Mortality in rheumatoid arthritis patients with pulmonary nontuberculous mycobacterial disease: A retrospective cohort study.

OBJECTIVE: The aim of this study was to compare long-term mortality following diagnosis of pulmonary nontuberculous mycobacterial (NTM) disease between patients with and without rheumatoid arthritis (RA) and to evaluate predictive factors for death outcomes.
METHODS: We reviewed the electronic medical records of all patients who were newly diagnosed with pulmonary NTM disease at participating institutions between August 2009 and December 2018. Patients were followed until death, loss to follow-up, or the end of the study. Taking into consideration the presence of competing risks, we used the cumulative incidence function with Gray's test and Fine-Gray regression analysis for survival analysis.
RESULTS: A total of 225 patients (34 RA patients and 191 non-RA controls) were followed, with a mean time of 47.5 months. Death occurred in 35.3% of RA patients and 25.7% of non-RA patients. An exacerbation of pulmonary NTM disease represented the major cause of death. The estimated cumulative incidence of all-cause death at 5 years was 24% for RA patients and 23% for non-RA patients. For NTM-related death, the 5-year cumulative incidence rate was estimated to be 11% for RA patients and 18% for non-RA patients. Gray's test revealed that long-term mortality estimates were not significantly different between patient groups. Fine-Gray regression analysis showed that the predictive factors for NTM-related death were advanced age (adjusted hazards ratio 7.28 [95% confidence interval 2.91-18.20] for ≥80 years and 3.68 [1.46-9.26] for 70-80 years vs. <70 years), male sex (2.40 [1.29-4.45]), Mycobacterium abscessus complex (4.30 [1.46-12.69] vs. M. avium), and cavitary disease (4.08 [1.70-9.80]).
CONCLUSIONS: RA patients with pulmonary NTM disease were not at greater risk of long-term mortality compared with non-RA patients. Rather, advanced age, male sex, causative NTM species, and cavitary NTM disease should be considered when predicting the outcomes of RA patients with pulmonary NTM disease.

Introduction

Nontuberculous mycobacteria (NTM) are typically opportunistic pathogens that are ubiquitous in natural and man-made environments. While NTM species can cause a wide variety of skin, soft-tissue, and osteoarticular infections as well as superficial lymphadenitis, its most common infection site is the lung [1]. Precise data on the prevalence or incidence of pulmonary NTM disease are limited by the fact that, unlike tuberculosis (TB), NTM disease reporting is not mandatory. Nevertheless, there has been increasing awareness among clinicians that pulmonary NTM disease is becoming more prevalent and can be seen as an emerging public health problem [2, 3]. According to nationwide surveys conducted in industrialized countries, the incidence of TB has decreased or stabilized, but the annual prevalence or incidence rate of pulmonary NTM disease is increasing and now exceeds that of TB [4-9]. In addition, population-based studies conducted in Japan and the United States have reported that the number of NTM-related deaths is increasing, although there is significant geographical variation in each country [10, 11]. In a recent population-based comparative study in Korea, NTM-infected patients had poor prognosis compared with TB patients or the general population [12].

The increased risk of pulmonary NTM disease in patients with rheumatoid arthritis (RA) has been reported worldwide. Compared with non-RA patients, the adjusted hazard ratios (HRs) for RA patients were calculated as 2.07 in Canada and 4.17 to 6.24 in Taiwan [13-15]. A high prevalence of pulmonary complications, such as interstitial lung disease (ILD) and airway disease, is well known in RA patients [16-18], and the risk for developing TB is also higher among RA patients than among the general population [14, 15]. Structural abnormalities in the lungs associated with these conditions are considered one of the major host risk factors for pulmonary NTM disease [19]. In addition, reports of NTM disease are emerging in RA patients undergoing treatment with anti-tumor necrosis factor (anti-TNF) agents [20-23]. In the United States, the crude incidence rate (100,000 person-years [PYs]) of pulmonary NTM disease is significantly higher in the anti-TNF-exposed RA population compared with unexposed RA patients (105 vs. 19.2) and the general population (105 vs. 4.1) [21]. Oral prednisolone was also reported as a risk factor for developing NTM disease in RA patients [19, 23]. It is evident that data on incidence rates and risk factors for the development of pulmonary NTM disease in the RA population is accumulating. Nevertheless, it remains unknown if RA may increase the risk of mortality in patients who have developed pulmonary NTM disease or whether RA-specific factors may be associated with mortality in patients with pulmonary NTM disease.

To address these issues, we performed a retrospective cohort study on RA and non-RA patients who were newly diagnosed with pulmonary NTM disease in the divisions of rheumatology and respiratory medicine of our institutions between August 2009 and December 2018. Taking into consideration the presence of competing risks, we used the cumulative incidence function (CIF) and Gray’s test for survival analysis. We estimated the cumulative incidence rates of all-cause death and NTM-related death over time and compared these mortality estimates between RA and non-RA patients. To evaluate the effect of baseline patient characteristics on death outcome and to calculate an adjusted HR for each predictor variable, we performed Fine-Gray competing risks regression analysis.

Materials and methods

Patients

The present study included all RA patients who were newly diagnosed with pulmonary NTM disease in the rheumatology divisions of the following community hospitals in Japan between August 2009 and December 2018: National Hospital Organization (NHO) Kumamoto Saishun Medical Center and Sasebo Chuo Hospital. All patients were required to fulfill the 1987 American College of Rheumatology (ACR) criteria or the 2010 ACR/European League Against Rheumatism (EULAR) criteria for diagnosis of RA [24, 25]. We defined pulmonary NTM disease according to both the 2008 diagnostic criteria of pulmonary NTM disease proposed by the Japanese Society for Tuberculosis (JST) and the Japanese Respiratory Society (JRS) and the 2007 diagnostic criteria for NTM lung disease proposed by the American Thoracic Society (ATS) and the Infectious Disease Society of America (IDSA); namely, patients must have positive culture results from two or more sputum samples obtained separately (or at least one isolation of NTM in the case of bronchoscopy specimens) plus one or more of the following radiological findings: nodular opacities, dissemination of small nodular or branching opacities, homogeneous opacities, cavitary lesions, and bronchiectasis or bronchiolectasis. In addition, other diagnoses must be excluded [26, 27]. As non-RA controls, we registered all patients without RA who were newly diagnosed with pulmonary NTM disease in the respiratory disease division of NHO Kumamoto Saishun Medical Center during the same period. Among non-RA patients in our cohort, only one had a diagnosis of autoimmune rheumatic disease (ANCA-associated vasculitis). Participants in this study were required to be 18 years of age or over.

Study design

We reviewed patients’ electronic medical records to scrutinize clinical data at baseline and during follow-up periods. For each patient, baseline data were obtained at the time when the diagnosis of pulmonary NTM disease was determined, which included demographic characteristics, RA-related data (disease duration, radiological Steinbrocker’s stages, and treatment regimens for RA), comorbidities (type 2 diabetes, malignancy, and ILD), TB history, and laboratory data (serum albumin levels and lymphocyte count). Patient hypoalbuminemia and lymphocytopenia were graded according to the National Cancer Institute’s Common Terminology Criteria for Adverse Events (NCI-CTCAE) version 4.0.

Causative NTM isolates were determined at the same time. RA therapies that patients were receiving when pulmonary NTM was first suspected were deemed before-diagnosis therapies and those that patients decided to continue or start at the time of the diagnosis of pulmonary NTM were deemed after-diagnosis therapies. Follow-up started on the day of pulmonary NTM disease diagnosis and ended with death, loss to follow-up, or the last follow-up visit before February 1, 2020, whichever was first. Patients who missed two or more scheduled visits without any contact were classified as lost to follow-up.

Determination of HRCT patterns of pulmonary NTM disease

For radiological classification of pulmonary NTM disease, we reviewed high-resolution computed tomography (HRCT) images taken when the diagnosis of pulmonary NTM disease was determined. HRCT abnormalities included nodules (centrilobular small nodules and nodules greater than 10 mm in diameter), tree-in-bud sign, airspace consolidation, bronchiectasis/bronchiolectasis, and cavities [28]. Based on the predominant HRCT findings and their distributions, each patient was classified as having one of the following three forms: nodular bronchiectasis (NB) form, fibrocavitary form, and unclassifiable form. The NB form was defined by the presence of multifocal bronchiectasis and clusters of small nodules, which was further classified into cavitary NB and non-cavitary NB according to the presence of cavitary lesions on HRCT. The fibrocavitary form was defined by the presence of cavitary lesions often associated with pleural thickening predominantly in the upper lobes [29]. In this study, cavitary NB form and fibrocavitary form were combined and statistically analyzed as the cavitary disease group because (1) it has been reported that both forms have a similar prognosis [29-31]; (2) we focused on the influence of presence of cavitary lesions on mortality estimates over time; and (3) the number of patients with the fibrocavitary form was small. If the disease did not fall under either the NB form or the fibrocavitary form, it was considered unclassifiable.

Anti-NTM therapy

The following strategy was routinely used as anti-NTM therapy in the participating division. For patients with pulmonary Mycobacterium avium complex (MAC) disease, anti-NTM treatment based on triple therapy was started with clarithromycin (600–800 mg/day), ethambutol (15 mg/kg/day, maximum 750 mg), and rifampicin (10 mg/kg/day, maximum 600 mg) according to the 2012 JST/JRS guidelines for anti-NTM chemotherapy. If necessary, streptomycin or kanamycin was added [32]. For patients with NTM disease caused by other NTM species, treatment regimens were decided by the treating physician. The timing of treatment commencement was decided on a case-by-case basis after due consideration of the risk-and-benefit balance of the treatment. The primary endpoint of treatment was set as 12 months of negative sputum cultures while on therapy [26, 32]. The number of patients who had continued anti-NTM therapy until culture-negative sputum had been maintained for 12 months (completion of anti-NTM therapy) was recorded during follow-up.

For RA patients who were given the diagnosis of pulmonary NTM disease but decided to continue or start RA therapy with a biological disease-modifying antirheumatic drug (bDMARD) or a targeted synthetic DMARD (tsDMARD), anti-NTM drugs were used concomitantly during follow-up under strict physician supervision with full patient compliance.

Cause of death

Primary cause of death, which was defined as the disease or event that started the chain of events that led to death, was determined according to each treating physician’s judgment. NTM-related death was defined as death caused by an exacerbation of pulmonary NTM disease based on radiological findings. Final diagnosis was determined by consensus.

Ethical approval

This study was conducted in accordance with the principles of the Declaration of Helsinki (2008). The protocol of this study also meets the requirements of the Ethical Guidelines for Medical and Health Research Involving Human Subjects, Japan (2014), and has been approved by the Human Research Ethics Committee of the NHO Kumamoto Saishun Medical Center (No. 29-45/29-45-2) and the Institutional Review Board of Sasebo Chuo Hospital (No. 2014–12). Since the study involved a retrospective review of patient records and the data were analyzed anonymously, our ethical committees waived the requirement of patient informed consent to participate.

Statistical analysis

To compare baseline patient characteristics between the RA and non-RA groups, we performed the chi-square test or Fisher’s exact probability test for categorial variables and by the independent-measures t-test for continuous variables. Crude incidence rates of death and 95% confidence intervals (CIs) were calculated by dividing the number of incidence cases by the number of corresponding follow-up PYs overall for both patient groups.

Cumulative incidence of death is defined as the probability that a death event has occurred before a given time. In the present study, we used the CIF to estimate the provability of the occurrence of a death event over time, because we considered the presence of competing risks (namely, lost to follow-up in the survival analysis of all-cause death outcome; lost to follow-up and other-cause death in the survival analysis of NTM-related death outcome). The occurrence of a competing risk event precludes the occurrence of the primary event of interest. In the absence of competing risks, the Kaplan-Meier survival function can be used to estimate the probability of death over time. In the presence of competing risks, however, the simple use of the Kaplan-Meier survival function can overestimate the cumulative incidence probability of all-cause and NTM-related death. To avoid this possibility, we used the CIF instead of the Kaplan-Meier survival function. Gray’s test for the CIF model, with or without the post hoc Holm’s procedure, was used to test the equality of CIF plots among two or three patient groups. Gray’s test is the analogue to the log-rank test that is used for testing the equality of Kaplan-Meier survival curves between groups [33, 34].

Fine-Gray competing risks regression analysis was used to evaluate the effect of each of the baseline patient characteristics on all-cause death and NTM-related death over time and to calculate adjusted HRs with 95% CIs. To reduce the possibility that variables with the clinical relevance and importance might be missed out, we first screened all predictive variables with Gray’s test as univariate analysis. Predictor variables with p-values <0.1 in Gray’s test were then employed in a Fine-Gray regression analysis. To compensate for the small number of death events, a backward stepwise selection with a cut-off significance level of 0.05 was used as the variable selection procedure in the Fine-Gray analysis. The proportional hazards assumption was checked using log-minus-log plots of the log cumulative hazard curve function and scaled Schoenfeld residual plots for exposure variables over time. By calculating the variance inflation factor, we also examined if there was any multicollinearity among predictor variables.

For all tests, probability values (p values) <0.05 were considered to indicate statistical significance. All calculations were performed using PASW Statistics version 22 (SPSS Japan Inc., Tokyo, Japan) and Easy R (Saitama Medical Center, Jichi Medical University, Saitama Japan) [35].

Results

Baseline characteristics of patients who were newly given a diagnosis of pulmonary NTM disease

A total of 225 patients were newly diagnosed with pulmonary NTM disease at participating institutions between August 2009 and December 2018. Baseline characteristics are shown in Table 1. Among them, there were 34 RA patients and 191 non-RA controls. In RA patients, the mean duration of RA was 11.6 years (95% CI 7.7–15.5), and approximately two-thirds were at Steinbrocker’s radiological stages III and IV. All RA patients were receiving pharmaceutical RA therapy; among them, 11 patients (32.4%) and one patient (2.9%) were being treated with a biological DMARD (infliximab, etanercept, adalimumab, abatacept, or tocilizumab) and a tsDMARD (tofacitinib), respectively. Nine RA patients continued or started pharmaceutical therapies with a bDMARD or tofacitinib, together with anti-NTM drugs, after the diagnosis of pulmonary NTM disease was made. Females were predominant in the RA group compared with the control group (88.2% vs. 67.5%). There were no significant differences in rates of comorbidities or past TB. The mean lymphocyte count was lower in RA patients compared with non-RA patients. The most common NTM isolate was M. intracellulare; it was isolated in 50% of RA patients and 67.0% of non-RA patients. M. avium was isolated in 38.2% of RA patients and 24.1% of non-RA patients, and the M. abscessus complex was isolated in 11.8% of RA patients and 5.5% of non-RA patients. In both patient groups, the most predominant HRCT pattern was the non-cavitary NB form (44.1% of RA patients and 42.9% of non-RA patients), followed by the cavitary NB form (29.4% and 28.3%), the unclassifiable form (23.5% and 15.2%), and the fibrocavitary form (2.9% and 13.6%). Cavitary lesions also existed at similar rates on HRCT between the RA and non-RA groups (32.4% vs. 41.9%). There were no significant differences in the rates of other abnormal findings on HRCT scans, such as the tree-in-bud sign, consolidation, nodules, or bronchiectasis/bronchiolectasis. After the diagnosis of pulmonary NTM disease, approximately 45% of patients in both groups completed anti-NTM therapy.

Table 1

Baseline characteristics of patients who were newly diagnosed with pulmonary NTM disease (n = 225).

	RA patients (n = 34)	Non-RA patients (n = 191)	p*
Age, years, mean (95% CI)	70.6 (67.1–74.2)	70.7 (69.1–72.3)	0.98
≥80, number (%)	8 (23.5)	46 (24.1)	1.00
≥70 and <80, number (%)	12 (35.3)	57 (29.8)	0.55
<70, number (%)	14 (41.2)	88 (46.1)	0.71
Male, number (%)	4 (11.8)	62 (32.5)	0.014
RA duration, years, mean (95% CI)	11.6 (7.7–15.5)	–	–
Steinbrocker’s stages III/IV, number (%)	23 (67.6)	–	–
RA therapies†, before/after diagnosis, number (%)	34 (100) / 34 (100)	–	–
MTX therapy	10 (29.4) / 8 (23.5)	–	–
csDMARD (except MTX) therapy	5 (14.7) / 8 (23.5)	–	–
bDMARD therapy (with or without MTX)	11 (32.4) / 8 (23.5)	–	–
tsDMARD therapy (with or without MTX)	1 (2.9) / 1 (2.9)	–	–
No DMARD use (oral steroids and/or NSAIDs)	7 (20.6) / 9 (26.5)	–	–
Comorbidity, number (%)
Type 2 diabetes	4 (11.8)	24 (12.6)	1.00
Malignancy	1 (2.9)	26 (13.6)	0.090
Interstitial lung disease	4 (11.8)	15 (7.9)	0.50
Tuberculosis history, number (%)	1 (2.9)	9 (4.7)	1.00
Serum albumin, g/dl, mean (95% CI)	3.6 (3.4–3.8)	3.8 (3.7–3.8)	0.19
<3.0	4 (11.8)	20 (10.5)	0.77
≥3.0 and <4.0	21 (61.8)	88 (46.1)	0.10
≥4.0	9 (26.5)	83 (43.5)	0.09
Lymphocyte count, /mm3, mean (95% CI)	1195 (1047–1343)	1394 (1320–1468)	0.036
<800	7 (20.6)	21 (11.0)	0.15
≥800 and <1000	5 (14.7)	20 (10.5)	0.55
≥1000	22 (64.7)	150 (78.5)	0.12
Causative NTM species, number (%)
M. avium	13 (38.2)	46 (24.1)	0.093
M. intracellulare	17 (50)	128 (67.0)	0.079
M. abscessus complex	4 (11.8)	11 (5.8)	0.25
Other species‡	0	6 (3.1)	0.60
HRCT patterns of NTM disease, number (%)
Cavitary NB form	10 (29.4)	54 (28.3)	1.00
Non-cavitary NB form	15 (44.1)	82 (42.9)	1.00
Fibrocavitary form	1 (2.9)	26 (13.6)	0.090
Unclassifiable form	8 (23.5)	29 (15.2)	0.22
Presence of abnormal HRCT findings, number (%)
Cavitary lesion	11 (32.4)	80 (41.9)	0.35
Tree-in-bud sign	18 (53.0)	110 (57.6)	0.71
Consolidation	15 (44.1)	77 (40.3)	0.71
Nodules	32 (94.1)	179 (93.7)	1.00
Bronchiectasis/bronchiolectasis	25 (73.5)	159 (83.2)	0.23
Completion rate of anti-NTM therapy§, number (%)	15 (44.1)	87 (45.5)	1.00

Data were obtained at the time of pulmonary NTM disease diagnosis.

*Comparisons of baseline characteristics between the RA and non-RA groups were performed using the chi-square test or Fisher’s exact probability test for categorial variables and by the independent-measures t-test for continuous variables.

†RA therapies represent those that patients were receiving when pulmonary NTM was first suspected (before diagnosis) and those that patients decided to continue or restart at the time of pulmonary NTM disease diagnosis (after diagnosis). bDMARDs included etanercept, infliximab, adalimumab, abatacept, and tocilizumab. csDMARDs included tacrolimus and salazosulfapyridine. tsDMARD was tofacitinib.

‡Other species included M. gordonae (n = 3), M. fortuitum (n = 2), and M. szulgai (n = 1).

§Treatment completion rate was defined as the number (%) of participants who had continued anti-NTM therapy until the primary treatment endpoint (culture-negative sputum for 12 months). This value was determined during follow-up.

RA, rheumatoid arthritis; MTX, methotrexate; DMARD, disease-modifying antirheumatic drug; csDMARD, conventional synthetic DMARD; bDMARD, biological DMARD; tsDMARD, targeted synthetic DMARD; NSAIDs, non-steroidal anti-inflammatory drugs; NTM, nontuberculous mycobacteria; NB form, nodular/bronchiectatic form; HRCT, high-resolution computed tomography.

Mortality in RA and non-RA patients with pulmonary NTM disease

After the diagnosis of pulmonary NTM disease was newly made, patients were followed for a mean time of 47.5 months (95% CI 42.9–52.0). Sixty-nine patients (2 RA patients and 67 non-RA patients) were lost during follow-up. As shown in Table 2, death occurred in a total of 61 patients (12 cases in the RA group and 49 cases in the non-RA group). An exacerbation of pulmonary NTM disease represented the major cause of death in the RA and non-RA patient groups (50% vs. 73.5%, respectively). In RA patients, respiratory failure due to an exacerbation of ILD accounted for one-quarter of the causes of death.

Table 2

Cause of death in patients with pulmonary NTM disease (n = 61).

	RA patients (n = 12)	Non-RA patients (n = 49)
Causes, number (%)
Exacerbation of pulmonary NTM disease	6 (50)	36 (73.5)
Exacerbation of interstitial lung disease	3 (25)	3 (6.1)
Malignancy	0	5 (10.2)
Ischemic heart failure	1 (8.3)	0
Pyelonephritis	1 (8.3)	0
Cerebral infarction	0	1 (2.0)
Subarachnoid hemorrhage	0	1 (2.0)
HCV-related liver cirrhosis	0	1 (2.0)
Gastrointestinal amyloidosis	0	1 (2.0)
Intestinal infectious disease	0	1 (2.0)
Myelodysplastic syndrome	1 (8.3)	0

NTM, nontuberculous mycobacteria; RA rheumatoid arthritis; HCV hepatitis C virus.

As shown in Table 3, the crude incidence rate of all-cause death was 6.9 per 100 PYs (95% CI 3.9–12.1) for RA patients and 6.9 per 100 PYs (95% CI 5.2–9.1) for non-RA patients. For NTM-related death, which was defined as death caused by the exacerbation of pulmonary NTM disease, the crude incidence rate was 3.4 per 100 PYs (95% CI 1.5–7.6) for RA patients and 5.0 per 100 PYs (95% CI 3.6–7.0) for non-RA patients.

Table 3

Mortality in patients with pulmonary NTM disease.

	All patients (n = 225)	RA patients (n = 34)	Non-RA patients (n = 191)
Follow-up*, months, mean (95% CI)	47.5 (42.9–52.0)	61.7 (67.1–74.2)	44.9 (40.0–49.8)
Lost to follow-up, number (%)	69 (30.7)	2 (5.9)	67 (35.1)
All-cause death, number (%)	61 (27.1)	12 (35.3)	49 (25.7)
Crude incidence rate per 100 PYs (95% CI)	6.9 (5.3–8.8)	6.9 (3.9–12.1)	6.9 (5.2–9.1)
Cumulative incidence at 5 years (95% CI) †	0.22 (0.17–0.28)	0.24 (0.10–0.41)	0.23 (0.17–0.29)
NTM-related death‡, number (%)	42 (18.7)	6 (17.6)	36 (18.8)
Crude incidence rate per 100 PYs (95% CI)	5.1 (3.8–6.8)	3.4 (1.5–7.6)	5.0 (3.6–7.0)
Cumulative incidence at 5 years (95% CI) †	0.16 (0.11–0.22)	0.11 (0.03–0.29)	0.18 (0.12–0.24)

* Follow-up was measured from the diagnosis of pulmonary NTM disease.

†Cumulative incidences of all-cause death and NTM-related death at 5 years (5-year mortality rates) were estimated by the CIF. Gray’s test was used for comparisons of mortality estimates over time between RA patients and non-RA patients (p = 0.36 for all-cause death and p = 0.77 for NTM-related death).

‡NTM-related death was defined as death caused by an exacerbation of the pulmonary NTM disease shown in Table 2.

NTM, nontuberculous, mycobacteria; RA rheumatoid arthritis; PYs, patient-years; CIF, cumulative incidence function; CI, confidence interval.

According to the CIF, which was based on a competing risks model, the overall 5-year cumulative death probability was estimated to be 24% for RA patients and 23% for non-RA patients: the cumulative incidence of all-cause death at 5 years was 0.24 (95% CI 0.10–0.41) for RA patients and 0.23 (95% CI 0.17–0.29) for non-RA patients (Table 3). There were no significant differences in mortality estimates over time between patient groups (p = 0.36 with Gray’s test). Similarly, the cumulative incidence of NTM-related death at 5 years was not significantly different between RA patients and non-RA patients (0.11 [95% CI 0.03–0.29] vs. 0.18 [95% CI 0.12–0.24], p = 0.77). CIF plots for NTM-related death and all-cause death in RA and non-RA patients are shown in Fig 1.

Fig 1

Cumulative incidence of NTM-related death and all-cause death in RA and non-RA patients.

Using the CIF, the cumulative incidence of NTM-related death (A) and all-cause death (B) in patients who were newly given a diagnosis of pulmonary NTM disease is shown in the RA and non-RA groups. Numbers below these figures represent the number of patients at risk. The cumulative incidence of death over time between both groups was compared using Gray’s test. According to univariate Fine-Gray analyses, the unadjusted HR (95% CI) of RA versus non-RA was 0.86 (0.38–1.98, p = 0.73) for NTM-related death and 1.34 (0.75–2.40, p = 0.32) for all-cause death. RA, rheumatoid arthritis; NTM, nontuberculous mycobacterial disease; CIF, cumulative incidence function; HR, hazard ratio; CI, confidence interval.

Characteristics of death cases in RA patients who developed pulmonary NTM disease during RA treatment

The characteristics of the death cases among RA patients are shown in Table 4. Four cases were receiving a bDMARD when pulmonary NTM was first suspected (before diagnosis; cases 1, 3, 5, and 11). All patients who decided to continue or start RA therapy with biological DMARDs at the start of follow-up concomitantly received anti-NTM therapy (cases 1, 6, and 11). Anti-NTM therapy was completed according to the ATS/IDSA and JST/JRS guidelines in five death cases (cases 1, 3, 5, 7, and 8). During the follow-up period, 55% of patients with advanced age (≥70 years) at baseline, 50% of males, 75% of patients with coexisting ILD, 50% of patients with causative M. abscessus complex, and 63.6% of patients with cavitary disease at baseline eventually died. Fig 2 shows HRCT scans of case 5 in which the patient died due to an exacerbation of pulmonary NTM disease 61 months after the NTM diagnosis.

Table 4

Characteristics of RA patients who were newly diagnosed with pulmonary NTM disease and eventually died during follow-up.

Case no.	Age/Sex	Causes of death	HRCT patterns of NTM	NTM species	Lung comorbidities‡	Survival periods (months)*	RA therapies†
							before	after
1	80F	NTM exacerbation	Cavitary NB	M. intracellulare	–	80	MTX/ETN	MTX/ETN
2	75F	UIP exacerbation	Unclassifiable	M. intracellulare	UIP	2	TAC	TAC
3	78F	UIP exacerbation	Non-cavitary NB	M. avium	UIP	26	TCZ	TAC
4	70F	NTM exacerbation	Non-cavitary NB	Mab	–	27	MTX	MTX
5	84F	NTM exacerbation	Cavitary NB	M. intracellulare	–	61	ETN	TAC
6	84F	NTM exacerbation	Cavitary NB	M. intracellulare	–	45	MTX	ABT
7	76M	NTM exacerbation	Cavitary NB	M. intracellulare	–	69	SASP	SASP
8	80F	Heart failure	Unclassifiable	M. intracellulare	–	52	Steroid	Steroid
9	79F	UIP exacerbation	Fibrocavitary	Mab	UIP	19	Steroid	Steroid
10	81F	Pyelonephritis	Non-cavitary NB	M. avium	–	108	TAC	TAC
11	43M	NTM exacerbation	Cavitary NB	M. avium	–	77	MTX/ETN	ABT
12	80F	Myelodysplasia	Cavitary NB	M. intracellulare	–	92	MTX	MTX

*Survival periods represent time intervals between diagnosis of pulmonary NTM disease and death.

†RA therapies represent those that patients were receiving when pulmonary NTM disease was first suspected (before diagnosis) and those that patients decided to continue or start at the time of pulmonary NTM disease diagnosis (after diagnosis).

‡No patients had past TB.

RA, rheumatoid arthritis; NTM nontuberculous mycobacteria; TB, tuberculosis; Mab, M. abscessus complex; NB, nodular/bronchiectatic; UIP, unusual interstitial pneumonia; MTX, methotrexate; TAC, tacrolimus; SASP, salazosulfapyridine; ETN, etanercept; TCZ, tocilizumab; ABT, abatacept.

Fig 2

HRCT scans of a patient with the cavitary NB form (case 5).

(A) An HRCT scan taken at the time of diagnosis of pulmonary NTM disease. Nodules and ground-glass opacities are evident in both lungs. Consolidation is evident in the right middle lobe (S4). In addition, bronchiectasis, the tree-in-bud sign, and cavitary lesions are evident in the lingular segment of the left upper lobe (S4). (B) An HRCT scan taken 8 months before the patient died. Extensive nodular opacities are evident in both lungs. Bronchiectasis, the tree-in-bud sign, and cavitary lesions are prominent in the right middle lobe, the lingular, and the left lower lobe.

Predictive factors for mortality in patients with pulmonary NTM disease

As shown in Table 3, there was no significant difference in mortality estimates of all-cause death or NTM-related death over time between RA and non-RA patients. We next compared mortality estimates over time between groups of patients classified according to each of the predictor variables. Estimates of cumulative incidence of all-cause death and NTM-related death over time in each group were computed using CIF and compared with Gray’s test (Table 5). For all-cause death, advanced age (≥70 years), male sex, ILD, past TB, hypoalbuminemia (<3.0 d/dl), lymphocytopenia (<800/mm3), M. abscessus complex, the presence of cavitary disease (cavitary NB/fibrocavitary form), and abnormal HRCT findings (cavitary lesion and consolidation) were identified as variables significantly associated with mortality estimates over time. For NTM-related death, advanced age (≥70 years), male sex, hypoalbuminemia (<3.0 g/dl), lymphocytopenia (<800/mm3), M. abscessus complex, the presence of cavitary disease (cavitary NB/fibrocavitary form), and abnormal HRCT findings (cavitary lesion) were identified as factors significantly associated with mortality estimates over time. CIF plots grouped according to age, sex, NTM species, and HRCT forms are shown in Fig 3.

Table 5

Comparisons of mortality estimates over time between patient groups classified according to each predictor variable.

Predictor variables	p values
	All-cause death	NTM-related death
Age (years)
≥80	<0.001	<0.001
≥70 and <80	0.001	0.002
<70 (reference)	–	–
Sex (male vs. female)	0.002	0.003
RA (yes vs. no)	0.36	0.77
Use of bDMARD or tsDMARD
Prior to diagnosis (yes vs. no)	0.52	0.50
After diagnosis (yes or no)	0.85	0.32
Type 2 diabetes (yes vs. no)	0.053	0.55
Malignancy (yes vs. no)	0.11	0.25
Interstitial lung disease (yes vs. no)	<0.001	0.17
Tuberculosis history (yes vs. no)	0.003	0.084
Serum albumin, g/dl
<3.0	<0.001	0.023
≥3.0 and <4.0	0.08	0.11
≥4.0 (reference)	–	–
Lymphocyte count, /mm3
<800	<0.001	0.007
≥800 and <1000	0.06	0.04
≥1000 (reference)	–	–
Causative NTM species
M. abscessus complex	0.025	0.004
M. intracellulare	0.27	0.25
M. avium (reference)	–	–
HRCT patterns of NTM disease
Cavitary NB/fibrocavitary form	<0.001	<0.001
Unclassifiable form	0.30	0.93
Non-cavitary NB form (reference)	–	–
Cavitary lesion (yes vs. no)	<0.001	<0.001
Tree-in-bud sign (yes vs. no)	0.050	0.74
Consolidation (yes vs. no)	0.018	0.091
Nodule (yes vs. no)	0.071	0.84
Bronchiectasis (yes vs. no)	0.52	0.44

Mortality estimates (cumulative incidence rates) over time were compared between patient groups using Gray’s test for CIF plots. In the case of multiple comparisons, the post hoc Holm’s procedure was used in the Gray’s test. The completion rate of anti-NTM therapy was unable to be compared in these analyses because this variable was determined during follow-up (i.e., it was a time-varying covariate).

RA, rheumatoid arthritis; DMARD, disease-modifying antirheumatic drug; bDMARD, biological DMARD; tsDMARD, targeted synthetic DMARD; NTM nontuberculous mycobacteria; NB form, nodular/bronchiectatic form; CIF, cumulative incidence function.

Fig 3

Cumulative incidence of NTM-related death grouped by predictive factors.

Using the CIF, the cumulative incidence of NTM-related death in patients who were newly diagnosed with pulmonary NTM disease is shown grouped according to predictive factors for death. Predictive factors included (A) age (≥80 years and 70–80 years vs. <70 years), (B) sex (male vs. female), (C) NTM species (M. abscessus complex [Mab] and M. intracellulare vs. M. avium), and (D) HRCT patterns (cavitary NB/fibrocavitary form and unclassifiable form vs. non-cavitary NB form). Numbers below these figures represent the number of patients at risk. The cumulative incidence of death over time between groups with and without predictive factors was compared using Gray’s test with or without the post hoc Holm’s procedure. NTM, nontuberculous mycobacterial disease; Mab, M. abscessus complex; NB, nodular bronchiectatic form; FC form, fibrocavitary form; CIF, cumulative incidence function.

All predictor variables with p values <0.1 in Gray’s test were run through Fine-Gray competing risks regression analysis. The adjusted HRs (95% CI) for the predictor variables of all-cause death and NTM-related death are shown in Table 6. Advanced age (adjusted HR 3.79 [95% CI 1.82–7.89] for ≥80 years and 2.56 [1.27–5.16] for ≥70 and <80 years vs. <70 years), male sex (2.20 [1.27–5.16]), serum albumin <3.0 g/dl (3.16 [1.34–7.44] vs. ≥4.0 g/dl), lymphocyte count <800/mm3 (2.84 [1.41–5.72] vs. 1000/mm3), and cavitary disease (cavitary NB/fibrocavitary form 2.92 [1.51–5.65] vs. non-cavitary NB form) were identified as significant predictive factors for all-cause death in pulmonary NTM disease patients. For NTM-related death, the predictive factors were advanced age (adjusted HR 7.28 [95% CI 2.91–18.20] for ≥80 years and 3.68 [1.46–9.26] for 70–80 years vs. <70 years), male sex (2.40 [1.29–4.45]), M. abscessus complex (4.30 [1.46–12.69] vs. M. avium), and cavitary disease (cavitary NB/fibrocavitary form 4.08 [1.70–9.80] vs. non-cavitary NB form). We also performed Fine-Gray competing risks regression analyses for all-cause and NTM-related death using the forced-entry method. Data are shown in S1 Table. We confirmed that there was neither multicollinearity nor violation of the proportional hazards assumption in these predictive factors.

Table 6

Predictive factors for mortality in patients with pulmonary NTM disease.

Predictor variables	All-cause death		NTM-related death
	Adjusted HRs (95% CIs) *	p	Adjusted HRs (95% CIs) *	p
Age, years
≥80	3.79 (1.82–7.89)	<0.001	7.28 (2.91–18.20)	<0.001
≥70 and <80	2.56 (1.27–5.16)	0.008	3.68 (1.46–9.26)	0.006
<70	1 (reference)	–	1 (reference)	–
Male vs. female	2.20 (1.21–3.99)	0.010	2.40 (1.29–4.45)	0.006
Serum albumin, g/dl
<3.0	3.16 (1.34–7.44)	0.009	–	–
≥3.0 and <4.0	1.29 (0.66–2.51)	0.46	–	–
≥4.0 (reference)	1 (reference)	–	–	–
Lymphocyte count, /mm3
<800	2.84 (1.41–5.72)	0.003	–	–
≥800 and <1000	1.50 (0.66–3.41)	0.33	–	–
≥1000 (reference)	1 (reference)		–	–
Causative NTM species
M. abscessus complex	–	–	4.30 (1.46–12.69)	0.008
M. intracellulare	–	–	1.36 (0.59–3.13)	0.48
M. avium	–	–	1 (reference)	–
HRCT pattern of NTM disease
Cavitary NB/fibrocavitary form	2.92 (1.51–5.65)	0.002	4.08 (1.70–9.80)	0.002
Unclassifiable form	1.30 (0.44–3.83)	0.63	1.14 (0.31–4.18)	0.84
Non-cavitary NB form (reference)	1 (reference)	–	1 (reference)	–

*Adjusted HRs (95% CIs) are shown for variables that remained in the final Fine-Gray models.

Fine-Gray competing risks analyses were conducted to evaluate the baseline patient characteristics that predict all-cause mortality and NTM-related mortality over time. All predictor variables with p-values <0.1 in Gray’s test shown in Table 5 were included in Fine-Gray regression analyses. Abnormal HRCT findings were not included in these analyses together with HRCT patterns of pulmonary NTM disease because both predictor variables were highly correlated. A backward stepwise selection with a cut-off significance level of 0.05 was used as the variable selection procedure in each regression analysis.

RA, rheumatoid arthritis; NTM nontuberculous mycobacteria; NB form, nodular/bronchiectatic form; HRs, hazard ratios; CIs, confidence intervals.

The completion rate of anti-NTM therapy was similar between all-cause death, NTM-related death, and survival cases (45.9%, 40.5%, and 44.2%, respectively), which suggested that this rate might have little effect on all-cause or NTM-related mortality. We were not able to include this variable in the Fine-Gray analyses because it was determined during follow-up (time-varying covariate).

Discussion

In this retrospective cohort study for patients who were newly diagnosed with pulmonary NTM disease, the crude incidence rate of NTM-related mortality was not greater in the RA group compared with the non-RA group. The estimated cumulative incidence of NTM-related death over time was also similar between groups. Through Fine-Gray competing risks regression analysis, advanced age (≥70 years), male sex, M. abscessus complex, and the presence of cavitary disease were identified as the predictive factors for NTM-related death. Similarly, there was no significant difference in crude incidence rates or longitudinal mortality estimates of all-cause death between RA and non-RA patient groups. The predictive factors for all-cause mortality were advanced age (≥70 years), male sex, hypoalbuminemia, lymphocytopenia, and the presence of cavitary disease.

There remains a dearth of information regarding incidence rates and predictive factors of NTM-related death in RA patients who have developed pulmonary NTM disease. Yamakawa et al. reported that, during a median follow-up of 4.4 years, all-cause death occurred in 38 out of 98 RA patients (38.8%) who were newly diagnosed with pulmonary NTM disease at a single center in Japan between 1993 and 2011, with a cumulative incidence rate of 0.34 at 5 years [31]. They also demonstrated that the presence of cavitary disease (cavitary NB/fibrocavitary form) was a negative prognostic factor for all-cause mortality. Although the incidence rate of NTM-related death was not determined in that study, the results were not inconsistent with our findings. In the present study, 35.3% of RA patients died from any cause during follow-up with a mean of 61.7 months, and when focused on RA patients with cavitary disease at baseline, 63.6% had a death outcome. In a case-control study for RA patients with and without NTM disease who were identified at a single center in Taiwan between 2001 and 2014, Liao et al. showed that eight out of 50 RA patients (16%) died a mean of 1.1 years after NTM infection, and among them, 6 cases had pulmonary NTM disease. Male gender and advanced age were factors associated with mortality [19].

There have been several studies focusing on patients under treatment with bDMARDs. By reviewing data from Northern California Kaiser Permanente, Winthrop et al. identified 18 patients with NTM disease who had received anti-TNF therapy between 2000 and 2008, and found that seven patients (39%) died with a median time between infection and death of 569 days [21]. Among the death cases, five continued to receive anti-TNF agents after the diagnosis of NTM disease. It is uncertain whether or not they received anti-NTM therapy concomitantly. In a retrospective chart review of 13 patients who had developed pulmonary NTM disease during bDMARD therapy for RA, Mori et al. showed that, following the discontinuation of bDMARDs, most patients responded to anti-NTM therapy and no deterioration of radiological findings was observed in any patients [28]. In a case series study of 11 patients with RA receiving bDMARDs after diagnosis of pulmonary NTM disease, Yamakawa et al. showed that radiological deterioration was not observed in the majority (64%) of these patients. In some patients undergoing anti-NTM therapy, radiological outcomes of NTM disease were favorable [36]. Several cases of the successful continuation or start of bDMARDs after diagnosis of pulmonary NTM disease have also been reported, in which adequate anti-NTM drugs were concomitantly used during bDMARD therapy [20, 37, 38]. In the present study, the continuation or start of bDMARD or tsDMARD after the diagnosis of NTM disease was not identified as a factor associated with estimates of all-cause or NTM-related mortality over time, which might be explained by the strict instruction related to the concomitant use of anti-NTM drugs. Although the use of bDMARDs has been recognized as a risk factor for the development of NTM disease, it seems unlikely to increase the risk of death in RA patients concomitantly receiving anti-NTM therapy. The survival benefits of the long-term use of a macrolide as anti-NTM therapy to patients with NTM infection were recently reported [12].

Through a systematic review of patients with pulmonary MAC disease, Diel et al. identified 14 eligible studies from the literature up to August 2017, and showed that the pooled estimate of 5-year all-cause mortality was 0.27 [39]. A high degree of heterogeneity was observed across studies, ranging from 0.1 to 0.48. Predictive factors of all-cause mortality consistent across studies included male sex, presence of comorbidities, and advanced age. In addition, several studies reported a higher risk of death in patients with cavitary NTM disease [29, 30, 40–43]. Hypoalbuminemia and lymphocytopenia were also reported as predictors of overall mortality [41, 43]. In a most recent retrospective study including 1445 patients newly diagnosed with pulmonary NTM disease caused by MAC or M. abscessus between 1997 and 2013 at a single referral hospital in South Korea, Jhun et al. reported that the 5-, 10-, and 15-year cumulative all-cause mortality rates were 0.12, 0.24, and 0.36, respectively [44]. Causative NTM species (M. abscessus), cavitary disease, and some demographic characteristics such as advanced age and male sex were significantly associated with long-term all-cause mortality. Through an analysis of the nationwide database of South Korean National Health Insurance, Lee et al. showed that the overall 6-, 10-, and 14-years cumulative survival probabilities were 75.1%, 65.4%, and 57.0%, respectively [12]. Advanced age, male gender, provincial area, and comorbidities were significant factors associated with the mortality of NTM infection. In the present study, the cumulative incidence of all-cause death at 5 years was estimated to be 0.22, and similar baseline variables to those studies were identified as the predictive factors for death outcomes.

Several studies showed that respiratory comorbidities, particularly ILD, emphysema, past TB, and chronic obstructive pulmonary disease (COPD), were predictive factors for all-cause death in patients with pulmonary NTM disease, although their effect was less potent compared with advanced age and male gender [12, 30]. Mirsaeidi et al. indicated that compared to TB-related mortality, COPD, bronchiectasis, and ILD were significantly more common in patients with NTM-related death [11]. Diel et al. showed that the mortality rate was significantly higher in COPD patients with pulmonary NTM disease compared with those without NTM disease [45]. For RA patients, Yamakawa et al. indicated that underlying lung disease was present in 50% of patients (16% for ILD, 9% for emphysema, 7% for past TB, and 7% for bronchiolitis). Survival probabilities were significantly different between patients with usual interstitial pneumonia or emphysema and those without underlying lung disease. In a Cox regression analysis, however, these comorbidities were not identified as prognostic factors for all-cause mortality [31]. In the present study, ILD and past TB were factors associated with all-cause death in univariate analyses, but did not remain as predictive factors in multivariate Fine-Gray regression analysis. Although patients with chronic pulmonary disease apparently have an increased risk of developing pulmonary NTM disease [4, 5, 7, 46], patient demographical characteristics, causative NTM species, and the presence of cavitary disease appear to contribute more to mortality in pulmonary NTM patients.

In the present study, the mortality estimates of NTM-related or all-cause death in RA patients were not significantly different between RA patients and non-RA patients, which might be explained by the similarity in baseline patient characteristics (age, comorbidities, and laboratory data) as well as characteristics of NTM disease (NTM species and HRCT patterns) between both patient groups in our cohort. The predominance of female RA patients may have contributed to this result. Although it is well recognized that the risk of the development of pulmonary NTM disease is higher in RA patients compared with non-RA patients [13-15], pulmonary NTM disease may have similar clinical features, prognostic factors, and outcomes between RA and non-RA patients.

There are several limitations to this study. First, this study was conducted in two community hospitals located in the Kyushu region of Japan. Therefore, our results may not be generalizable to other geographical areas. In addition, our institutions are tertiary referral centers and, therefore, selection bias cannot be entirely excluded. Second, the number of RA patients who had been newly diagnosed with pulmonary NTM disease was small in this study. Therefore, it is unlikely that the study reflects the complete characteristics of pulmonary NTM disease occurring in RA patients. Large-scale population-based registry studies are warranted to confirm our results. Third, since the main aim of the present study was not to evaluate radiological deterioration on serial HRCT scans following the diagnosis of pulmonary NTM disease, we did not calculate the detailed scores for each of the abnormal HRCT findings according to the scoring system for quantification of the extent of NTM disease [47, 48]. Therefore, we refrained from adopting each of these abnormalities for Fine-Gray regression analysis as predictor variables. Fourth, we could not include the rate of completion of anti-NTM therapy in survival analyses, because this variable was determined after starting follow-up (i.e., it was a time-varying variable). However, the similar completion rate observed in this study may suggest that this rate might have little effect on all-cause or NTM-related mortality. Finally, this was a retrospective cohort study, which may confer certain inherent limitations. Some clinical and laboratory findings were not available. Body mass index, which has been reported to be associated with poor prognosis in the general population [30, 41, 43, 44], was not always measured at the time when the definitive diagnosis of pulmonary NTM disease was made.

Conclusions

According to Fine-Gray competing risks regression analysis, advanced age (≥70 years), male sex, M. abscessus complex as the causative species, and the presence of cavitary disease were the predictive factors for NTM-related death in patients who were newly diagnosed with pulmonary NTM disease. Contrary to our expectations, RA patients with pulmonary NTM disease did not exhibit a greater risk of long-term mortality compared with non-RA patients. When predicting NTM disease outcomes in RA patients, clinicians should instead consider patients’ demographical characteristics, causative NTM species, and the presence of cavitary disease, all of which have been generally recognized as the predictive factors for mortality in patients with pulmonary NTM disease.References

Predictive factors for mortality in patients with pulmonary NTM disease (Fine-Gray models using a forced-entry method).

(DOC)

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2 Oct 2020

PONE-D-20-28997

Mortality in rheumatoid arthritis patients with pulmonary nontuberculous mycobacterial disease: A longitudinal cohort study

PLOS ONE

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Reviewer #1: Mori et al. examined the mortality in rheumatoid arthritis (RA) patients with pulmonary nontuberculous mycobacterial (NTM) disease by a retrospective study. The authors should elucidate the following issues:

1. The title is not incorrect but misleading, because this is a retrospective study.

2. Non-RA controls must be specified. Did they include patients with other rheumatic diseases such as Sjögren syndrome (Chao et al. BMC Infectious Diseases 2017) and others (Takenaka et al. Mod Rheumatol 2020)? Because this article did not describe laboratory data such as serum albumin level (Kim et al. BMC Pulmonary Medicine 2017) and lymphocyte count (Hirose et al. Mod Rheumatol 2019), the description of controls is crucial.

3. Some descriptions in Statistical analysis section may be moved to elsewhere.

4. Death caused by the exacerbation of pulmonary NTM disease may be demonstrated by the chest images.

5. Figure 1 and 2: The labeling for the y-axis should be improved for the understanding without figure legends.

6. The identification of age ≥80 as a mortality predictor is universal and clinically meaningless. How about ≥70?

Reviewer #2: Mori et al. analyzed newly diagnosed 225 pulmonary NTM cases to clarify the predictive factors of death outcomes. They focused on the differences between cases with/without RA. The methodologies and statistical analyses are suitable, and the manuscript is well written. However, the conclusions were the same as the previous studies, and there are several concerns in this manuscript.

#. I understand that the authors tried to clarify whether RA could influence on the NTM mortality. However, the number of cases in this study is too small to generalize the results. Furthermore, the study was conducted in the tertiary hospitals for NTMs and RA. Although they describe geographical area bias as a limitation, the results cannot be generalized, and the population-based or large scare registry studies are warranted.

#. HRCT findings; they analyzed nodules, tree-in-bud sign, and consolidation, but the results were not shown in the results section.

#. Statistic: I am not sure why they used stepwise selection in this study. Please ask a statistician.

#. Ethical; the study was approved in the Kumamoto Saishun Medical Center, but there was no description of the Sasebo Chuo Hospital's approval. What is the meaning of the following sentence? "this has been approved by our ethical committee."

#. In the previous large scale study conducted in South Korea, M. intracellulare was a risk factor for deaths. So it would be better to divide into M. avium and M. intracellulare.

#. M. abscessus should be "M. abscessus complex."

#. Cavitary opacity is better to be "Cavitary lesion."

#. They need to explain the cumulative incidence function in the method section. Similarly, in Line 266, "all-cause death at five years was 0.24". What the unit of 0.24?

#. The footnote of Table 6, Gray's scale test shown in Table "4", and in the following line, NTT should be "NTM."

#. Figure 1B: The cumulative incidence of death in RA cases seems to be increasing after six years.

Reviewer #3: Comments to the Author

Mori al. report a study on the focusing between RA-NTM and non-RA-NTM. This focus of authors is unique and interesting, though this study does not extremely original results.

★comments

Patients with RA have an increased risk of infection compared with the general population. Therefore, I expected the result that survival for patients RA-NTM would worse than those for patients with non-RA-NTM. Because sample size of this study is relatively small, this might lead to those results. However, it is interesting to me.

Authors mentioned that RA patients with p-NTM disease were not greater risk of long-term mortality compared with non-RA patients. In other words, because there was no significant difference of prognosis for NTM as whether RA or not, radiological cavitary disease, older, and male were thought to be important for prognosis of each patient. This matter should be emphasized for more including author’s speculation.

In addition, I thought that the present study may mean to most important factor of comorbidity for chronic pulmonary disease (i.e., interstitial lung disease, pulmonary emphysema, and old pulmonary tuberculosis). I would like you to discuss in this point.

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5 Nov 2020

Response to Reviewers

We are most grateful to the reviewers for their valuable comments. We have made all requested changes and added new information to the manuscript in response to their insightful comments. All alterations are highlighted in red text in the revised version of the manuscript. We are confident that the manuscript has benefited from the reviewers’ useful comments and suggestions.

Below are point-by-point replies to the reviewers’ comments.

Reply to Reviewer 1

1. Thank you for this helpful comment. Since longitudinal studies can be retrospective or prospective, we used “a longitudinal cohort study” in the original title. We understand the reviewer’s concern that this title may be misleading, however. As such, in the revised version, we modified the title as follows: “Mortality in rheumatoid arthritis patients with pulmonary nontuberculous mycobacterial disease: A retrospective cohort study” (lines 2–3). We also added the word “retrospective” to several sentences in the text (lines 88 and 350), for clarity

2. We agree with your comment that we should specialize non-RA controls. Among the non-RA group in this study, only one patient had autoimmune rheumatic disease other than RA (ANCA-associated vasculitis). There were no patients with Sjögren’s syndrome or other rheumatic diseases (systemic lupus erythematosus, dermatomyositis, etc.). This information was added to the Materials and Methods section in the revised version (lines 118–119). In addition, we included baseline serum albumin and lymphocyte count for each patient as predictor variables in the survival analyses for all-cause death and NTM-related death in the revised version. We obtained the following new data: (1) the mean lymphocyte count at baseline was lower in RA patients compared with non-RA patients; (2) in univariate analyses (Gray’s test), hypoalbuminemia (<3.0 g/dl) and lymphocytopenia (<800/mm³) were associated with cumulative incidence probability over time for all-cause death and NTM-related death; (3) according to Fine-Gray regression analyses, hypoalbuminemia and lymphocytopenia were significant predictive factors for all-cause death, not NTM-related death, in pulmonary NTM disease patients. We added new data and information to the text (lines 129–132, 254–255, 315–324, 329–334, 358–360, and 408–409) as well as Tables 1, 5, and 6 of the revised manuscript.

3. We appreciate your suggestion to move some of the descriptions in the Statistical Analysis section. In response to this comment, we removed the descriptions of predictor variables (lines 195–201 of the previous version) and placed some of them in the Results section of the revised version (lines 313–315). All of the predictor variables used in the survival analyses are shown in Table 5.

4. We appreciate your suggestion that exacerbation of pulmonary NTM disease may be demonstrated by chest images. In response to this suggestion, we included HRCT images of a patient with the cavitary nodular/bronchiectatic (NB) form (case 5 in Table 4) as Fig. 2 of the revised version. HRCT scans were taken at the time of diagnosis of pulmonary NTM disease and 8 months before the patient died. This patient discontinued etanercept monotherapy after NTM disease was suspected and completed anti-NTM therapy. Radiological findings were exacerbated, however, and the patient eventually died. In addition, we included several sentences in the revised Results section (lines 306–307) and added the figure legend for Fig. 2 (lines 682–689).

5. We appreciate your comment on the labeling for the y-axis of Figs. 1 and 2 in the previous version. Cumulative incidence of death is defined as the probability that a death event occurs before a given time. In the present study, we used the cumulative incidence function (CIF) instead of the Kaplan–Meier (K–M) survival function to estimate the probability of the occurrence of a death event over time, because we considered the presence of competing risks in the survival analyses (lines 206–211). In the K–M survival curves, “survival probability” or “survival percentage” is often used as the label for the y-axis. In the CIF plots, the software for statistical analysis (Easy R), which we used for this study, labeled the y-axis with “cumulative incidence” with a scale of 0.0–1.0. In the present study, we used “cumulative incidence” to clearly show that the analysis has been done with the CIF (not the K–M function). In response to your comment, we added “probability of all-cause death” or “probability of NTM-related death” to the label for the y-axis of Fig. 1 and “probability of death” to Fig. 3 in the revised version. In addition, we modified several sentences in the abstract and text (lines 39–42 and 284–286).

6. We agree with your comment that age ≥80 years as a predictive factor of death is clinically meaningless. In response to this comment, we categorized the patients into three groups (age ≥80, ≥70 and <80, and <70 years), and then performed survival analyses using age <70 years as a reference. According to the Fine-Gray regression analysis, advanced age (≥80 and 70 – <80) was a significant predictive factor for all-cause death (adjusted HR 3.79 [95% CI 1.82–7.89] for ≥80 years and 2.56 [1.27–5.16] for 70 – <80 years vs. <70 years) and NTM-related death adjusted (HR 7.28 [95% CI 2.91–18.20] for ≥80 years and 3.68 [1.46–9.26] for 70 – <80 years vs. <70 years). We included these results in the abstract and text (lines 43–47, 303, 315–324, 329–338, 353–356, 358–360, and 478–481) of the revised version. We also added new data to Tables 1, 5, and 6. Figure 3A (cumulative incidence of NTM-related death grouped according to age) and its figure legend (lines 694–695) were also modified.

Regarding the data availability, all data underlying the findings in this study are available, without restriction, from the Human Research Ethics Committee of the National Hospital Organization Kumamoto Saishun Medical Center (contact information: Mr. Shunichi Tsutsumiuchi, Control Manager of the Committee, tsutsumiuchi.shunichi.dz@mail.hosp.go.jp) for all interested researchers who meet the criteria for access to confidential data. These data include potentially identifying personal information of individual patients. Data that are not directly identifiable are also inappropriate to share publicly, because, in combination, these data can become identifying, especially data collected from the RA group with NTM disease and the NTM-related death group. Therefore, the Ethics Committee does not recommend that such data be made public unnecessarily. Please understand that these strict rules for protecting participant privacy are imposed on us by the Ethics Committee.

Reply to Reviewer 2

Limitations

We understand your concern about the generalization of this study. As you pointed out, our institutions are tertiary referral centers and, therefore, selection bias cannot be entirely excluded. In addition, the number of RA patients who had been newly diagnosed with pulmonary NTM disease was small in this study. Therefore, it seems unlikely that the study reflects the complete characteristics of pulmonary NTM disease occurring in the RA population. Population-based or large-scale registry studies are warranted. We added these limitations to the Discussion section of the revised version (lines 457–461).

HRCT findings

We appreciate your comment that the results regarding abnormal HRCT findings (tree-in-bud, nodules, and consolidation) were not presented in the previous version. In response to this comment, we added the number of patients with each of these abnormal findings to Table 1 and the Results section (lines 263–265). In addition, we compared the estimated cumulative incidence of death over time between patient groups classified according to each of the abnormal HRCT findings, using the cumulative incidence function (CIF) with Gray’s test. Cavitary lesions and consolidation were variables that were significantly associated with the cumulative incidence of all-cause death. New data were added to Table 5 and the Results section (lines 315–324) of the revised version.

In the present study, we used these abnormal HRCT findings to determine the HRCT patterns of pulmonary NTM disease for each patient according to the predominant findings and their distribution. Since the main aim of the present study was not to evaluate radiological deterioration on serial HRCT scans following the diagnosis of pulmonary NTM disease, we did not calculate the detailed scores for each of the abnormal HRCT findings according to the previously published scoring system for quantification of the extent and severity of NTM disease (refs. 47and 48). In the revised version, we therefore refrained from adopting each of these abnormalities for Fine-Gray regression analysis as predictor variables. We added this limitation to the Discussion section (lines 461–467) of the revised version. New references (refs. 47 and 48) were also added. Instead of using the abnormal HRCT findings, we used the HRCT pattern as a predictive factor in the revised version. The cavitary nodular bronchiectatic (NB) form and fibrocavitary form were combined and statistically analyzed as the cavitary disease group, because (1) it has been reported that both forms have a similar prognosis (refs. 29–31), (2) we focused on the effect of cavitary lesions on mortality estimates over time; and (3) the number of patients with the fibrocavitary form was small. We modified the Materials and Methods section in the revised version (lines 142–147 and 154–159). New data was also included in the Results section (lines 329–338) as well as Tables 5 and 6 in the revised version.

Statistical analysis

We appreciate your comment on the use of the stepwise selection procedure in the Fine-Gray regression analysis. In the present study, the number of death events were 61 for all-cause death and 42 for NTM-related death. In logistic regression and Cox/Fine-Gray regression analyses, it is generally recommended that one predictor variables be studied for every ten events (the one in ten rule: Peduzzi P, et al. J Clin Epidemiol 1996; 49, 1373-9). For smaller ratios of events per predictor variable, the regression coefficients can be biased in both positive and negative directions. In addition, collinearity can be caused by having too many variables in the same regression analysis. In accordance with the one in ten rule, the number of predictor variables in this study should be limited to 6 for all-cause death and 4 for NTM-related death. In the previous version, to compensate for the small number of death events, we used a stepwise selection as the variable selection procedure in the Fine-Gray regression analyses. To avoid missing predictor variables with clinical relevance and importance, we first screened predictive variables with Gray’s test as univariate analysis. As you pointed out, the selection of predictor variables with p < 0.1 led to fulfilment of the one in ten rule in the previous version, and therefore we did not need to use the stepwise selection procedure.

During the revision of the manuscript, however, we found additional predictor variables with p < 0.1 in Gray’s test, and therefore we needed to include them in the Fine-Gray analyses’ nine predictor variables (serum albumin, lymphocyte count, past tuberculosis, age, sex, type 2 diabetes, interstitial lung disease, NTM species, and cavitary disease) for all-cause death and 7 (serum albumin, lymphocyte count, past tuberculosis, age, sex, NTM species, and cavitary disease) for NTM-related death. Therefore, we used backward stepwise selection to construct the final Fine-Gray models in the revised version. To address your concern, we newly included results from Fine-Gray regression analyses without stepwise selection (namely, the use of the forced-entry method) as supplementary Table S1 in the revised version. We added new information regarding Fine-Gray regression analysis to the text of the revised version (lines 223–229 and 338–340).

Ethical approval

First comment:

As you pointed out, the approval of the Ethics Committees of the participating institutions is critical, and we are sorry that this information was insufficient in the previous version. The National Hospital Organization (NHO) Kumamoto Saishun Medical Center and Sasebo Chuo Hospital have collaborated in a number of research projects under the approval of both ethics committees. The protocol of this study has been approved by the Human Research Ethics Committees of the NHO Kumamoto Saishun Medical Center (No. 29-45/29-45-2) and the Institutional Review Board of Sasebo Chuo Hospital (No. 2014-12).

Second comment:

Since the study involved a retrospective review of patient records and the data were analyzed anonymously, our ethical committees waived the requirement of informed consent to participate.

To clarify these points, we modified several sentences in the Ethical Approval section, and provided the approval number issued by the Institutional Review Board of Sasebo Chuo Hospital (lines 191–197).

M. intracellulare and M. avium

We appreciate your comment on the need to divide the M. avium complex (MAC) group into M. intracellulare and M. avium groups. In response to this comment, we performed all statistical analyses after separating M. intracellulare and M. avium groups. New data and information are now included in Tables 1, 4, 5, and 6 as well as Fig. 3 and its figure legend. We modified the abstract and text (lines 43–47, 255–258, and 334–338).

Terminology of M. abscessus

In response to your comment, we changed “M. abscessus” to “M. abscessus complex” throughout the revised manuscript.

Cavitary opacity

In response to your comment, we changed “cavitary opacity” to “cavitary lesion” throughout the revised manuscript.

Regarding the CIF

We wish to thank you for the comment regarding the need to explain the CIF. Cumulative incidence of death is defined as the probability that a death event has occurred before a given time. In the present study, we used the CIF to estimate the provability of the occurrence of a death event over time, because we considered the presence of competing risks. The occurrence of a competing risk event precludes the occurrence of the primary event of interest. In the absence of competing risks, the Kaplan–Meier (K–M) survival function can be used to estimate the probability of death. In the presence of competing risks, however, the simple use of the K-M survival function can overestimate the cumulative incidence provability of all-cause and NTM-related death. To avoid this possibility, we used the CIF instead of the K-M survival function. Gray’s test for the CIF model was used to compare estimates of death incidence over time among two or three patient groups. Gray’s test is the analogue to the log-rank test that is used for testing the equality of K–M survival curves between groups. We added these descriptions to the Materials and Methods section (lines 206–220) of the revised version. New references were also added (refs. 33 and 34).

As mentioned above, the cumulative incidence of death is defined as the probability that a death event has occurred before a given time. In the K–M survival curves, “survival probability” or “survival percentage” is often used as the label for the y-axis. In the CIF plots, the software for statistical analysis (Easy R), which we used for survival analyses in this study, labeled “cumulative incidence” for the y-axis with a scale of 0.0 to 1.0. In the present study, we used “cumulative incidence” to clearly show that the analysis has been done with the CIF (not the K–M function). In response to your comment, we added the following to the Results section of the revised version, “the overall 5-year cumulative death probability was estimated to be 24% for RA patients and 23% for non-RA patients” (lines 284–286). Similarly, we modified the description regarding the cumulative incidence of all-cause death and NTM-related death at 5 years in the Abstract (lines 39–42). We also added the term “probability of all-cause death” or “probability of NTM-related death” to the label of the y-axis of Fig. 1 and “probability of death” to Fig. 3 in the revised version.

Footnote of Table 6

Thank you for pointing out these mistakes. We corrected them in the revised version.

Fig. 1B

We appreciate your comment that the CIF plots seem different between the RA and non-RA groups after 6 years of follow-up. Gray’s test is a method to compare the cumulative incidence of an event of interest over time, not the cumulative incidence of the event occurring at a specific time-point. Accordingly, the impression obtained from the CIF plots and the result of Gray’s test sometimes differ. This is also observed between the impression of K–M curves and the result of the log-rank test. When comparing K–M curves between groups, we can select the log-rank test, generalized Wilcoxon test, or Tarone-Ware test according to the pattern of survival curves. For CIF plots, Gray’s test is the only reliable method to compare the estimated cumulative incidence probability between patient groups. In the revised version, in addition to Gray’s test, we showed the effect of RA on all-cause of death and NTM-related death over time using univariate Fine-Gray regression analyses. The unadjusted HR (95% CI) of RA versus non-RA was 0.86 (0.38–1.98, p = 0.73) for NTM-related death and 1.34 (0.75–2.40, p = 0.32) for all-cause death. These results were added to the figure legend for Fig. 1 (lines 676–678).

Reply to Reviewer 3

We are most grateful for your valuable comments and suggestions. As described in the Introduction section, the increased risk of pulmonary NTM disease in RA patients, compared with non-RA patients, has been reported worldwide. In this context, we expected that RA might increase the risk of mortality in patients who had developed pulmonary NTM disease. In the present study, however, we found that the estimated cumulative incidence probability of NTM-related or all-cause death is not greater in the RA group compared with the non-RA group. RA did not contribute to mortality in our patient cohort. Rather, the generally recognized predictive factors, such as advanced age, male sex, NTM species, and cavitary disease, did, which is the point we would like to emphasize in the present study. These opinions are presented in the Abstract and Conclusion sections of the revised manuscript (lines 48–51 and 481–487).

In the revised version, we discussed a possible reason why the mortality estimates of NTM-related or all-cause death RA patients were not significantly different between RA patients and non-RA patients in this study. This may be explained by the similarity in baseline patient characteristics (age, respiratory or non-respiratory comorbidities, and laboratory data) as well as the characteristics of NTM disease (NTM species and HRCT patterns) between both patient groups in our cohort. The predominance of female RA patients may also have contributed to this result. In addition, the continuation and restart of biological or targeted synthetic antirheumatic drugs appears unlikely to increase the risk of death in RA patients concomitantly receiving anti-NTM therapy. The survival benefits of the long-term use of a macrolide as ani-NTM therapy in patients with NTM infection was reported (ref. 12). Since the number of RA patients who had been newly diagnosed with pulmonary NTM disease was small in this study, however, it is unlikely that the study reflects the complete characteristics of pulmonary NTM disease occurring in RA patients. Large-scale population-based registry studies are warranted to confirm our results. We added this discussion to the revised version (lines 397–401, 444–453, and 457–461). A new reference (ref. 12) was also included in the revised version.

In the revised version, we evaluated the effect of interstitial lung disease (ILD) and past tuberculosis (TB) on the cumulative incidence probabilities of all-cause and NTM-related death. We found that these comorbidities were associated with all-cause death as evidenced by univariate analyses (Table 5), but did not remain as predictive factors in multivariate Fine-Gray regression analysis (Table 6). Several studies showed that respiratory comorbidities, particularly ILD, emphysema, past TB, and chronic obstructive pulmonary disease (COPD), were predictive factors for all-cause death in patients with pulmonary NTM disease, although their effect was less potent compared with advanced age and male gender (refs. 12 and 30). Mirsaeidi et al. showed that compared to TB-related mortality, COPD, bronchiectasis, and ILD were significantly more common in patients with NTM-related death (ref. 11). Diel et al. showed that the mortality rate was significantly higher in COPD patients with pulmonary NTM disease compared with those without NTM disease (ref. 45). For RA patients, Yamakawa et al. indicated that underlying lung disease was present in 50% of patients (ILD, emphysema, past TB, and bronchiolitis). Survival probabilities were significantly different between patients with usual interstitial pneumonia or emphysema and those without underlying lung disease. In a Cox regression analysis, however, these comorbidities were not identified as prognostic factors for all-cause mortality (ref. 31). Although patients with chronic pulmonary disease are apparently exposed to an increased risk of developing pulmonary NTM disease (refs. 4, 5, 7, and 46), patient demographical characteristics, causative NTM species, and the presence of cavitary disease appeared to contribute more to mortality in pulmonary NTM patients. We included this discussion (lines 424–443) and new references (refs. 7, 12, 45, and 46) in the revised version.

During the manuscript revision, a population-based study addressing the mortality and prognostic factors in NTM infection was reported from South Korea (ref. 12). We included the results from this study in the text of the revised version (lines 66-68, 400–401, 416–420, and 424–427).

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16 Nov 2020

Mortality in rheumatoid arthritis patients with pulmonary nontuberculous mycobacterial disease: A retrospective cohort study

PONE-D-20-28997R1

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Reviewer #1: The manuscript has been intensively and adequately revised according to the reviewer's comments, and now it is suitable for publication.

Reviewer #2: The authors address all of the reviewers' comments and the manuscript has been much improved from the original version. I think the study is worth reporting.

Reviewer #3: Mori et al. analyzed pNTM cases to clarify the predictors of outcomes, by focusing between cases with/without RA. This revised manuscript is well written, however, this conclusion was extremely original.

In large-scale study, Hayashi et al. reported that a multivariate Cox proportional hazard model showed male sex, older age, presence of systemic and/or respiratory comorbidity, non-NB radiographic features, body mass index (BMI) less than 18.5 kg/m2, anemia, hypoalbuminemia, and erythrocyte sedimentation rate greater than or equal to 50 mm/h to be negative prognostic factors for all-cause mortality, and FC or FC1NB radiographic features, BMI less than 18.5 kg/m2, anemia, and C-reactive protein greater than or equal to 1.0 mg/dl to be negative prognostic factors for MAC specific mortality. This study included 36 patients with collagen vascular disease of 634 MAC patients. The present study by Mori et al. included 34 RA patients and 191 non-RA patients. Therefore, it would be natural of similar results between this and a previous study. Despite this limitation, I think there is a value in this study because of limited information in RA-NTM.

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18 Nov 2020

PONE-D-20-28997R1

Mortality in rheumatoid arthritis patients with pulmonary nontuberculous mycobacterial disease: A retrospective cohort study

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