Original Research
Frontiers in Tuberculosis ·
Volume 4 - 2026 | https://doi.org/10.3389/ftubr.2026.1740382
Non-tuberculous mycobacteria pulmonary disease in Texas: an analysis of 8 years of hospital discharge data
- Alex Baham1
- Jotam G. Pasipanodya2
- Devanshi Mehta3
- Susan McBride1
- Shashikant Srivastava4,5*corresponding author
- 1Institute for Health Innovations, Data Science, and Research, The University of Texas at Tyler, Tyler, TX, United States
- 2Division of Infectious Diseases, Vanderbilt University Medical Center, Nashville, TN, United States
- 3Section of Pulmonary and Critical Care, Department of Medicine, University of Texas at Tyler School of Medicine, Tyler, TX, United States
- 4Division of Infectious Diseases, Department of Medicine, University of Texas at Tyler School of Medicine, Tyler, TX, United States
- 5Department of Cellular and Molecular Biology, University of Texas Health Science Center at Tyler, Tyler, TX, United States
Abstract
Non-tuberculous mycobacterial (NTM) pulmonary disease (PD) is a recognized chronic condition associated with high healthcare utilization. Texas statewide NTM diagnosis-coded inpatient discharges per 100,000 discharge records (healthcare utilization) have not been systematically studied. We analyzed Texas hospital inpatient discharge public use data between 2016 and 2023 for all 254 Texas counties. MS-EXCEL and SPSS were used for data collection and analysis. Out of 23.33 million hospital discharge records, 12,587 were identified to have an NTM diagnosis-coded inpatient discharge. Among the patients with NTM, 3.3% of the patients were aged 0–17 years, 19.5% were 18–44 years, 29.5% were 45–64 years, and 47.7% were 65 + years old. The NTM diagnosis-coded inpatient discharge rate in Texas was calculated to be 59.9/100,000 records (range 46.1–62.6). A total of 815 NTM cases were reported in Northeast Texas and 4,203 cases in the Gulf Coast counties. The total number of in-hospital deaths among the NTM-coded discharges was 692 (5.5% of total NTM cases). The number of patients with NTM covered under Medicare Part A was 5,102 and 1,521 were on Medicaid. Based on the hospital discharge data analysis, there appears to be regional variation in the prevalence of NTM disease in Texas. Further studies are needed to determine these variations and to improve our understanding of NTM-PD in Texas.
Keywords
1 Introduction
Non-tuberculous mycobacteria (NTM) are environmental mycobacteria; several of them are pathogenic to humans, causing “hard-to-treat” pulmonary disease (PD) (1). NTM are comprised of multispecies organisms whose risk factors (2–6) and prevalence vary significantly and are frequently associated with contaminated soil and municipal water sources (7–11). Mycobacterium avium complex (MAC), Mycobacterium abscessus, and Mycobacterium kansasii are among the top three NTM (1). As progress is made to improve the diagnosis and treatment of tuberculosis, resulting in fewer cases, there has been a notable increase in the reported prevalence and incidence of NTM-PD in the United States (11) for incompletely understood reasons. Challenges within the field include diagnosis, determination of who would benefit from treatment, less-than-desirable treatment success rates, and frequent recurrence even in the setting of culture conversion.
Middle-aged to elderly (>65 years of age) women of Caucasian descent without a history of smoking or obvious risk factors constitute a large proportion of patients with NTM-PD. Among the other risk groups are immunologically suppressed patients with cystic fibrosis or ciliary-related diseases, young male smokers or patients with prior tuberculosis, and patients with bronchiectasis or chronic obstructive pulmonary disease who develop rapidly progressive cavitary disease. Population prevalence studies and trends in healthcare utilization rates, either from insurance claims databases, pharmacy records, or hospital inpatient admission records, have traditionally been used to track NTM disease burden (12) and report a growing prevalence in the North American population (11–17).
The aim of this study was to estimate the yearly NTM diagnosis-coded inpatient discharges, in high-cost healthcare utilization cases, in Texas between 2016 and 2023, using Texas hospital inpatient discharge public use data (THIDPUD). Data were extracted using the International Classification of Diseases (ICD-10-CM) codes to identify the NTM cases. The American Thoracic Society (ATS)/Infectious Diseases Society of America (IDSA) pulmonary NTM disease criteria used to define the disease recommend that clinical, radiographic, and microbiological criteria are equally important, and all must be met to make a diagnosis of NTM-PD (18). Since we analyzed the hospitalization data and patients may be admitted due to other comorbidities, we refrained from classifying the identified NTM cases as “severe.” Preliminary results from this study were presented as an abstract and poster at the 2025 Colorado NTM Conference (19).
2 Methods
2.1 Rationale for the study
Since NTM-PD is not reportable, large data sets with comprehensive patient records are often hard to obtain, and diagnosis requires a complex combination of clinical symptoms paired with radiological findings and microbiological confirmation, proxy-based studies may provide an estimate of NTM disease burden in Texas.
2.2 Data sources and analysis
The study was approved by the University of Texas at Tyler Institutional Review Board (IRB#2024-170). We used THIDPUD collected between 2016 and 2023. We used the ICD-10-CM codes (20) A31.0 (pulmonary mycobacterial infection), A31.2 (disseminated M. avium-intracellulare complex, A31.8 (other mycobacterial infections), and A31.9 (mycobacterial infection, unspecified) in either the primary or secondary diagnosis fields to identify discharges associated with NTM pulmonary disease in the Texas data. We caution that since these codes were used as a proxy for NTM-PD, the data may include non-pulmonary or non-specific NTM diagnosis. Records were screened to collect data on patients with NTM as the primary or secondary diagnosis in all 254 Texas counties. A sub-analysis was performed for the 35 counties in the Northeast Texas (NETX) region, the geographic area we serve, and for 13 Texas Gulf Coast counties. Annual NTM diagnosis-coded inpatient discharge rates/100,000 discharges were estimated for each calendar year by dividing the case counts by the total number of discharges and then multiplying by 100,000. We also collected data on in-hospital deaths among NTM-coded discharges. MS-EXCEL, MS-Power BI, and SPSS were used for data collection, graphing, and analysis.
3 Results
3.1 NTM-PD in Texas
A total of 23,333,839 hospital discharge records for the years 2016–2023 were available for analysis (Table 1). Female patients accounted for 54.5% (n = 12,723,702) of the total hospital discharge records across all 254 Texas counties. We observed a slight decline in the number of hospitalization records in 2020, followed by a reversal of the trend (Table 1). We speculate that this observation could be due to the then ongoing COVID-19 pandemic (21). With regards to the NTM diagnosis-coded inpatient discharge records across Texas, a total of 12,587 cases were identified, out of which 5,821 (46.2%) were female. There were 2,204 (17.5%) masked gender cases, i.e., we could not assign them as male or female. Therefore, the actual number of female patients could potentially be higher or vice versa. As shown in Table 1, among the female patients with NTM-coded discharges, a large proportion (4,482, 77.0%) were Caucasian.
Table 1. Year-wise distribution of hospital discharge data for NTM-PD in Texas.
| Year | Discharges | Female | NTM cases | ||||
|---|---|---|---|---|---|---|---|
| Total | NTM rate/100K admissions | Female, n (%) | Caucasian female, n (%) | Maskeda, n (%) | |||
| 2016 | 2,837,676 | 1,676,511 | 1536 | 54.1 | 819 (53.3) | 584 (71.3) | 0 (0.0) |
| 2017 | 2,996,158 | 1,642,736 | 1,814 | 60.5 | 825 (45.5) | 632 (76.6) | 398 (21.9) |
| 2018 | 2,904,605 | 1,599,014 | 1,713 | 59.0 | 775 (45.2) | 593 (76.5) | 330 (19.3) |
| 2019 | 2,905,507 | 1,596,139 | 1,818 | 62.6 | 790 (43.5) | 634 (80.3) | 375 (20.6) |
| 2020 | 2,760,250 | 1,483,946 | 1,402 | 50.8 | 631 (45.0) | 495 (78.4) | 261 (18.6) |
| 2021 | 2,892,602 | 1,551,597 | 1,334 | 46.1 | 632 (47.4) | 491 (77.7) | 243 (18.2) |
| 2022 | 3,005,701 | 1,569,936 | 1,476 | 49.1 | 655 (44.4) | 523 (79.8) | 296 (20.1) |
| 2023 | 3,031,340 | 1,603,823 | 1,494 | 49.3 | 694 (46.5) | 530 (76.4) | 301 (20.1) |
| Total | 23,333,839 | 12,723,702 | 12,587 | 59.9 (46.1–62.6) | 5,821 (46.2) | 4,482 (77.0) | 2,204 (17.5) |
| Northeast Texas (NETX) | |||||||
| 2016 | 179,628 | 103,791 | 92 | 51.2 | 50 (54.3) | 46 (92.0) | 0 (0.0) |
| 2017 | 191,291 | 104,221 | 115 | 60.1 | 58 (50.4) | 50 (86.2) | 12 (10.4) |
| 2018 | 186,116 | 101,549 | 103 | 55.3 | 49 (47.6) | 47 (95.9) | 13 (12.6) |
| 2019 | 186,511 | 100,720 | 125 | 67.0 | 48 (38.4) | 45 (93.8) | 25 (20.0) |
| 2020 | 177,022 | 94,060 | 86 | 48.6 | 31 (36.0) | 31 (100.0) | 14 (16.3) |
| 2021 | 183,606 | 96,995 | 79 | 43.0 | 44 (55.7) | 40 (90.9) | 3 (3.8) |
| 2022 | 182,500 | 94,233 | 123 | 67.4 | 57 (46.3) | 51 (89.5) | 19 (15.4) |
| 2023 | 183,075 | 97,024 | 92 | 50.3 | 40 (43.5) | 34 (85.0) | 16 (17.4) |
| Total | 1,469,749 | 792,593 | 815 | 55.5 (43.0–67.4) | 377 (46.3) | 344 (91.2) | 102 (12.5) |
| Texas Gulf Coast | |||||||
| 2016 | 693,200 | 410,762 | 479 | 69.1 | 275 (57.4) | 183 (66.5) | 0 (0.0) |
| 2017 | 711,100 | 393,739 | 587 | 82.5 | 269 (45.8) | 205 (76.2) | 134 (22.8) |
| 2018 | 688,531 | 386,088 | 591 | 85.8 | 276 (46.7) | 197 (71.4) | 115 (19.5) |
| 2019 | 705,613 | 394,638 | 609 | 86.3 | 252 (41.4) | 181 (71.8) | 112 (18.4) |
| 2020 | 674,663 | 368,693 | 499 | 74.0 | 227 (45.5) | 169 (74.4) | 86 (17.2) |
| 2021 | 715,292 | 387,061 | 453 | 63.3 | 220 (48.6) | 163 (74.1) | 91 (20.1) |
| 2022 | 725,964 | 385,120 | 472 | 65.0 | 224 (47.5) | 152 (67.9) | 81 (17.2) |
| 2023 | 736,124 | 388,147 | 513 | 69.7 | 243 (47.4) | 160 (66.8) | 123 (24.0) |
| Total | 5,650,487 | 3,114,248 | 4,203 | 74.4 (63.3–86.3) | 1,986 (47.3) | 1,410 (71.0) | 742 (17.7) |
Data are shown for the 8 years between 2016 and 2023 for all 254 Texas counties and then subdivided for 35 Northeast Texas (NETX) counties and 13 Texas Gulf Coast counties. The rate is for per 100,000 (100 K) records.
Masked means no ethnicity and gender information was available to assign the case as male or female.
Table 2 summarizes the data by age group and proportion of female patients with an associated NTM-related diagnosis. We found that across all age groups, 53.4% (range: 43.8%–70.3%) were female, with the highest proportion (70.3%) among the 18-to-44-year age group. The distribution of NTM cases by age group showed that female patients accounted for 46.7% (range: 29.3%–67.2%) and the percentage of NTM cases among elderly women was high (48.6% in the 66–74-year age group and 67.2% in the 75+ age group). However, since sex/gender was masked/unknown for 2,204/12,587 NTM-coded discharge records, the actual disease burden may be different among female patients and across age groups. Regarding the region-wide distribution, the number of reported NTM cases in NETX was 815 and 4,203 in the Gulf Coast region of Texas.
Table 2. Age and sex-wise NTM case distribution in Texas overall and in the Northeast Texas and Gulf counties.
| Age group | Total discharges | NTM cases | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Texas | Northeast Texas | Gulf Coast | ||||||||||
| n | Female, n (%) | Masked, n (%) | n | Female, n (%) | Masked, n (%) | n | Female, n (%) | Masked, n (%) | n | Female, n (%) | aMasked, n (%) | |
| 0–17 | 4,156,138 | 2,006,630 (48.3) | 102,615 (2.5) | 416 | 215 (51.7) | 11 (2.6) | 13 | 7 (53.8) | 0 (0.0) | 145 | 85 (58.6) | 0 (0.0) |
| 18–44 | 6,188,956 | 4,348,603 (70.3) | 714,272 (11.5) | 2,460 | 720 (29.3) | 1,145 (46.5) | 100 | 35 (35.0) | 52 (52.0) | 770 | 197 (25.6) | 373 (48.4) |
| 45–64 | 5,247,348 | 2,300,064 (43.8) | 675,560 (12.9) | 3,709 | 1,367 (36.9) | 867 (23.4) | 231 | 77 (33.3) | 36 (15.6) | 1,314 | 525 (40.0) | 303 (23.3) |
| 65–74 | 3,514,838 | 1,702,037 (48.4) | 184,247 (5.2) | 2,753 | 1,337 (48.6) | 143 (5.2) | 220 | 92 (41.4) | 12 (5.5) | 956 | 492 (51.5) | 55 (5.8) |
| 75+ | 4,213,433 | 2,364,011 (56.1) | 66,378 (1.6) | 3,249 | 2,182 (67.2) | 38 (1.2) | 251 | 166 (66.1) | 2 (0.8) | 1,018 | 687 (67.5) | 11 (1.1) |
Masked means no gender information was available to assign the case as male or female.
We found an in-hospital death rate of 5.5% among the NTM-coded discharges between 2016 and 2023, with Table 3 reporting the distribution across different age groups and the proportion of female patients with NTM-PD. We could not find any association between NTM-PD and length of hospital stay. Among the patients who died with reported NTM-coded discharges, the mean length of hospital stay was (mean ± standard deviation) 21.0 ± 60.9 days, compared to 11.4 ± 17.6 days in NTM-coded discharges with no reported death. Regarding healthcare insurance usage, the top two insurance providers were Medicare Part “A,” with 5,102 cases, and Medicaid, with 1,521 cases.
Table 3. Year-wise, age group, and sex-based NTM-coded mortality records in Texas and regional variations.
| Year | Texas | NETX | Gulf Coast | ||||||
|---|---|---|---|---|---|---|---|---|---|
| deaths | NTM cases | % | deaths | NTM cases | % | deaths | NTM cases | % | |
| 2016 | 100 | 1,536 | 6.51 | 4 | 92 | 4.35 | 32 | 479 | 6.68 |
| 2017 | 92 | 1,814 | 5.07 | 2 | 115 | 1.74 | 25 | 587 | 4.26 |
| 2018 | 102 | 1,713 | 5.95 | 8 | 103 | 7.77 | 29 | 591 | 4.91 |
| 2019 | 76 | 1,818 | 4.18 | 4 | 125 | 3.20 | 19 | 609 | 3.12 |
| 2020 | 66 | 1,402 | 4.71 | 4 | 86 | 4.65 | 16 | 499 | 3.21 |
| 2021 | 74 | 1,334 | 5.55 | 3 | 79 | 3.80 | 21 | 453 | 4.64 |
| 2022 | 83 | 1,476 | 5.62 | 6 | 123 | 4.88 | 24 | 472 | 5.08 |
| 2023 | 102 | 1,494 | 6.83 | 6 | 92 | 6.52 | 29 | 513 | 5.65 |
| Mortality in different age groups | |||||||||
| 0–17 | 5 | 416 | 1.20 | 0 | 13 | 0.00 | 0 | 145 | 0.00 |
| 18–44 | 121 | 2460 | 4.92 | 4 | 100 | 4.00 | 36 | 770 | 4.68 |
| 45–64 | 197 | 3,709 | 5.31 | 7 | 231 | 3.03 | 50 | 1,314 | 3.81 |
| 65–74 | 170 | 2,753 | 6.18 | 14 | 220 | 6.36 | 49 | 956 | 5.13 |
| 75+ | 202 | 3,249 | 6.22 | 12 | 251 | 4.78 | 60 | 1,018 | 5.89 |
| Mortality by gender | |||||||||
| Male | 294 | 4,562 | 6.44 | 15 | 336 | 4.46 | 79 | 1,475 | 5.36 |
| Female | 267 | 5,821 | 4.59 | 15 | 377 | 3.98 | 77 | 1,986 | 3.88 |
| Masked/unknown | 134 | 2,204 | 6.08 | 7 | 102 | 6.86 | 39 | 742 | 5.26 |
3.2 NTM-PD in NETX
The NETX region comprises 35 counties, referred to as the DSHS Health Service Region 4/5 (https://utsystem.edu/netx/)) (22). The population of the NETX region is ∼1.6 million people, i.e., ∼5.4% of the Texas population (22). There were a total of 1,469,749 hospital discharge records available for the NETX region between 2016 and 2023 (Table 1). As shown in Table 1, a total of 815 NTM diagnosis-coded inpatient discharge records could be identified; 377 were female, and among these, 344 records were Caucasian female patients. The proportion of female patients with NTM-PD in the 18–44, 45–64, and 75+ age groups was calculated to be 35.0%, 33.3%, and 66.1%, respectively (Table 2). The number of in-hospital deaths in NTM-coded discharges in NETX, over the 8-year study duration, was calculated to be 37/815 (4.5%) (Table 3). The mean length of hospital stay for patients with an NTM-coded discharge record who died in NETX was 11.3 ± 10.8 days, which was not statistically different from that of those with NTM-coded discharge records who did not die (10.9 ± 16.6 days).
3.3 NTM-PD in the Texas Gulf Coast region
As per the 2020 Census, the Texas Gulf Coast region, which includes 13 counties, is home to ∼7.3 million (∼25% of the state's total population) people, and nearly 65% of the region's population is concentrated in Harris County (23). We identified 5,650,487 inpatient discharge records from the Gulf Coast region, and 4,203 were associated with NTM (Table 1). As shown in Table 1, 1,986/4,203 (47.3%) of the NTM cases were female, and 1,410/1,986 (71.0%) were Caucasian female patients. The proportion of female patients with NTM in the 18–44 and 45–64 age groups was calculated to be 25.6% and 67.5%, respectively (Table 2). The number of NTM-coded death records in the Gulf Coast region between 2016 and 2023 was 195/4,203 (4.6%), and 77 were female patients (Table 3). The length of hospital stay of the patients who died and had an NTM-coded diagnosis was 28.6 ± 106.9 days vs. 11.6 ± 16.4 days for the patients for whom no death was reported.
4 Discussion
There has been a global increase in both the number of clinical isolates and the prevalence of NTM-PD (4, 12, 15, 16, 24–26). However, an exact determination of the NTM-PD burden is challenging due to case selection and difficulties in subspecies identification, and NTM infections are not reportable. Even after a diagnosis of NTM infection is established, a significant proportion of patients do not encounter favorable treatment outcomes (27, 28). Thus, continued observation even after treatment completion is required. Without a doubt, NTM-PD imposes a significant financial burden on patients and the healthcare systems. However, estimation of the NTM-PD cost burden was not the objective of this study, and such cost-linkage studies are warranted.
A recent study by Spaulding et al. (25) reported geographic variation in the distribution of NTM in the United States, and an increasing trend in the prevalence of NTM-PD cases. Analyzing data for the period between 2009 and 2013, this study reported that MAC was the predominant NTM with 75% of all the NTM isolates and up to 61% of the NTM isolates in the West South Central region, including Texas (25). Another study by Winthrop et al (5), utilizing the statewide laboratory-based surveillance project for NTM in Oregon over 2 years, 2005–2006, highlighted the limited NTM epidemiological information available regarding the prevalence of NTM-PD in the United States. However, no such study was found that specifically highlighted the NTM disease burden in Texas.
Thus, this retrospective study analyzed Texas inpatient hospital discharge data over 8 years (2016–2023) to determine the NTM-PD burden in Texas and whether there exists geographic variation within the state to better inform policy decisions. On the state level, first, we screened >23 million hospital discharge records using ICD-10-CM codes to identify cases associated with NTM-PD. We found that, in Texas, female patients consistently accounted for more than half of the hospital discharge records associated with NTM-PD. Second, despite a large number of masked cases for race/gender/ethnicity, a large proportion (77.0%) of the female patients with NTM-PD were Caucasian. Third, similar to a previous report citing an increasing incidence rate of NTM-PD in the aged population (29), we found that, in Texas, the percentage of NTM-PD cases among women was high, with rates of 48.4% in the 65–74-year age group and 67.2% in the 75+ age group. Thus, age appears to be a significant risk factor among all others for developing NTM-PD in women. Fourth, while we could not find any association between NTM-PD and length of hospital stay, 695 deaths were reported in the NTM-coded discharge records between 2016 and 2023, and the proportion was higher in patients over 65 + years of age, i.e., 372 (53.5%).
Regarding regional differences in NTM-PD prevalence in Texas, in the NETX region, which has 35 counties, out of 1,469,749 hospital discharge records, 815 NTM-PD cases were counted. Caucasian female patients accounted for a large proportion of the female NTM-PD cases, i.e., 344/377 (91.2%) in NETX. We observed high mortality (14/220, 6.36%) in the 65–74 age group. In this study, we found that the proportion of female gender cases was higher in the Gulf counties compared to other Texas counties. The proportion of Caucasian female patients among patients with NTM-PD in the Gulf counties (71.0%) was similar to the Texas state average (77.0%), in contrast to NETX (91.2%). The distribution of patients across age groups and mortality in the NTM-coded records was not different over the 8-year study duration. Our study also provides a statewide birds-eye view of the estimate of NTM-PD burden (in terms of NTM diagnosis-coded inpatient discharges/100,000) among beneficiaries covered via different insurance plans, with Medicare Part A and Medicaid covering a large proportion of the patients by virtue of the age distribution; however, the burden was not as high as that reported in a previous Medicare-based study where the annual prevalence (cases/100,000 persons) increased ∼2.5-fold between 1997 and 2007 (30). These findings and previous reports indicate a potential need for additional healthcare support in aging patients with NTM-PD.
Despite meaningful findings on the NTM-PD burden in Texas, our hospital discharge data analysis study has several limitations. First, we used data from a hospitalized population, whereas the majority of patients with NTM-PD are diagnosed and managed in an outpatient setting. Therefore, the NTM-PD burden we report may not be the same for outpatient populations. Second, in the deidentified data, we could not identify multiple hospitalizations for any patient. Therefore, it is a possibility that a single patient could be represented more than once each year, resulting in an overestimation of the true impact of NTM-PD. Third, gender was masked for 17.5% of the total NTM-PD cases. Therefore, the proportion of female patients we report here may not be a true representation of the NTM-PD burden in Texas. Fourth, the hospital discharge data we used for these analyses did not include microbiological information to determine which NTM (e.g., MAC vs. M. abscessus) is the prevalent pathogen in Texas, and if the dominant species are different in NETX and the Gulf Coast region. Fifth, the analyzed data did not include the required information to perform a subanalysis to determine other pulmonary comorbidities in the identified NTM cases and what, if any, independent risk factors for NTM-PD were present.
In conclusion, despite the limitations of our data, NTM-PD is high in Texas, particularly among elderly Caucasian women in certain geographic areas. Further studies are needed to systematically define the actual prevalence of NTM disease in non-hospitalized persons to identify the risk factors for disease susceptibility as well as environmental exposure.
Generative AI statement
The author(s) declared that generative AI was not used in the creation of this manuscript.
Any alternative text (alt text) provided alongside figures in this article has been generated by Frontiers with the support of artificial intelligence and reasonable efforts have been made to ensure accuracy, including review by the authors wherever possible. If you identify any issues, please contact us.
Publisher's note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
Footnotes
Edited by: Harald Gotten Wiker, University of Bergen, Norway
Reviewed by: Matt Johansen, University of Technology Sydney, Australia
Byung Woo Jhun, Sungkyunkwan University, Republic of Korea
Statements
- Conflict of interest
The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
The reviewer MJ declared a past co-authorship with the author JP to the handling editor.
- Funding
The author(s) declared that financial support was not received for this work and/or its publication.
- Data availability
The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author.
- Ethics approval
This study involving humans was approved by the Institutional Review Board of the University of Texas at Tyler. This study was conducted in accordance with the local legislation and institutional requirements. The ethics committee/institutional review board waived the requirement of written informed consent for participation from the participants or the participants' legal guardians/next of kin because this was a retrospective study of publicly available data.
- Author contributions
AB: Data curation, Formal analysis, Methodology, Software, Visualization, Writing – review & editing. JP: Validation, Visualization, Writing – review & editing. DM: Writing – review & editing. SM: Data curation, Resources, Writing – review & editing. SS: Conceptualization, Formal analysis, Funding acquisition, Supervision, Visualization, Writing – original draft, Writing – review & editing.
References
- 1. Nahid P, Mase SR, Migliori GB, Sotgiu G, Bothamley GH, Brozek JL. Treatment of drug-resistant tuberculosis. An official ATS/CDC/ERS/IDSA clinical practice guideline. Am J Respir Crit Care Med. (2019) 200 (10): e93 – 142. doi:10.1164/rccm.201909-1874ST
- 2. Corbett EL, Churchyard GJ, Clayton T, Herselman P, Williams B, Hayes R. Risk factors for pulmonary mycobacterial disease in South African gold miners. A case-control study. Am J Respir Crit Care Med. (1999) 159 (1): 94 – 9. doi:10.1164/ajrccm.159.1.9803048
- 3. Iseman MD, Marras TK. The importance of nontuberculous mycobacterial lung disease. Am J Respir Crit Care Med. (2008) 178 (10): 999 – 1000. doi:10.1164/rccm.200808-1258ED
- 4. Strollo SE, Adjemian J, Adjemian MK, Prevots DR. The burden of pulmonary nontuberculous mycobacterial disease in the United States. Ann Am Thorac Soc. (2015) 12 (10): 1458 – 64. doi:10.1513/AnnalsATS.201503-173OC
- 5. Winthrop KL, McNelley E, Kendall B, Marshall-Olson A, Morris C, Cassidy M. Pulmonary nontuberculous mycobacterial disease prevalence and clinical features: an emerging public health disease. Am J Respir Crit Care Med. (2010) 182 (7): 977 – 82. doi:10.1164/rccm.201003-0503OC
- 6. Nqwata L, Ouedrago AR. Non-tuberculous mycobacteria pulmonary disease: a review of trends, risk factors, diagnosis and management. Afr J Thorac Crit Care Med. (2022) 28 (2):82–6. doi:10.7196/AJTCCM.2022.v28i2.157
- 7. Biet F, Boschiroli ML, Thorel MF, Guilloteau LA. Zoonotic aspects of Mycobacterium bovis and Mycobacterium avium -intracellulare complex (MAC). Vet Res. (2005) 36 (3): 411 – 36. doi:10.1051/vetres:2005001
- 8. Adjemian J, Frankland TB, Daida YG, Honda JR, Olivier KN, Zelazny A. Epidemiology of nontuberculous mycobacterial lung disease and tuberculosis, Hawaii, USA. Emerg Infect Dis. (2017) 23 (3): 439 – 47. doi:10.3201/eid2303.161827
- 9. Adjemian J, Olivier KN, Seitz AE, Falkinham JO 3rd, Holland SM, Prevots DR. Spatial clusters of nontuberculous mycobacterial lung disease in the United States. Am J Respir Crit Care Med (2012) 186 (6): 553 – 8. doi:10.1164/rccm.201205-0913OC
- 10. Agizew T, Basotli J, Alexander H, Boyd R, Letsibogo G, Auld A. Higher-than-expected prevalence of non-tuberculous mycobacteria in HIV setting in Botswana: implications for diagnostic algorithms using Xpert MTB/RIF assay. PLoS One. (2017) 12 (12): e0189981. doi:10.1371/journal.pone.0189981
- 11. O'Brien RJ, Geiter LJ, Snider DE Jr. The epidemiology of nontuberculous mycobacterial diseases in the United States. Results from a national survey. Am Rev Respir Dis (1987) 135 (5): 1007 – 14. doi:10.1164/arrd.1987.135.5.1007
- 12. Winthrop KL, Marras TK, Adjemian J, Zhang H, Wang P, Zhang Q. Incidence and prevalence of nontuberculous mycobacterial lung disease in a large U.S. managed care health plan, 2008–2015. Ann Am Thorac Soc. (2020) 17 (2): 178 – 85. doi:10.1513/AnnalsATS.201804-236OC
- 13. Cassidy PM, Hedberg K, Saulson A, McNelly E, Winthrop KL. Nontuberculous mycobacterial disease prevalence and risk factors: a changing epidemiology. Clin Infect Dis. (2009) 49 (12): e124 – 9. doi:10.1086/648443
- 14. Marras TK, Daley CL. Epidemiology of human pulmonary infection with nontuberculous mycobacteria. Clin Chest Med. (2002) 23 (3): 553 – 67. doi:10.1016/S0272-5231(02)00019-9
- 15. Prevots DR, Marras TK. Epidemiology of human pulmonary infection with nontuberculous mycobacteria: a review. Clin Chest Med. (2015) 36 (1): 13 – 34. doi:10.1016/j.ccm.2014.10.002
- 16. Prevots DR, Shaw PA, Strickland D, Jackson LA, Raebel MA, Blosky MA. Nontuberculous mycobacterial lung disease prevalence at four integrated health care delivery systems. Am J Respir Crit Care Med. (2010) 182 (7): 970 – 6. doi:10.1164/rccm.201002-0310OC
- 17. Billinger ME, Olivier KN, Viboud C, de Oca RM, Steiner C, Holland SM. Nontuberculous mycobacteria-associated lung disease in hospitalized persons, United States, 1998–2005. Emerg Infect Dis. (2009) 15 (10): 1562 – 9. doi:10.3201/eid1510.090196
- 18. Griffith DE, Aksamit T, Brown-Elliott BA, Catanzaro A, Daley C, Gordin F. An official ATS/IDSA statement: diagnosis, treatment, and prevention of nontuberculous mycobacterial diseases. Am J Respir Crit Care Med. (2007) 175 (4): 367 – 416. doi:10.1164/rccm.200604-571ST
- 19. Baham A, Pasipahodya JG, McBride S, Srivastava S. Analysis of hospital admission data for NTM pulmonary disease in Texas, 2016–2023. Colorado Mycobacteria Conference 2025; May 28, 2025. Fort Collins, CO (2025).
- 20. ICD-10-CM Codes › A00-B99 › A30-A49 › Infection due to other mycobacteria A31 [Internet]. (2025). Available online at: (Accessed December 5, 2025).
- 21. O'Leary C, Ziad-M.Said M, Bazbaz A, Iglesias JI, Varon J. The prevalence of nontuberculous mycobacteria infections in the COVID-19 era. CHEST. (2025) 168 (Suppl 4): A1285. doi:10.1016/j.chest.2025.07.750
- 22. Nehme E, Schuessler K, Alvarado C, Elerian N, Miyakado H, Mandell D. The Health Status of Northeast Texas, 2021. Tyler, TX: The University of Texas at Tyler/University of Texas System Population Health (2021).
- 23. The Gulf Coast Region. 2022 Regional Report. In: Texas Comptroller of Public Accounts, editor. Texas Comptroller of Public Accounts (2022).
- 24. Huang HL, Cheng MH, Lu PL, Shu CC, Wang JY, Wang JT. Epidemiology and predictors of NTM pulmonary infection in Taiwan—a retrospective, five-year multicenter study. Sci Rep. (2017) 7 (1): 16300 – 7. doi:10.1038/s41598-017-16559-z
- 25. Spaulding AB, Lai YL, Zelazny AM, Olivier KN, Kadri SS, Prevots DR. Geographic distribution of nontuberculous mycobacterial species identified among clinical isolates in the United States, 2009–2013. Ann Am Thorac Soc. (2017) 14 (11): 1655 – 61. doi:10.1513/AnnalsATS.201611-860OC
- 26. Kendall BA, Winthrop KL. Update on the epidemiology of pulmonary nontuberculous mycobacterial infections. Semin Respir Crit Care Med. (2013) 34 (1): 87 – 94. doi:10.1055/s-0033-1333567
- 27. Pasipanodya JG, Ogbonna D, Deshpande D, Srivastava S, Gumbo T. Meta-analyses and the evidence base for microbial outcomes in the treatment of pulmonary Mycobacterium avium -intracellulare complex disease. J Antimicrob Chemother. (2017) 72 (Suppl_2): i3 – i19. doi:10.1093/jac/dkx311
- 28. Pasipanodya JG, Ogbonna D, Ferro BE, Magombedze G, Srivastava S, Deshpande D. Systematic review and meta-analyses of the effect of chemotherapy on pulmonary Mycobacterium abscessus outcomes and disease recurrence. Antimicrob Agents Chemother. (2017) 61 (11): 9. doi:10.1128/AAC.01206-17
- 29. Zhang Z, Pang Y, Wang Y, Cohen C, Zhao Y, Liu C. Differences in risk factors and drug susceptibility between Mycobacterium avium and Mycobacterium intracellulare lung diseases in China. Int J Antimicrob Agents. (2015) 45 (5): 491 – 5. doi:10.1016/j.ijantimicag.2015.01.012
- 30. Adjemian J, Olivier KN, Seitz AE, Holland SM, Prevots DR. Prevalence of nontuberculous mycobacterial lung disease in U.S. Medicare beneficiaries. Am J Respir Crit Care Med. (2012) 185 (8): 881 – 6. doi:10.1164/rccm.201111-2016OC
Citation
Baham, A., et al. (2026). Non-tuberculous mycobacteria pulmonary disease in Texas: an analysis of 8 years of hospital discharge data. Frontiers in Tuberculosis, Volume 4. https://doi.org/
- Received
- Accepted
- Published
- Volume
- 4 - 2026
Copyright
© 2026 Baham, Pasipanodya, Mehta, McBride and Srivastava.
License: https://creativecommons.org/licenses/by/4.0/
*Correspondence: Shashikant Srivastava
Article metrics
- Views
- 0
- Downloads
- 0
- Citations
- 0
- Shares
- 0
