Development and validation of the HEALTH scoring system = A novel and non-invasive laboratory panel to differentiate intestinal tuberculosis from   other gastrointestinal diseases

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Diagnosing intestinal tuberculosis (ITB) is challenging due to its symptoms, which mimic other diseases, limited laboratory tests, and the need for invasive procedures like colonoscopy. This study aimed to develop a non-invasive laboratory panel for ITB using various biomarkers. Methods A cross-sectional study from November 2020 to December 2022 was carried out at Dr. Cipto Mangunkusumo National Central General Hospital. Laboratory parameters from 143 subjects were identified by Chi-square test and multiple regression analysis. The scoring system was developed based on the identified independent diagnostic parameters scored by regression coefficient β value and standard errors, with the cut-off value determined by the ROC curve. The sensitivity and specificity of the scoring system were determined using the ROC curve. Results Among 143 subjects, 22 were diagnosed with ITB and 121 Non-ITB (prevalence of 15.38%). This study was dominated by females (65.03%), with a ratio of 1.86: 1. The median age in this study was 41 years. The scoring system to differentiate ITB and Non-ITB consisted of 6 diagnostic parameters (referred to as the HEALTH scoring system) as follows: stool HBD-2 (1 and 0 points), ESR (1 and 0 points), blood ADA activity (1 and 0 points), Lymphocyte (0 and 1 point), stool TB PCR (2 and 0 points), and NLR (1 and 0 points). Subjects with scores ≥ 4 could be diagnosed as ITB. The sensitivity and specificity of the HEALTH scoring system were 68.18% and 95.04%, respectively. Conclusion This study developed and validated a laboratory panel called the HEALTH scoring system based on clinical biomarkers of stool HBD-2 level, ESR, blood ADA activity, lymphocytes, stool TB PCR, and NLR, which could be used to differentiate ITB from other gastrointestinal diseases. 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F1000Research 2025, 14 :103 ( https://doi.org/10.12688/f1000research.160489.1 ) NOTE: If applicable, it is important to ensure the information in square brackets after the title is included in all citations of this article. Close Copy Citation Details Export Export Citation Sciwheel EndNote Ref. Manager Bibtex ProCite Sente EXPORT Select a format first Track Share ▬ ✚ Research Article Development and validation of the HEALTH scoring system = A novel and non-invasive laboratory panel to differentiate intestinal tuberculosis from other gastrointestinal diseases [version 1; peer review: 1 approved, 1 approved with reservations] Nuri Dyah Indrasari https://orcid.org/0000-0001-8250-5456 1,2 , Marcellus Simadibrata 1,3 , Primariadewi Rustamadji 1,4 , [...] Yusra Yusra 1,2 , Suhendro Suwarto https://orcid.org/0000-0001-6394-0591 1,3 , Aria Kekalih 5 , Heri Wibowo 6 , Ida Parwati 7,8 , Alida Roswita Harahap 2 , Nindy Auliana https://orcid.org/0009-0008-3499-3502 1,2 Nuri Dyah Indrasari https://orcid.org/0000-0001-8250-5456 1,2 , Marcellus Simadibrata 1,3 , [...] Primariadewi Rustamadji 1,4 , Yusra Yusra 1,2 , Suhendro Suwarto https://orcid.org/0000-0001-6394-0591 1,3 , Aria Kekalih 5 , Heri Wibowo 6 , Ida Parwati 7,8 , Alida Roswita Harahap 2 , Nindy Auliana https://orcid.org/0009-0008-3499-3502 1,2 PUBLISHED 17 Jan 2025 Author details Author details 1 Dr. Cipto Mangunkusumo National Central General Hospital, Jakarta, Indonesia 2 Department of Clinical Pathology, Faculty of Medicine, Universitas Indonesia, Jakarta, Indonesia 3 Department of Internal Medicine, Faculty of Medicine, Universitas Indonesia, Jakarta, Indonesia 4 Department of Anatomical Pathology, Faculty of Medicine, Universitas Indonesia, Jakarta, Indonesia 5 Department of Community Medicine, Faculty of Medicine, Universitas Indonesia, Jakarta, Indonesia 6 Department of Parasitology, Faculty of Medicine, Universitas Indonesia, Jakarta, Indonesia 7 Dr. Hasan Sadikin General Hospital, Bandung, Indonesia 8 Department of Clinical Pathology, Faculty of Medicine, Universitas Padjajaran, Bandung, Indonesia Nuri Dyah Indrasari Roles: Conceptualization, Data Curation, Formal Analysis, Funding Acquisition, Investigation, Methodology, Project Administration, Resources, Software, Supervision, Validation, Visualization, Writing – Original Draft Preparation, Writing – Review & Editing Marcellus Simadibrata Roles: Conceptualization, Data Curation, Formal Analysis, Investigation, Methodology, Supervision, Validation Primariadewi Rustamadji Roles: Conceptualization, Investigation, Supervision, Validation Yusra Yusra Roles: Conceptualization, Methodology, Supervision, Validation Suhendro Suwarto Roles: Conceptualization, Data Curation, Formal Analysis, Methodology, Supervision, Validation Aria Kekalih Roles: Conceptualization, Data Curation, Formal Analysis, Methodology, Software, Supervision, Validation Heri Wibowo Roles: Conceptualization, Supervision, Validation Ida Parwati Roles: Conceptualization, Methodology, Supervision, Validation Alida Roswita Harahap Roles: Conceptualization, Supervision, Validation Nindy Auliana Roles: Data Curation, Formal Analysis, Project Administration, Resources, Software, Visualization, Writing – Original Draft Preparation, Writing – Review & Editing OPEN PEER REVIEW DETAILS REVIEWER STATUS This article is included in the Global Public Health gateway. Abstract Backgrounds Tuberculosis (TB) remains a significant health issue in Indonesia, ranking second globally in TB incidence in 2021. Diagnosing intestinal tuberculosis (ITB) is challenging due to its symptoms, which mimic other diseases, limited laboratory tests, and the need for invasive procedures like colonoscopy. This study aimed to develop a non-invasive laboratory panel for ITB using various biomarkers. Methods A cross-sectional study from November 2020 to December 2022 was carried out at Dr. Cipto Mangunkusumo National Central General Hospital. Laboratory parameters from 143 subjects were identified by Chi-square test and multiple regression analysis. The scoring system was developed based on the identified independent diagnostic parameters scored by regression coefficient β value and standard errors, with the cut-off value determined by the ROC curve. The sensitivity and specificity of the scoring system were determined using the ROC curve. Results Among 143 subjects, 22 were diagnosed with ITB and 121 Non-ITB (prevalence of 15.38%). This study was dominated by females (65.03%), with a ratio of 1.86: 1. The median age in this study was 41 years. The scoring system to differentiate ITB and Non-ITB consisted of 6 diagnostic parameters (referred to as the HEALTH scoring system) as follows: stool HBD-2 (1 and 0 points), ESR (1 and 0 points), blood ADA activity (1 and 0 points), Lymphocyte (0 and 1 point), stool TB PCR (2 and 0 points), and NLR (1 and 0 points). Subjects with scores ≥ 4 could be diagnosed as ITB. The sensitivity and specificity of the HEALTH scoring system were 68.18% and 95.04%, respectively. Conclusion This study developed and validated a laboratory panel called the HEALTH scoring system based on clinical biomarkers of stool HBD-2 level, ESR, blood ADA activity, lymphocytes, stool TB PCR, and NLR, which could be used to differentiate ITB from other gastrointestinal diseases. READ ALL READ LESS Keywords Diagnosis, intestinal tuberculosis, internal validation, laboratory panel, scoring system Corresponding Author(s) Nuri Dyah Indrasari ( [email protected] ) Close Corresponding author: Nuri Dyah Indrasari Competing interests: No competing interests were disclosed. Grant information: The author(s) declared that no grants were involved in supporting this work. Copyright: © 2025 Indrasari ND et al . This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. How to cite: Indrasari ND, Simadibrata M, Rustamadji P et al. Development and validation of the HEALTH scoring system = A novel and non-invasive laboratory panel to differentiate intestinal tuberculosis from other gastrointestinal diseases [version 1; peer review: 1 approved, 1 approved with reservations] . F1000Research 2025, 14 :103 ( https://doi.org/10.12688/f1000research.160489.1 ) First published: 17 Jan 2025, 14 :103 ( https://doi.org/10.12688/f1000research.160489.1 ) Latest published: 17 Jan 2025, 14 :103 ( https://doi.org/10.12688/f1000research.160489.1 ) Introduction World Health Organization (WHO) reported through the Global Tuberculosis Report 2022 that Indonesia is in second place with the highest burden of tuberculosis in 2021. 1 Tuberculosis (TB) is an infectious disease caused by Mycobacterium tuberculosis (MTB). These bacteria primarily infect the lung tissue but can also spread to other body parts. When TB affects areas outside the lungs, it is referred to as extrapulmonary tuberculosis (EPTB). The prevalence of EPTB worldwide is 16%, while in Indonesia is 10–19%. 2 Intestinal tuberculosis (ITB) as part of EPTB has a prevalence of around 3–16%. 3 – 5 The proportion of TB colitis in Dr. Cipto Mangunkusumo National Central General Hospital, reported by Suparmin, was 8/60 (13.3%). 6 Although pulmonary TB (PTB) is more common, ITB can present with vague, non-specific gastrointestinal symptoms, such as abdominal pain, diarrhea, weight loss, and bloating. It remains a diagnostic challenge due to its overlap with other gastrointestinal diseases, such as Crohn’s disease (CD) and colon cancer. The management of ITB, CD, and colon cancer is known to be very different. 7 – 10 While ITB can be cured with anti-TB therapy, CD typically persists and may relapse. Misdiagnosis of CD as ITB results in unnecessary anti-TB therapy, increased risk of toxicity, and late treatment of the primary disease. Otherwise, misdiagnosis of ITB as CD results in fatal ITB. 7 – 14 Misdiagnosis of ITB as colon cancer can lead to unnecessary surgical interventions, such as hemicolectomy, which could have been avoided with accurate diagnosis. Misdiagnosing colon cancer as ITB can delay necessary cancer treatments, potentially worsening patient outcomes. Both conditions require different treatment approaches, and incorrect treatment due to misdiagnosis can lead to increased morbidity and even mortality. 15 , 16 The routine diagnosis of ITB is based on clinical manifestations, Ziehl-Neelsen (ZN) acid-fast bacterial (AFB) staining examination of stool, stool culture, colonoscopy, and histopathology. 4 , 14 , 17 – 19 Each of these ITB diagnostic examinations has advantages and limitations. Considering that some laboratory parameters often available in healthcare facilities and the impact of inflammation in ITB produces an abnormal immune response in leukocytes and differential count, erythrocyte sedimentation rate (ESR), neutrophil to lymphocyte ratio (NLR), monocyte to lymphocyte ratio (MLR), interferon-gamma (IFN-γ), adenosine deaminase (ADA), and the antimicrobial protein human beta defensin-2 (HBD-2) 20 – 26 have proven to be valuable in differentiating ITB and other gastrointestinal diseases. Furthermore, using non-invasive laboratory samples, especially stool and blood, has become a pivotal area in modern diagnostics. These biological specimens offer significant advantages in patient comfort, non-invasive, ease of sample collection, and the potential for early detection of various diseases. 27 In recent years, numerous studies have been attempted to create model panels that could improve the accuracy and success rate of ITB management, 28 – 33 but they used different diagnostic models and scoring systems, some of which are not user-friendly, as they may need a calculator or a computer, and cannot be applied in healthcare facilities that lack access to colonoscopy and histopathology services. Hence, in this study, we aimed to develop and validate a non-invasive laboratory panel using a scoring system to differentiate ITB from other gastrointestinal diseases. Methods Study population We recruited 191 adult subjects > 18 years who underwent colonoscopy at Dr. Cipto Mangunkusumo National Central General Hospital from November 2020 to December 2022. All suspected subjects fulfilled the 3 of 4 main clinical criteria: (1) weight loss, (2) non-specific abdominal pain, (3) fever, (4) diarrhea or chronic constipation, and 1 of 3 additional histories: (1) pulmonary tuberculosis history, (2) active pulmonary tuberculosis with ongoing anti-tuberculosis therapy (ATT) < 3 months, (3) contact with positive TB patient. All diagnosed subjects with ITB fulfilled the 2 of 4 criteria or positive stool TB PCR only: (1) summary of colonoscopy result showed ITB suspect, (2) histopathological result showed lesions in the submucosa or submuscular include epithelioid cells, Datia Langhans cells, lymphocytes at the edge of the granuloma, and caseous necrosis, (3) positive stool TB PCR, and (4) subjects showed a good response to ATT with clinical manifestation consistent with active TB. In addition, all subjects who were ongoing ATT > 3 months and post-treatment with ATT < 6 months are excluded from this study. Forty-eight subjects dropped out due to incomplete specimens. There were 143 subjects with complete specimens that could be analyzed. Clinical and laboratory investigation of ITB The clinical data included age, gender, abdominal pain, chronic diarrhea, constipation, blood in stool, mucus in stool, weight loss, fever, night sweats, appetite loss, cough, TB contact, and TB history. Laboratory data included stool and blood examinations. For stool sample collection, participants provided a stool collection kit consisting of a red screw-capped collection tube, ice pack, plastic, plastic gloves, and a plastic spoon. Stool samples were collected using a plastic spoon in the tube. The tube was capped and the sample was sent to the laboratory with ice pack. Stool samples were then aliquoted and stored at -20 °C until processing. For blood sample colection, venous blood was taken from each subject and collected in 1 EDTA tube, 3 Heparin tubes, and 1 serum tube. Stool examination included TB PCR, IFN-γ, and HBD-2. Stool specimens were subjected to direct extraction via lysis bead-based method using AllPrep ® PowerFecal ® DNA/RNA Kit (Qiagen, Hilden, Germany) according to the manufacturer’s instruction. The extracted DNA was then used as template DNA for the AccuPower ® MTB&NTM Real-Time PCR Kit (Bioneer, Daejeon, South Korea). This assay relies on real-time PCR (RT-PCR) and distinguishes between MTB and non-tuberculosis mycobacteria. Stool IFN-γ assay relies on Enzyme-linked Immunosorbent Assay (ELISA) method using Human Interferon Gamma (IFNG) ELISA kit MBS017987 (MyBioSource, San Diego, United States) according to the manufacturer’s instruction. Stool HBD-2 assay relies on ELISA method using β-Defensin 2 ELISA kit (Immunodiagnostik AG, Bensheim, Germany) according to the manufacturer’s instruction. Blood examination included hematology tests (leukocytes, differential count, NLR and MLR), ESR, IGRA, and blood ADA activity. Hematology tests using automated blood cell counter Sysmex XN-1000 (Sysmex, Kobe, Japan). ESR test relies on Westergren method using automated sedimentation rate analyzer Starrsed RS (RR Mechatronics, Zwaag, Netherland). IGRA was measured relies on sandwich ELISA method using QuantiFERON-TB Gold PLUS ® (Qiagen, Hilden, Germany). Blood ADA activity assay relies on enzymatic colorimetry method using automated biochemistry analyzer Mindray BS-200 (Mindray, Shenzhen, China). These laboratory data were dichotomized based on their cut-off value. Determination of scoring system Statistical analyses were performed using the Statistical Program for Social Science (SPSS) version 20 (IBM, New York, USA) and STATA 14 (StataCorp LLC, Texas, USA) (free alternative, R programming language). Subject characteristics and clinical manifestation were presented descriptively. Categorical variables were reported as frequency and percentages. Numerical variables were reported as mean (standard deviation) or median (interquartile range) depending on the distribution of data. Bivariate analysis of clinical and laboratory parameters between 2 groups i.e., ITB and Non-ITB subjects was conducted using the Chi-square test. Variables with p-values < 0.25 in the bivariate analysis were included in the initial model in multivariate analysis using the multiple regression analysis. Variables with p-values < 0.05 in the multivariate analysis were considered independent diagnostic parameters. These independent diagnostic parameters were subsequently incorporated into a scoring system. The score for each parameter was calculated based on its regression coefficient β value divided by the standard errors, then the results are divided by the smallest value, and the values rounded off to the nearest integer. The optimal cut-off value of the scoring system was determined by the receiver operating characteristic (ROC) curve, selecting the point on the curve with the largest area under the curve (AUC). The sensitivity and specificity of the scoring system were also determined by the ROC curve. Calibration and validation of scoring system Calibration in the final model was determined using the Hosmer-Lemeshow test with p > 0.05. Discrimination performance was evaluated by the ROC curve corresponding to the point on the curve with the AUC. The internal validation of the final model was processed using a bootstrapping method to ensure that the scoring system can be used on a population with the same characteristics as subject characteristics in this study, with a larger number of subjects. Results Subject characteristics and clinical manifestations Subject characteristics and clinical manifestations are summarized in Table 1 . Among 143 subjects, 22 were diagnosed with ITB and 121 Non-ITB (inflammatory bowel diseases, non-specific ileocolitis, malignancy, and hemorrhoid). This study was dominated by females (65.03%), with a female-to-male ratio of 1.86: 1. The median age of subjects with ITB and Non-ITB were 33.5 and 41 years, respectively. The prevalence of ITB in this study was 15.38%. Abdominal pain (86.01%) was the most common presenting symptom, followed by constipation (66.43%), chronic diarrhea (60.14%), alternating diarrhea and constipation (59.44%), and weight loss (57.34%). A history of pulmonary and extrapulmonary TB was only found in 12 subjects (8.39%). Weight loss, cough, appetite loss, chronic diarrhea, and alternating diarrhea-constipation showed statistically significant differences among ITB and Non-ITB subjects. Table 1. Subject characteristics and clinical manifestations. Variables ITB (n = 22, 15.38%) Non-ITB (n = 121, 84.62%) Total (n = 143) p-value Subject characteristics Age (years), Median (IQR) 33.5 (24–55) 41 (29–57) 41 (28–57) 0.278 a Gender, n (%) Males 11 (50.00) 39 (32.23) 50 (34.97) 0.108 b Females 11 (50.00) 82 (67.77) 93 (65.03) Clinical manifestations Weight loss, n (%) 18 (81.82) 64 (52.89) 82 (57.34) 0.012 b * Night sweat, n (%) 2 (9.09) 4 (3.31) 6 (4.30) 0.213 b Cough, n (%) 3 (13.64) 4 (3.31) 7 (4.90) 0.039 b * Fever, n (%) 6 (27.27) 15 (12.40) 21 (14.69) 0.070 b Appetite loss, n (%) 13 (59.09) 37 (30.58) 50 (34.97) 0.010 b * Non-spesific abdominal pain, n (%) 17 (77.27) 106 (87.60) 123 (86.01) 0.199 b Chronic diarrhea, n (%) 18 (81.82) 68 (56.20) 86 (60.14) 0.024 b * Constipation, n (%) 18 (81.82) 77 (63.64) 95 (66.43) 0.097 b Alternating diarrhea and constipation, n (%) 18 (81.82) 67 (55.37) 85 (59.44) 0.020 b * Blood in stools, n (%) 10 (45.45) 67 (55.37) 77 (53.85) 0.391 b Mucus in stools, n (%) 10 (45.45) 68 (56.20) 78 (54.55) 0.352 b Blood and mucus in stools, n (%) 10 (45.45) 66 (54.55) 76 (53.15) 0.432 b TB history Contact history with TB subjects, n (%) 1 (4.55) 1 (0.83) 2 (1.40) 0.172 b Pulmonary and extrapulmonary TB history, n (%) 3 (13.64) 9 (7.44) 12 (8.39) 0.335 b a Analyzed using Mann-Whitney U test. b Analyzed using Chi-square test. * Statistically significance at p < 0.05. Laboratory findings In this study, laboratory findings among ITB and Non-ITB subjects were presented in Table 2 . Hematology test results (leukocytes, differential count, NLR, MLR) and IGRA showed no significant difference in ITB and Non-ITB subjects. However, ESR and blood ADA activity in ITB subjects were significantly higher than Non-ITB subjects (p < 0.0001 and p = 0.001, respectively). Stool HBD-2 level in this study was not significantly different in ITB and Non-ITB subjects (p = 0.170). Stool IFN-γ level in ITB subjects was significantly higher than Non-ITB subjects (p = 0.016). Stool TB PCR result was significantly different among ITB and Non-ITB subjects (p < 0.0001). The proportion of positive results for stool TB PCR in ITB subjects was 10/22 (45.5%), while none of the Non-ITB subjects had MTB detected. ROC curve analysis was generated for these laboratory findings that were tabulated and cut-off value were identified as shown in Table 2 . Table 2. Laboratory findings in ITB and Non-ITB subjects. Biomarkers ITB Non-ITB p-value Cut-off AUC Sensitivity Specificity Stool HBD-2 level (ng/mL), median (IQR) 13.19 (6.69–88.37) 35.83 (13.65–90,06) 0.170 b 31.14 0.592 68.15% 54.55% Stool IFN-γ level (pg/mL), median (IQR) 153.36 (63.19–647.88) 75.53 (31–163.05) 0.016 b * 75.76 0.661 72.73% 50.41% Blood ADA activity (IU/L), median (IQR) 15.42 (12.76–24.98) 11.96 (8.85–15.83) 0.001 b * 12.56 0.772 81.82% 60.33% Stool TB PCR (n, %) Positive 10 (45.5) 0 (0.0) < 0.0001 a * 45.45% 100.00% Negative 12 (54.5) 121 (100.0) Leukocytes (10 3 /μL), median (IQR) 7.63 (5.35–11.34) 6.98 (5.58–8.34) 0.406 b 6.98 0.556 54.55% 49.59% Basophil (%), median (IQR) 0.45 (0.3–0.62) 0.60 (0.40–0.80) 0.057 b 0.55 0.627 36.36% 48.76% Eosinophil (%), median (IQR) 1.25 (0.57–4.05) 1.9 (1–3.75) 0.193 b 1.85 0.587 36.36% 46.28% Neutrophil (%), mean (SD) 65.70 (SD 13.99) 60.89 (SD 11.49) 0.084 c 63.55 0.622 68.18% 60.33% Lymphocytes (%), mean (SD) 24.47 (SD 12.44) 28.68 (SD 9.79) 0.078 c 26.85 0.623 63.64% 60.33% Monocytes (%), median (IQR) 6.85 (4.5–8.17) 6.6 (5.4–7.9) 0.978 b 6.65 0.502 54.55% 53.72% NLR, median (IQR) 3.22 (1.60–4.75) 2.09 (1.56–2.97) 0.065 b 2.32 0.624 68.18% 61.98% MLR, median (IQR) 0.31 (0.19–0.45) 0.22 (0.18–0.28) 0.057 b 0.265 0.629 63.64% 66.12% ESR (mm), median (IQR) 65.00 (34.75–97.50) 25 (13–44) < 0.0001 b * 33.5 0.775 81.82% 66.12% Positive IGRA (n, %) Yes 12 (54.5) 39 (32.2) 0.055 a 54.55% 67.77% No 10 (45.5) 82 (67.8) a Analyzed using Chi-Square test. b Analyed using Mann-Whitney U test. c Analyzed using independent t-test. * Statistically significance at p < 0.05. Diagnostic parameters for differentiating ITB and non-ITB subjects In the initial model, the results of bivariate analysis (p < 0.25) to determine the potential diagnostic laboratory parameters for differentiating ITB and Non-ITB subjects are demonstrated in Table 3 . Stool HBD-2 levels, stool IFN-γ levels, blood ADA activity, stool TB PCR, basophil, eosinophil, neutrophil, lymphocytes, NLR, MLR, ESR, and IGRA have potential diagnostic laboratory parameters. These parameters were subjected to multiple regression analysis, and the results of multivariate analysis are demonstrated in Table 4 . However, the results of multivariate analysis showed that stool HBD-2 level, ESR, blood ADA activity, lymphocytes, stool TB PCR, and NLR were more significant candidates as diagnostic parameters for ITB than Non-ITB (p < 0.05). Table 3. Bivariate analysis based on cut-off value on potential diagnostic parameters for ITB diagnosis. Biomarkers ITB Non-ITB PR (95% CI) p-value Stool HBD-2 level (ng/mL) <31.14 15 (21.43%) 55 (78.57%) 2.234 (0.969–5.151) 0.060 ≥31.14 7 (9.59%) 66 (90.41%) Stool IFN-γ level (pg/mL) ≥75.76 16 (21.05%) 60 (78.95%) 2.351 (0.973–5.679) 0.057 <75.76 6 (8.96%) 61 (91.04%) Blood ADA activitiy (IU/L) ≥12.56 18 (27.27%) 48 (72.73%) 5.25 (1.863–14.793) 0.002 <12.56 4 (5.19%) 73 (94.81%) Stool TB PCR (n,%) Positive 10 (100.0%) 0 (0.0%) 11.083 (6.448–10.049) <0.0001 Negative 12 (9.02%) 121 (90.98%) Leukocytes (10 3 /μL) ≥6.98 12 (16.44%) 61 (83.56%) 1.151 (0.530–2.498) 0.723 <6.98 10 (14.29%) 60 (85.71%) Basophil (%) ≥0.55 8 (11.43%) 62 (88.57%) 0.596 (0.265–1.336) 0.209 <0.55 14 (19.18%) 59 (80.82%) Eosinophil (%) ≥1.85 8 (10.96%) 65 (89.04%) 0.548 (0.244–1.228) 0.144 <1.85 14 (20.00%) 56 (80.00%) Neutrophil (%) ≥63.55 15 (23.81%) 48 (76.19%) 2.721 (1,178–6.285) 0.019 <63.55 7 (8.75%) 73 (91.21%) Lymphocytes (%) <26.85 14 (22.58%) 48 (77.42%) 2.581 (1.109–6.005) 0.044 ≥26.85 8 (9.88%) 73 (90.12%) Monocytes (%) ≥6.65 12 (17.65%) 56 (82.35%) 1.323 (0.609–2.873) 0.478 <6.65 10 (13.33%) 65 (86.67%) NLR ≥2.32 15 (24.59%) 46 (75.41%) 2.880 (1.248–6.649) 0.013 <2.32 7 (8.54%) 75 (91.46%) MLR ≥0.265 14 (25.45%) 41 (74.55%) 2.800 (1.254–6.253) 0.012 <0.265 8 (9.09%) 80 (90.91%) ESR (mm) ≥33.5 18 (30.51%) 41 (69.49%) 6.407 (2.277–18.029) <0.0001 <33.5 4 (4.76%) 80 (95.24%) Positive IGRA (n,%) Yes 12 (23.53%) 39 (76.47%) 2.165 (1.003–4.670) 0.049 No 10 (10.87%) 82 (89.13%) Table 4. Multiple regression analysis on diagnostic parameters for differentiating ITB and Non-ITB subjects. Diagnostic parameters PR (95% CI) p-value β SE β/SE Score Rounded off scores Initial model Stool HBD-2 level 2.469 (1.250–4.876) 0.009 - - - - - Stool IFN-γ level 0.914 (0.410–2.038) 0.828 - - - - - Blood ADA activity 3.585 (1.258–10.212) 0.017 - - - - - Stool TB PCR 4.181 (1.682–10.391) 0.002 - - - - - Basophil 1.244 (0.633–2.445) 0.526 - - - - - Eosinophil 0.842 (0.375–1.893) 0.679 - - - - - Neutrophil 0.386 (0.087–1.719) 0.212 - - - - - Lymphocytes 5.497 (1.752–17.250) 0.003 - - - - - NLR 14.529 (2.517–83.846) 0.003 - - - - - MLR 0.967 (0.431–2.172) 0.937 - - - - - ESR (mm) 3.000 (1.101–8.175) 0.032 - - - - - Positive IGRA 0.930 (0.420–2.056) 0.858 - - - - - Final model Stool HBD-2 (<31.14 ng/mL) 2.392 (1.315–4.315) 0.004 0.872 0.463 1.88 1.161 1 ESR (≥33.5 mm) 2.906 (1.018–8.298) 0.046 1.067 0.629 1.70 1.0459 1 Blood ADA activitiy (≥12.56 IU/L) 3.205 (1.055–9.731) 0.040 1.164 0.646 1.80 1.1110 1 Lymphocytes (≥26.85 %) 5.608 (1.804–17.431) 0.003 1.724 1.063 1.62 1 1 Stool TB PCR (positive) 4.068 (1.953–8.472) <0.0001 1.403 0.528 2.66 1.638 2 NLR (≥2.32) 5.743 (1.834–17.985) 0.003 1.748 1.039 1.68 1.037 1 Determination of scoring system The scoring system based on the regression coefficient β value and standard errors of the independent diagnostic parameters in multiple regression analysis is displayed in Table 4 . After rounding off to the nearest integer, the scores of each parameter in the scoring system are defined as follows: 1 point for stool HBD-2 levels, ESR, blood ADA activity, lymphocytes, NLR, and 2 points for stool TB PCR. This combination of 6 biomarkers is referred to as the HEALTH scoring system. The total score of ITB subjects showed significantly higher than Non-ITB subjects (mean, 4.27 vs. 2.17, p < 0.0001). In this scoring system, we calculated the probability of ITB in each score, as shown in Table 5 . It was observed that there is a synergistic relationship between an increasing total score and a higher percentage of subjects with ITB. To determine a cut-off score that indicates whether a subject is considered to have ITB, a statistical cut-off score between sensitivity and specificity was searched for, which can be seen in Table 6 . Table 5. Probability of ITB in each score. Total scores ITB Total Probability (%) No Yes 0 1 0 1 0.46 1 25 0 25 3.19 2 53 2 55 2.20 3 36 5 41 13.63 4 6 5 11 52.55 5 0 5 5 88.68 6 0 5 5 98.20 Table 6. Sensitivity and specificity of scores at different cut-off point based on ROC curve analysis. Cut-off score Sensitivity Specificity Classified LR+ LR- (≥0) 100.00% 0.00% 15.38% 1 (≥1) 100.00% 0.83% 16.08% 1.0083 0 (≥2) 100.00% 21.49% 33.57% 1.2737 0 (≥3) 90.91% 65.29% 69.23% 2.619 0.1392 (≥4) 68.18% 95.04% 90.91% 13.75 0.3348 (≥5) 45.45% 100.00% 91.61% 0.5455 (≥6) 22.73% 100.00% 88.11% 0.7727 (>6) 0.00% 100.00% 84.62% 1 According to the ROC curve, the cut-off score of ≥ 4 yielded the largest AUC of 0.8978 (95% CI 0.823–0.971) with a sensitivity of 68.18% (95% CI 45.13%–86.14%) and specificity of 95.04% (95% CI 89.52%–98.16%) ( Figure 1 ). The HEALTH scoring system was then applied to our data and the subjects were split into two groups: Scores < 4 (Non-ITB) and scores ≥ 4 (ITB) as shown in Table 7 . It was found that the HEALTH scoring system with a cut-off score of ≥ 4 successfully predicted 15 of 22 ITB cases and the scores < 4 successfully predicted 115 of 121 Non-ITB cases, yielding positive predictive value of 71.43% (95% CI 52.14%–85.16%) and negative predictive value of 94.26% (95% CI 89.90%–96.81%). The new proposed scoring system for differentiating ITB and Non-ITB can be seen in Table 8 . Figure 1. Sensitivity and specificity of scoring system based on ROC curve analysis. Table 7. Validation of the HEALTH scoring system for differentiating ITB and Non-ITB subjects. Total scores Actual pathological diagnosis ITB Non-ITB <4 7 (5.74%) 115 (94.26%) ** ≥4 15 (71.43%) * 6 (28.57%) Total 22 121 * Positive Predictive Value = 71.4%. ** Negative Predictive Value = 94.3%. Table 8. New proposed of the HEALTH scoring system for differentiating ITB and Non-ITB subjects. Diagnostic parameters Scores Stool HBD-2 levels (ng/mL) <31.14 1 ≥31.14 0 ESR (mm) ≥33.5 1 <33.5 0 Blood ADA activity (IU/mL) ≥12.56 1 <12.56 0 Lymphocytes (%) <26.85 0 ≥26.85 1 Stool TB PCR Positive 2 Negative 0 NLR ≥2.32 1 <2.32 0 Total Scores ≥4 ITB <4 Non-ITB Calibration and validation of scoring system In this study, we calibrated the HEALTH scoring system with the Hosmer-Lemeshow test and the result was p = 0.896. This result showed good calibration based on the statistical significance of the Hosmer-Lemeshow test p > 0.05. This scoring system was also validated based on the bootstrapping method to ensure that the scoring system can be used on a population with the same characteristics as subject characteristics in this study, with a larger number of subjects. Internal validation was carried out using the bootstrapping method 1000 times and the Hosmer Lemeshow test result was p = 0.896, meaning this scoring system has good internal validation. Discussion Scoring systems in laboratory diagnostics play a crucial role in improving the accuracy and efficiency of disease diagnosis. By integrating specific biomarkers and clinical data, these systems enhance the ability to distinguish between similar diseases, predict disease progression, and guide treatment decisions. The development and validation of these systems across various diseases highlight their potential to transform clinical practice and improve patient outcomes. In Indonesia, a laboratory panel using a scoring system to diagnose ITB has not been developed. There is currently no stand-alone laboratory test in ITB management, which creates opportunities for developing laboratory examinations using various biomarkers to diagnose ITB according to its pathophysiology. These examinations include routine examinations (such as hematology, IGRA, and blood ADA activity) and specific examinations (such as TB PCR). This study used multiple regression and ROC curves to determine independent diagnostic parameters. After multivariate analysis, we developed and validated a combination of 6 biomarkers from blood and stool specimens to differentiate ITB and other gastrointestinal diseases, including stool HBD-2 level, ESR, blood ADA activity, lymphocytes, stool TB PCR, and NLR. Stool HBD-2 levels in the ITB subjects were lower than Non-ITB subjects. Researchers have noted limited studies on stool HBD-2 levels in ITB subjects. The stool HBD-2 levels can stimulated through two pathways: one involves pro-inflammatory cytokines (IL-1β, IL-1α, and TNF-α), while the other involves microbial components like lipopolysaccharides and peptidoglycan. The elevated stool HBD-2 levels in Non-ITB subjects may result from activation through both pathways: the NFκB pathway and mitogen-activated protein kinase (MAPK), which produce pro-inflammatory cytokines similar to those seen in IBD, as well as pathways activated by microbial component in infectious colitis or ileitis. Stool HBD-2 is a crucial antimicrobial protein that mediates the innate immune response. The production of stool HBD-2 through the microbial component pathway is non-specific and does not distinguish between MTB and non-MTB microbes. The ITB subjects in this study were suspected to have chronic infections, which may account for their relatively low stool HBD-2 levels. 34 , 35 The ESR in the ITB subjects was significantly higher compared to Non-ITB subjects. The ESR test, which has a high sensitivity of 81%, can effectively serve as a screening tool for ITB. However, there are limited studies explicitly focusing on ESR in ITB cases. Most studies have primarily examined ESR in pulmonary TB cases, as documented by Khalil et al., 36 Bashir et al., 37 and Chong. 38 The ESR test measures acute-phase proteins produced in acute and chronic diseases. In ITB, pro-inflammatory cytokines stimulate the liver to produce these proteins, including fibrinogen, which can elevate ESR results. Chronic diseases like TB often lead to increased immunoglobulin levels as part of the immune response to persistent infection. These positively charged immunoglobulin proteins can bind to the negatively charged surface of erythrocytes, promoting the formation of erythrocyte rouleaux and thus resulting in a rapid ESR. Despite its usefulness, the ESR test has limitations. It is influenced by anemia and hypoalbuminemia, leading to a false increase in the ESR. Therefore, it is crucial to consider the presence of anemia and hypoalbuminemia when interpreting ESR results in ITB subjects. Blood ADA activity in ITB subjects was significantly higher than Non-ITB subjects. This finding aligns with Salmanzadeh et al., who observed significantly higher blood ADA activity in subjects with pulmonary tuberculosis than those with pneumonia, lung malignancies, and healthy controls. 39 It is important to highlight that ADA activity measured in the blood does not pinpoint the exact production source but reflects the overall ADA activity from activated lymphocytes and monocytes throughout the body, including areas affected by MTB. Currently, ADA tests cannot be performed on stool specimens or biopsy tissue, making it impossible to determine local ADA production in the intestine in ITB. The increased number of monocytes in ITB subjects correlates with the elevated ADA activity, suggesting that monocytes play a more significant role than other cells in the context of ITB. 40 , 41 The percentage of lymphocytes in the ITB subjects showed no significant difference than Non-ITB subjects and was still within the normal range (reference value: 20–40%). In TB infection, the percentage of lymphocytes in the blood often appears in the normal range due to a complex mechanism of immune responses. While some lymphocyte subsets may be changed, the overall lymphocytes can remain within normal ranges. Infection of MTB can cause shifts in lymphocyte homeostasis, with some subsets like CD8+ T-cells and B-cells increasing, while others like CD4+ T-cells decrease. These changes can balance out, resulting in a normal overall percentage of lymphocytes. 42 , 43 In this study, the proportion of positive stool TB PCR was significantly higher in the ITB subjects than Non-ITB subjects. The results of stool TB PCR in this study are similar to those reported by Suparmin et al. 6 The high proportion of positive stool TB PCR can be influenced by the high endemicity of TB in the population. This study also showed “acceptable” specificity (100%) for stool TB PCR test in differentiating ITB and Non-ITB subjects. This finding aligns with Gaur et al., who reported that stool TB PCR tests showed high specificity in EPTB subjects. 44 PCR is a recent advanced diagnostic method increasingly used to diagnose TB. Unlike biopsy, stool TB PCR is non-invasive and less prone to sampling error. The detailed mechanism of MTB DNA shedding in stool remains to be investigated. A recent study indicates a two-way interaction between the gut and lung (gut-lung axis) in the transfer of metabolites, immune cells, and bacterial fragments via the bloodstream. 45 However, these findings require further investigation, as the mechanistic basis of ITB is still unclear. A major challenge in diagnosing ITB is its non-specific and diverse clinical manifestations, which delay confirmation. Therefore, detecting MTB DNA in ITB subjects’ stool may serve as a valuable rule-in test. In the present study, the NLR, an indicator of acute infection or inflammation, remained within the normal range and showed no significant difference between ITB and Non-ITB subjects. This finding contrasts with the results reported by Rees et al., who noted higher NLR levels in symptomatic pulmonary TB cases compared to controls. 21 This discrepancy may be attributed to the role of neutrophils in non-granulomatous and acute inflammatory conditions. NRL is a newly identified biomarker of inflammation that is simpler to measure and relatively stable compared to other inflammatory biomarkers. However, the relationship between NLR and clinical outcomes can be influenced by several factors, including comorbidities, immune status, and virulence of the tuberculosis strain. Additionally, NLR can vary significantly between individuals based on age, gender, and ethnicity. It can also fluctuate over time due to stress, medications, and physiological conditions. Developing laboratory panels using a scoring system based on subjects’ clinical biomarkers is nothing new. For managing the risk of patient severity or differentiating the disease from another disease, several previous studies developed laboratory scoring systems for infectious diseases, such as a lab score system for predicting COVID-19 patient severity, differentiating subjects with severe and mild H1N1 infection, and discrimination of TB infection from both PTB and EPTB disease. 46 – 48 However, researchers have pointed out that there are still very few reports regarding laboratory panels for differentiating ITB from other gastrointestinal diseases. Makharia et al. developed scoring system with 4 parameters (blood in stool, weight loss, histologically focally enhanced colitis, and involvement of sigmoid colon) to differentiate intestinal tuberculosis and Crohn’s disease. 28 Shi et al. mentioned the use of various parameters such as good response to ATT and positive IGRA, combined with clinical, endoscopy, radiology, and histopathology to diagnose intestinal tubeculosis, but not in a scoring system panel. 14 The strength of the HEALTH scoring system is that this is the first study based on laboratory findings that predicted the probability of ITB. Additionally, the laboratory tests involved in this scoring system are user-friendly and non-invasive, as they only require blood and stool samples. In Indonesia, this scoring system can be utilized by healthcare facilities, regardless of whether they have colonoscopy and histopathology services. Healthcare facilities that lack these services can use the HEALTH scoring system to assist clinicians in managing ITB. On the other hand, healthcare facilities equipped with colonoscopy and histopathology services can use the HEALTH scoring system to identify patients who should undergo colonoscopy, thereby reducing waiting times for colonoscopy examinations. It should be noted that our study has several limitations. This study was a single-center cross-sectional study, and the reagents used to examine stool IFN-γ in Indonesia do not include in vitro diagnostic reagents. Independent external validation, cost-effectiveness analysis, and multicenter randomized prospective study must be designed to validate the HEALTH scoring system. Conclusion This study developed and validated a laboratory panel called the HEALTH scoring system based on clinical biomarkers of stool HBD-2 level, ESR, blood ADA activity, lymphocytes, stool TB PCR, and NLR, which could be used to differentiate ITB from other gastrointestinal diseases. Ethical considerations This study was approved by the Ethics Committee, Faculty of Medicine, Universitas Indonesia–Dr. Cipto Mangunkusumo National Central General Hospital (KET-1498/UN2.F1/ETIK/PPM.00.02/2020, Date: 10.12.2020 and ND-3/UN2.F1/ETIK/PPM.00.02/2022, Date: 10.01.2022). All study participants or participants’ family have given their written informed consent regarding their participation and data publication in this study. Software availability Software availability statement: The statistical analyses performed in this article using SPSS version 20 and STATA 14 software can be conducted using the freely accessible software R (programming language) https://www.r-project.org/ Data availability Underlying data Figshare: Laboratory Panel for Intestinal Tuberculosis in Indonesia. https://doi.org/10.6084/m9.figshare.27957855 . 49 The project contains the following underlying data: − DATA SET - Laboratory panel of ITB.xlsx Data are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0). Acknowledgement The authors would thank to the participants, ITB Project Team, and the expert committee for their participation in this study. References 1. World Health Organization: Global Tuberculosis Report 2022.2022 [cited 2023 May 16]. Reference Source 2. World Health Organization: Global Tuberculosis Report 2020.2020 [cited 2022 Aug 12]. Reference Source 3. 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Indrasari ND, Simadibrata M, Rustamadji P, et al. : Laboratory Panel for Intestinal Tuberculosis in Indonesia. (Dataset) Figshare.com. 2024. Publisher Full Text Comments on this article Comments (0) Version 1 VERSION 1 PUBLISHED 17 Jan 2025 ADD YOUR COMMENT Comment Author details Author details 1 Dr. Cipto Mangunkusumo National Central General Hospital, Jakarta, Indonesia 2 Department of Clinical Pathology, Faculty of Medicine, Universitas Indonesia, Jakarta, Indonesia 3 Department of Internal Medicine, Faculty of Medicine, Universitas Indonesia, Jakarta, Indonesia 4 Department of Anatomical Pathology, Faculty of Medicine, Universitas Indonesia, Jakarta, Indonesia 5 Department of Community Medicine, Faculty of Medicine, Universitas Indonesia, Jakarta, Indonesia 6 Department of Parasitology, Faculty of Medicine, Universitas Indonesia, Jakarta, Indonesia 7 Dr. Hasan Sadikin General Hospital, Bandung, Indonesia 8 Department of Clinical Pathology, Faculty of Medicine, Universitas Padjajaran, Bandung, Indonesia Nuri Dyah Indrasari Roles: Conceptualization, Data Curation, Formal Analysis, Funding Acquisition, Investigation, Methodology, Project Administration, Resources, Software, Supervision, Validation, Visualization, Writing – Original Draft Preparation, Writing – Review & Editing Marcellus Simadibrata Roles: Conceptualization, Data Curation, Formal Analysis, Investigation, Methodology, Supervision, Validation Primariadewi Rustamadji Roles: Conceptualization, Investigation, Supervision, Validation Yusra Yusra Roles: Conceptualization, Methodology, Supervision, Validation Suhendro Suwarto Roles: Conceptualization, Data Curation, Formal Analysis, Methodology, Supervision, Validation Aria Kekalih Roles: Conceptualization, Data Curation, Formal Analysis, Methodology, Software, Supervision, Validation Heri Wibowo Roles: Conceptualization, Supervision, Validation Ida Parwati Roles: Conceptualization, Methodology, Supervision, Validation Alida Roswita Harahap Roles: Conceptualization, Supervision, Validation Nindy Auliana Roles: Data Curation, Formal Analysis, Project Administration, Resources, Software, Visualization, Writing – Original Draft Preparation, Writing – Review & Editing Competing interests No competing interests were disclosed. Grant information The author(s) declared that no grants were involved in supporting this work. Article Versions (1) version 1 Published: 17 Jan 2025, 14:103 https://doi.org/10.12688/f1000research.160489.1 Copyright © 2025 Indrasari ND et al . This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Download Export To Sciwheel Bibtex EndNote ProCite Ref. Manager (RIS) Sente metrics Views Downloads F1000Research - - PubMed Central info_outline Data from PMC are received and updated monthly. - - Citations open_in_new 0 open_in_new 0 open_in_new SEE MORE DETAILS CITE how to cite this article Indrasari ND, Simadibrata M, Rustamadji P et al. Development and validation of the HEALTH scoring system = A novel and non-invasive laboratory panel to differentiate intestinal tuberculosis from other gastrointestinal diseases [version 1; peer review: 1 approved, 1 approved with reservations] . F1000Research 2025, 14 :103 ( https://doi.org/10.12688/f1000research.160489.1 ) NOTE: If applicable, it is important to ensure the information in square brackets after the title is included in all citations of this article. COPY CITATION DETAILS track receive updates on this article Track an article to receive email alerts on any updates to this article. TRACK THIS ARTICLE Share Open Peer Review Current Reviewer Status: ? Key to Reviewer Statuses VIEW HIDE Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions Version 1 VERSION 1 PUBLISHED 17 Jan 2025 Views 0 Cite How to cite this report: Batra N. Reviewer Report For: Development and validation of the HEALTH scoring system = A novel and non-invasive laboratory panel to differentiate intestinal tuberculosis from other gastrointestinal diseases [version 1; peer review: 1 approved, 1 approved with reservations] . F1000Research 2025, 14 :103 ( https://doi.org/10.5256/f1000research.176395.r482025 ) The direct URL for this report is: https://f1000research.com/articles/14-103/v1#referee-response-482025 NOTE: it is important to ensure the information in square brackets after the title is included in this citation. Close Copy Citation Details Reviewer Report 12 May 2026 Nitish Batra , Datta Meghe Institute of Higher Education and Research, Nagpur, Maharashtra, India Approved with Reservations VIEWS 0 https://doi.org/10.5256/f1000research.176395.r482025 This manuscript addresses a clinically important problem that physicians frequently encounter in TB-endemic regions — distinguishing intestinal tuberculosis from other gastrointestinal diseases such as Crohn’s disease and malignancy. The idea of developing a non-invasive laboratory-based scoring system ... Continue reading READ ALL This manuscript addresses a clinically important problem that physicians frequently encounter in TB-endemic regions — distinguishing intestinal tuberculosis from other gastrointestinal diseases such as Crohn’s disease and malignancy. The idea of developing a non-invasive laboratory-based scoring system is highly relevant, especially for settings where access to colonoscopy and histopathology may be limited. The authors should be appreciated for combining several laboratory biomarkers into a practical scoring model. The use of stool-based testing together with routine blood parameters makes the proposed HEALTH scoring system potentially useful in real-world clinical practice. The manuscript also provides a detailed background and discusses the biological relevance of the included biomarkers. That said, there are several concerns that need to be addressed before the study can be considered for indexing. The most important limitation is the relatively small number of ITB patients included in the study. Only 22 confirmed ITB cases were analyzed, which raises concerns about the stability and reliability of the regression model. With multiple variables included in the analysis, there is a significant risk of overfitting. The authors should discuss this issue in greater detail. Another concern relates to the diagnostic criteria used for defining ITB. Including “response to anti-tuberculosis therapy” as part of the diagnostic standard may introduce bias because treatment response is not entirely objective. Clarification regarding how final diagnoses were established would strengthen the study. The scoring system itself is interesting, but the process used to assign points is not sufficiently clear. A more transparent explanation of how each score was derived from the regression coefficients would improve understanding and reproducibility. The reported specificity is excellent, but sensitivity is only moderate. This suggests that the HEALTH score may be more useful as a supportive or rule-in tool rather than a screening test. The clinical implications of missed ITB cases should therefore be discussed. The manuscript would also benefit from external validation in a larger multicenter population. Since this was a single-center study conducted in Indonesia, the generalizability of the findings remains uncertain. There are also some minor language and formatting issues throughout the paper. Several grammatical errors and incomplete table entries should be corrected during revision. Overall, the study is interesting and clinically relevant, and the proposed scoring system has potential value. However, additional clarification regarding methodology, statistical analysis, and validation is needed to improve the strength of the conclusions. Is the work clearly and accurately presented and does it cite the current literature? Partly Is the study design appropriate and is the work technically sound? Yes Are sufficient details of methods and analysis provided to allow replication by others? Partly If applicable, is the statistical analysis and its interpretation appropriate? Partly Are all the source data underlying the results available to ensure full reproducibility? Yes Are the conclusions drawn adequately supported by the results? Yes Competing Interests: No competing interests were disclosed. Reviewer Expertise: Internal Medecine , Nephrology I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above. Close READ LESS CITE CITE HOW TO CITE THIS REPORT Batra N. Reviewer Report For: Development and validation of the HEALTH scoring system = A novel and non-invasive laboratory panel to differentiate intestinal tuberculosis from other gastrointestinal diseases [version 1; peer review: 1 approved, 1 approved with reservations] . F1000Research 2025, 14 :103 ( https://doi.org/10.5256/f1000research.176395.r482025 ) The direct URL for this report is: https://f1000research.com/articles/14-103/v1#referee-response-482025 NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article. COPY CITATION DETAILS Report a concern Respond or Comment COMMENT ON THIS REPORT Views 0 Cite How to cite this report: Puspitasari Y. Reviewer Report For: Development and validation of the HEALTH scoring system = A novel and non-invasive laboratory panel to differentiate intestinal tuberculosis from other gastrointestinal diseases [version 1; peer review: 1 approved, 1 approved with reservations] . F1000Research 2025, 14 :103 ( https://doi.org/10.5256/f1000research.176395.r434620 ) The direct URL for this report is: https://f1000research.com/articles/14-103/v1#referee-response-434620 NOTE: it is important to ensure the information in square brackets after the title is included in this citation. Close Copy Citation Details Reviewer Report 30 Dec 2025 Yessy Puspitasari , Clinical Pathology, Universitas Airlangga, Surabaya, East Java, Indonesia Approved VIEWS 0 https://doi.org/10.5256/f1000research.176395.r434620 The work is clearly and accurately presented, with a coherent structure and logical flow throughout the manuscript. The methods and results are described in sufficient detail to allow reproducibility.While the manuscript cites relevant literature, several recent studies appear to be ... Continue reading READ ALL The work is clearly and accurately presented, with a coherent structure and logical flow throughout the manuscript. The methods and results are described in sufficient detail to allow reproducibility.While the manuscript cites relevant literature, several recent studies appear to be missing, especially those published within the last 3–5 years that could further strengthen the background and discussion. Updating the references and refining the clarity of certain paragraphs would greatly enhance the manuscript. Is the work clearly and accurately presented and does it cite the current literature? Partly Is the study design appropriate and is the work technically sound? Yes Are sufficient details of methods and analysis provided to allow replication by others? Yes If applicable, is the statistical analysis and its interpretation appropriate? Yes Are all the source data underlying the results available to ensure full reproducibility? Yes Are the conclusions drawn adequately supported by the results? Yes Competing Interests: No competing interests were disclosed. Reviewer Expertise: gastrointestinal molecular, Hepatology, Cancer, Infectious disease I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. Close READ LESS CITE CITE HOW TO CITE THIS REPORT Puspitasari Y. Reviewer Report For: Development and validation of the HEALTH scoring system = A novel and non-invasive laboratory panel to differentiate intestinal tuberculosis from other gastrointestinal diseases [version 1; peer review: 1 approved, 1 approved with reservations] . F1000Research 2025, 14 :103 ( https://doi.org/10.5256/f1000research.176395.r434620 ) The direct URL for this report is: https://f1000research.com/articles/14-103/v1#referee-response-434620 NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article. COPY CITATION DETAILS Report a concern Respond or Comment COMMENT ON THIS REPORT Comments on this article Comments (0) Version 1 VERSION 1 PUBLISHED 17 Jan 2025 ADD YOUR COMMENT Comment keyboard_arrow_left keyboard_arrow_right Open Peer Review Reviewer Status info_outline Alongside their report, reviewers assign a status to the article: Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions Reviewer Reports Invited Reviewers 1 2 Version 1 17 Jan 25 read read Yessy Puspitasari , Universitas Airlangga, Surabaya, Indonesia Nitish Batra , Datta Meghe Institute of Higher Education and Research, Nagpur, India Comments on this article All Comments (0) Add a comment Sign up for content alerts Sign Up You are now signed up to receive this alert Browse by related subjects keyboard_arrow_left Back to all reports Reviewer Report 0 Views copyright © 2026 Batra N. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 12 May 2026 | for Version 1 Nitish Batra , Datta Meghe Institute of Higher Education and Research, Nagpur, Maharashtra, India 0 Views copyright © 2026 Batra N. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. format_quote Cite this report speaker_notes Responses (0) Approved With Reservations info_outline Alongside their report, reviewers assign a status to the article: Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions This manuscript addresses a clinically important problem that physicians frequently encounter in TB-endemic regions — distinguishing intestinal tuberculosis from other gastrointestinal diseases such as Crohn’s disease and malignancy. The idea of developing a non-invasive laboratory-based scoring system is highly relevant, especially for settings where access to colonoscopy and histopathology may be limited. The authors should be appreciated for combining several laboratory biomarkers into a practical scoring model. The use of stool-based testing together with routine blood parameters makes the proposed HEALTH scoring system potentially useful in real-world clinical practice. The manuscript also provides a detailed background and discusses the biological relevance of the included biomarkers. That said, there are several concerns that need to be addressed before the study can be considered for indexing. The most important limitation is the relatively small number of ITB patients included in the study. Only 22 confirmed ITB cases were analyzed, which raises concerns about the stability and reliability of the regression model. With multiple variables included in the analysis, there is a significant risk of overfitting. The authors should discuss this issue in greater detail. Another concern relates to the diagnostic criteria used for defining ITB. Including “response to anti-tuberculosis therapy” as part of the diagnostic standard may introduce bias because treatment response is not entirely objective. Clarification regarding how final diagnoses were established would strengthen the study. The scoring system itself is interesting, but the process used to assign points is not sufficiently clear. A more transparent explanation of how each score was derived from the regression coefficients would improve understanding and reproducibility. The reported specificity is excellent, but sensitivity is only moderate. This suggests that the HEALTH score may be more useful as a supportive or rule-in tool rather than a screening test. The clinical implications of missed ITB cases should therefore be discussed. The manuscript would also benefit from external validation in a larger multicenter population. Since this was a single-center study conducted in Indonesia, the generalizability of the findings remains uncertain. There are also some minor language and formatting issues throughout the paper. Several grammatical errors and incomplete table entries should be corrected during revision. Overall, the study is interesting and clinically relevant, and the proposed scoring system has potential value. However, additional clarification regarding methodology, statistical analysis, and validation is needed to improve the strength of the conclusions. Is the work clearly and accurately presented and does it cite the current literature? Partly Is the study design appropriate and is the work technically sound? Yes Are sufficient details of methods and analysis provided to allow replication by others? Partly If applicable, is the statistical analysis and its interpretation appropriate? Partly Are all the source data underlying the results available to ensure full reproducibility? Yes Are the conclusions drawn adequately supported by the results? Yes Competing Interests No competing interests were disclosed. Reviewer Expertise Internal Medecine , Nephrology I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above. reply Respond to this report Responses (0) Batra N. Peer Review Report For: Development and validation of the HEALTH scoring system = A novel and non-invasive laboratory panel to differentiate intestinal tuberculosis from other gastrointestinal diseases [version 1; peer review: 1 approved, 1 approved with reservations] . F1000Research 2025, 14 :103 ( https://doi.org/10.5256/f1000research.176395.r482025) NOTE: it is important to ensure the information in square brackets after the title is included in this citation. The direct URL for this report is: https://f1000research.com/articles/14-103/v1#referee-response-482025 keyboard_arrow_left Back to all reports Reviewer Report 0 Views copyright © 2026 Puspitasari Y. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 30 Dec 2025 | for Version 1 Yessy Puspitasari , Clinical Pathology, Universitas Airlangga, Surabaya, East Java, Indonesia 0 Views copyright © 2026 Puspitasari Y. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. format_quote Cite this report speaker_notes Responses (0) Approved info_outline Alongside their report, reviewers assign a status to the article: Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions The work is clearly and accurately presented, with a coherent structure and logical flow throughout the manuscript. The methods and results are described in sufficient detail to allow reproducibility.While the manuscript cites relevant literature, several recent studies appear to be missing, especially those published within the last 3–5 years that could further strengthen the background and discussion. Updating the references and refining the clarity of certain paragraphs would greatly enhance the manuscript. Is the work clearly and accurately presented and does it cite the current literature? Partly Is the study design appropriate and is the work technically sound? Yes Are sufficient details of methods and analysis provided to allow replication by others? Yes If applicable, is the statistical analysis and its interpretation appropriate? Yes Are all the source data underlying the results available to ensure full reproducibility? Yes Are the conclusions drawn adequately supported by the results? Yes Competing Interests No competing interests were disclosed. Reviewer Expertise gastrointestinal molecular, Hepatology, Cancer, Infectious disease I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. reply Respond to this report Responses (0) Puspitasari Y. Peer Review Report For: Development and validation of the HEALTH scoring system = A novel and non-invasive laboratory panel to differentiate intestinal tuberculosis from other gastrointestinal diseases [version 1; peer review: 1 approved, 1 approved with reservations] . F1000Research 2025, 14 :103 ( https://doi.org/10.5256/f1000research.176395.r434620) NOTE: it is important to ensure the information in square brackets after the title is included in this citation. The direct URL for this report is: https://f1000research.com/articles/14-103/v1#referee-response-434620 Alongside their report, reviewers assign a status to the article: Approved - the paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations - A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved - fundamental flaws in the paper seriously undermine the findings and conclusions Adjust parameters to alter display View on desktop for interactive features Includes Interactive Elements View on desktop for interactive features Competing Interests Policy Provide sufficient details of any financial or non-financial competing interests to enable users to assess whether your comments might lead a reasonable person to question your impartiality. 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