Dear Editor,
We read with great interest the paper published by Perez-Garcia et al [1] on ‘Is methotrexate safe for men with an immune-mediated inflammatory disease and an active desire to become a father? Results of a prospective cohort study (iFAME-MTX)’. The authors bring original data to address an important and controversial topic regarding the use of MTX in men with immune-mediated inflammatory diseases (IMIDs) who desire to father a child. They prospectively evaluated the testicular toxicity profile of MTX through quantitative and qualitative study of the sperm from treated patients. The strength of this study lies in its prospective design and comprehensive evaluation of various fertility markers in men exposed to MTX such as semen parameters, reproductive hormone levels, sperm DNA fragmentation index, and the presence of MTX-polyglutamates (MTX-PG) in spermatozoa. The author included three distinct groups, namely MTX-starters, MTX-chronic, and healthy controls, to provide a comparative analysis and highlight the impact of both short-term and long-term MTX exposure on male fertility. They observe that MTX exposure in men with IMIDs does not significantly affect conventional semen parameters, reproductive endocrine markers, or sperm DNA fragmentation index. These results provide reassurance regarding the start or continuation of MTX therapy in men planning to father a child, which align with the recent recommendations from the American College of Rheumatology and the British Society for Rheumatology [2]. While this study provides significant insights, it is important to acknowledge some limitations, and mitigate the authors conclusions.

First, the sample size, particularly in the MTX-chronic group, is small (n = 5), which may affect the generalizability of the findings and inadequately represent the diversity of IMID patients receiving chronic MTX therapy. Importantly, small groups lead to insufficient statistical powers and an inability to demonstrate statistical differences. As an example, median spermatozoa concentration is 37x106/mL of sperm in chronic MTX users, whereas it is 60x106/mL in healthy donors or 57x106/mL in IMIDs patients not treated. These numerical differences (38% and 35% decreases, respectively) may reach statistical significance with bigger groups. The study did not provide detailed information on the MTX dosage and treatment duration for the participants. Chronic MTX users may have been on different doses and treatment durations, leading to varying cumulative exposure levels. This information is crucial as the effects on fertility may depend on the total amount of MTX received over time. Without considering cumulative exposure, the conclusion may not accurately reflect the potential impact of long-term MTX use on fertility.

Second, the authors use biological surrogates (concentration of MTX-PG, spermatozoa quantity and morphology, DNA fragmentation index) to evaluate MTX impact on semen. The use of these biological surrogates, although reassuring, cannot replace the evaluation of clinically relevant endpoints that are live birth, birth defect, and developmental abnormality of the child. While MTX-PG is relatively low in spermatozoa, it is high in the seminal fluid, which could impact the newly fertilized egg. A recent meta-analysis graded the evidence on the impact paternal exposure of MTX from “low” to “very low” [3], and a small cohort study has reported birth defect after paternal exposure [4]. Therefore, although the current study brings forward important and reassuring data, we believe that the study abstract conclusion stating that MTX therapy can be safely started or continued in men with a wish to conceive is incompletely supported by the authors data and the current literature. The precautionary principle should be used while good quality clinical data are not available to keep our oath, “Primum non nocere”.

REFERENCES
1 Perez-Garcia LF, Röder E, Krijthe BP, et al. Is methotrexate safe for men with an immune-mediated inflammatory disease and an active desire to become a father? Results of a prospective cohort study (iFAME-MTX). Ann Rheum Dis Published Online First: 1 June 2023. doi:10.1136/ard-2023-224032
2 Russell MD, Dey M, Flint J, et al. British Society for Rheumatology guideline on prescribing drugs in pregnancy and breastfeeding: immunomodulatory anti-rheumatic drugs and corticosteroids. Rheumatology 2023;62:e48–88. doi:10.1093/rheumatology/keac551
3 Mouyis M, Flint JD, Giles IP. Safety of anti-rheumatic drugs in men trying to conceive: A systematic review and analysis of published evidence. Semin Arthritis Rheum 2019;48:911–20. doi:10.1016/j.semarthrit.2018.07.011
4 Saougou I, Markatseli TE, Papagoras C, et al. Fertility in male patients with seronegative spondyloarthropathies treated with infliximab. Joint Bone Spine 2013;80:34–7. doi:10.1016/j.jbspin.2012.03.004

We would like to thank dr. Mahla for his interest in our paper and respond to the questions asked. The first question relates to the included patients, hospitals and countries. We were able to analyze 37,981 patients from 93 hospitals in 17 countries. Information on the included countries, and the number of patients and hospitals per country is provided in the original manuscript in table 1. Hospital latitudes are displayed in figure 1.
As we mentioned in the discussion section, one of the main limitations of our paper is that the number of patients per hospital/country strongly differs and it is impossible to determine to what extent these patients are representative of all patients with RA in a country. Especially in lower- and middle income economies, healthcare disparities may be significant and we were unable to include individual patients’ socioeconomic data . As an example, dr. Mahla mentions India, the country with the largest contribution of patients to our study. We performed a sensitivity analysis excluding India, and found very similar results.
Most countries were represented by only a limited number of hospitals. These were primarily located in cities. Whereas especially in lower income countries these hospitals serve a large area, this may have led to an underrepresentation of patients living in rural areas. We can only speculate on how this may have influenced our findings, which may not only depend on regional and personal socioeconomic circumstances and access to healthcare, but also on intangible factors that we were unable to measure.
Dr. Mahla gives a few examples: healthcare awareness, air pollution, vitamin D deficiency and genetic make-up. Unfortunately, reliable data on these factors were not available at either the patient or hospital level. Other factors such as demographics, age and sex were included in our model but did not satisfactorily explain the association between latitude and age at disease onset.
The final question relates to a stratification of latitude, for countries nearing the equator and for countries with a different socioeconomic status. We used a structural equation model, to assess the association between latitude and age at onset. In this model, we treated latitude as a continuous variable. Only some of the patient factors (ACPA, rheumatoid factor, ever smoking and sex) were included as dichotomous variables. All other variables, including indicators of country level socioeconomic status (e.g. GDP per capita) were treated as continuous variables. No stratified analyses were performed. We also refer to figures 2 and 3 in our original manuscript.
Only 8 hospitals are located in the southern hemisphere, at negative latitude. Since we observed no interaction between latitude and hemisphere (i.e. the association between latitude and age at onset was similar at the northern and southern hemisphere), all negative latitudes were artificially converted into positive latitudes.

We hope this response will contribute to further clarification of our results and conclusion.

Recently, we have been very interested in the article: "Increased risk of osteoarthritis in patients with atopic disease" by Baker et al. [1]. In this article, the author analyzed the incidence of OA in patients with atopic disease in two databases, suggesting that the immune response to atopic illness contributes to the increased incidence of OA. This study provides a new direction for immunotherapy against OA.
Overall, the authors' research design is meticulous. In two different databases, the author divided the idiopathic disease exposure group and the non-exposed group. The author strictly stipulated the sequence of idiopathic diseases and OA to ensure the impact of idiopathic diseases on OA. Matching was performed for age, sex, race/ethnicity, education level, Charlson comorbidity score, follow-up time, and clinic visit frequency, effectively reducing these factors influence. Furthermore, OA risk was reduced after adjusting for BMI in the STARR cohort, confirming that BMI is an independent confounding factor. However, although the authors analyzed various limitations of this study in the Discussion section, there are still some unmentioned issues worth considering.
First, to reduce the influence of confounding factors, the author matched and adjusted multiple independent factors, including age, gender, and BMI. In addition, the impact of factors such as history of joint trauma and physical activity level were mentioned in the discussion section. However, the pathogenesis of OA is complex. In addition to the factors mentioned in the article, the patient's smoking history, drinking history, and other living habits are essential factors affecting OA [2]. These confounding factors may affect the accuracy of the results. In another study, the author mentioned that in sedentary patients, the relationship between atopic dermatitis and osteoarthritis might be closer [3], which suggests that our occupation-related living habits also affect idiopathic diseases and the incidence of OA rate factor.
Second, recall bias is a problem that any retrospective study has to face. The author uses the International Classification of Disease (ICD) code 9 or 10 as the inclusion criteria for the disease. One of the problems here is the need for clinical experience in diagnosing the disease, and there may be differences in the results due to the diagnostic criteria of different ages and the diagnosis of other doctors.
Third, for idiopathic diseases, the authors discuss the contribution of idiopathic dermatitis and asthma to the increased incidence of OA. Idiopathic disease is an immune disease with elevated IgE levels. In addition to idiopathic dermatitis and asthma, joint diseases include hay fever [4]. The article does not discuss hay fever, which may include omitting objectives.
Also, we mentioned some suggestions. To exclude the influence of general lung diseases, the author compared the prevalence of OA in COPD patients and asthma patients, confirmed that COPD and other prevalent lung diseases do not affect the incidence of OA, and further confirmed that OA causes asthma through an immune response. We believe that the comparison between COPD patients and patients with non-idiopathic diseases can be increased, and it can be more directly explained that widespread lung diseases such as COPD do not affect the occurrence of OA. In this study, the impact of pre-existing idiopathic conditions on the event of OA was explored. In the future, whether patients with pre-existing OA will lead to the occurrence of idiopathic diseases is also a direction worthy of research.
We thank the authors again for their contributions and look forward to their responses.

Reference:
[1] M.C. Baker, K. Sheth, R. Lu, D. Lu, E.P. von Kaeppler, A. Bhat, D.T. Felson, W.H. Robinson, Increased risk of osteoarthritis in patients with atopic disease, Ann Rheum Dis 82(6) (2023) 866-872.
[2] J.M. Gwinnutt, M. Wieczorek, A. Balanescu, H.A. Bischoff-Ferrari, A. Boonen, G. Cavalli, S. de Souza, A. de Thurah, T.E. Dorner, R.H. Moe, P. Putrik, J. Rodriguez-Carrio, L. Silva-Fernandez, T. Stamm, K. Walker-Bone, J. Welling, M.I. Zlatkovic-Svenda, F. Guillemin, S.M.M. Verstappen, 2021 EULAR recommendations regarding lifestyle behaviours and work participation to prevent progression of rheumatic and musculoskeletal diseases, Ann Rheum Dis 82(1) (2023) 48-56.
[3] J. Liu, A. Martin, A. Thatiparthi, J.J. Wu, Association between atopic dermatitis and osteoarthritis among US adults in the 1999-2006 NHANES, J Eur Acad Dermatol Venereol 35(6) (2021) e375-e377.
[4] M. Rudwaleit, B. Andermann, R. Alten, H. Sorensen, J. Listing, A. Zink, J. Sieper, J. Braun, Atopic disorders in ankylosing spondylitis and rheumatoid arthritis, Ann Rheum Dis 61(11) (2002) 968-74.

We read with interest the article by Kristensen et al. based on primary ORAL Surveillance results (NCT02092467) enrolling rheumatoid arthritis (RA) patients aged ≥50 years and with ≥1 additional cardiovascular risk factor, who were treated with tofacitinib or tumor necrosis factor inhibitors [1,2]. According to the presence of age ≥65 years or smoking, two subpopulations (i.e., ’high-risk’ and ’low-risk’) were identified, among those receiving tofacitinib, with diverse relative event risk (i.e., malignancies, major cardiovascular events, myocardial infarction, venous thromboembolism, and all-cause death) [1].
One feature highlighted by Kristensen et al. is the increased risk of event in RA patients aged ≥ 65 years [1]. This elderly subpopulation comprises both elderly-onset RA patients, manifesting after the age of 60 years, and those patients diagnosed with RA early in life who naturally become members of this subset. The management of elderly RA patients may be challenging [3]. In fact, the typical high prevalence of comorbidities in these patients may be associated with a lower response to RA therapies and poor prognosis. Furthermore, the concomitant polypharmacy may make even more difficult the treatment of elderly patients due to increased likelihood of drug interactions, adverse events, and possible contraindications [3]. The increased frailty associated with older age may also complicate the management of such patients; this is a syndrome characterised by a decrease of strength, reduced physiological function, and increased individual vulnerability [4]. In addition, elderly RA patients appear to have a diverse biological profile, at least partially, showing higher IL-6 and lower TNF levels in association with senescent T cells [5,6]. An impaired JAK/STAT pathway signalling has been also shown in immune cells of older patients [5,6]. Interestingly, a defective regulatory JAK/STAT cytokine signalling could be associated to a reduced response capacity of T cell subsets [5,6]. Thus, an immunological link could be suggested between rheumatoid inflammation in elderly patients and decreased immune cell responsiveness in JAK/STAT pathway. Although further studies are needed to clarify this issue, this immunological profile could partially explain an increased risk of the event in elderly RA patients treated with tofacitinib, described by Kristensen et al. [1].
Another feature highlighted by Kristensen et al. is the role of smoking habit in this context [1]. The exposure of lung to cigarette smoking is associated with increased oxidative stress, apoptosis, development of a proinflammatory state and autoantibody production in rheumatic diseases [7]. The effects of smoking habit may also stimulate the release of reactive oxygen species and reactive nitrogen species. Moreover, cigarette smoking may cause the release of some danger-associated molecular patterns, which in turn may lead to the activation of macrophages, neutrophils, and dendritic cells [7,8]. Furthermore, smoke exposure may enhance the proliferation of T lymphocytes [8]. It has been also reported that smokers may have a decreased NK cell-mediated lytic activity [8]. All these features could contribute to the increased risk of event of RA patients treated with tofacitinib, reported by Kristensen et al. [1].
All things considered, a better patient characterization, also considering the patient clinical characteristics, may be of crucial importance in tailoring RA treatment according to principles of precision medicine [9]. A more accurate patient profiling could indeed improve the clinical benefits simultaneously reducing the potential side effects of any treatment [9,10]. Therefore, a new approach may be suggested leading to a shift from the concept and practical challenge of ‘finding the patient for the trial’ to ‘finding the trial for the patient’ toward patient-centric approach [10].
In conclusion, all these observations about elderly patients and smoking habit may suggest further indications in accurately guiding a benefit/risk assessment about the treatment with tofacitinib in RA.

References:
1. Kristensen LE, Danese S, Yndestad A, et al. Identification of two tofacitinib subpopulations with different relative risk versus TNF inhibitors: an analysis of the open label, randomised controlled study ORAL Surveillance. Ann Rheum Dis 2023:ard-2022-223715. doi: 10.1136/ard-2022-223715. Epub ahead of print.
2. Ytterberg SR, Bhatt DL, Mikuls TR, et al. Cardiovascular and Cancer Risk with Tofacitinib in Rheumatoid Arthritis. N Engl J Med. 2022;386:316-326.
3. Serhal L, Lwin MN, Holroyd C, Edwards CJ. Rheumatoid arthritis in the elderly: Characteristics and treatment considerations. Autoimmun Rev. 2020;19:102528.
4. Khan KT, Hemati K, Donovan AL. Geriatric Physiology and the Frailty Syndrome. Anesthesiol Clin. 2019;37:453-474.
5. Samson LD, Engelfriet P, Verschuren WMM, et al. Impaired JAK-STAT pathway signaling in leukocytes of the frail elderly. Immun Ageing. 2022;19:5.
6. Shen-Orr SS, Furman D, Kidd BA, et al. Defective Signaling in the JAK-STAT Pathway Tracks with Chronic Inflammation and Cardiovascular Risk in Aging Humans. Cell Syst. 2016;3:374-384.e4.
7. Gwinnutt JM, Verstappen SM, Humphreys JH. The impact of lifestyle behaviours, physical activity and smoking on morbidity and mortality in patients with rheumatoid arthritis. Best Pract Res Clin Rheumatol. 2020;34:101562.
8. Arnson Y, Shoenfeld Y, Amital H. Effects of tobacco smoke on immunity, inflammation and autoimmunity. J Autoimmun. 2010;34:J258-65.
9. Giacomelli R, Afeltra A, Bartoloni E, et al. The growing role of precision medicine for the treatment of autoimmune diseases; results of a systematic review of literature and Experts' Consensus. Autoimmun Rev. 2021;20:102738.
10. Pitzalis C, Choy EHS, Buch MH. Transforming clinical trials in rheumatology: towards patient-centric precision medicine. Nat Rev Rheumatol. 2020;16:590-599.

Declarations:
-Ethics approval and consent to participate:
Not applicable.

-Consent for publication:
Not applicable, all the patients’ data are de-identified.

-Availability of data and material:
All data relevant to the study are included in the article.

-Competing interests:
The authors declare that they have no conflicts of interest for this work.

-Funding:
No funding.

-Authors' contributions:
All authors made substantial contributions to the conception or design of the work, the acquisition and interpretation of data. All authors contributed to the critical review and revision of the manuscript and approved the final version. All the authors agreed to be accountable for all aspects of the work.

-Acknowledgements:
None.