, Bulovka Hospital, Charles University, Prague, Czech Republic
3. Third Faculty of Medicine, Charles University, Prague, Czech Republic
4. Department of Rheumatology, First Faculty of Medicine, Charles University, Katerinska 32, Prague 121 08, Czech Republic
5. Institute of Rheumatology, Prague, Czech Republic

Published online: 08 August 2026