Keywords
Drug resistant Tuberculosis, Mumbai, delays, pathway to TB care
Drug resistant Tuberculosis, Mumbai, delays, pathway to TB care
The rising threat of multidrug resistant-tuberculosis (MDR-TB), defined as in vitro resistance to at least isoniazid and rifampicin, necessitates early detection of drug resistance and appropriate treatment initiation. A total of 480,000 MDR-TB cases are identified annually worldwide, accounting for 3.3% of newly diagnosed TB patients and 20% of retreatment TB patients1,2. An estimated 71,000 MDR-TB cases are reported from India, making it not only a major public health threat, but a huge economic burden on patients and health-systems as well. Mumbai, a fast growing urban metropolis in India with about 60% population living in vulnerable settings, has become the epicenter of various forms of MDR-TB3. Whilst national estimates for MDR-TB are 2.5% among new and 16% among retreatment patients1, reports from the city have recorded rates as high as 24% among new and 41% in retreatment patients4.
A patient with TB continues to be infectious until initiated on effective treatment. It is therefore imperative to understand the amount of time taken to detect patients with DR-TB and initiate them on appropriate treatment. This study looks at the durations from the onset of symptoms until initiation of appropriate treatment and tries to understand the type of patients that show maximum delay in accessing care.
Between April and July 2014, a population-based, two-stage, retrospective study was conducted in 15 high TB burden wards. BMGF consultants had provided the estimated sample size of around 100 TB cases based on TB prevalence surveys conducted in rural areas (N=D*Z2(p*q)/(e2)).
The first stage involved identification of patients treated for TB with a household (HH) survey, using a multistage cluster approach from the 2011 Census Enumerated Block (CEB) maps. A total of 153 pulmonary TB cases were identified in stage 1 based on treatment details, e.g. doctor's prescriptions, case files, lab reports, anti-TB treatment cards, anti-TB treatment blister packs, etc.
The second stage involved in-depth interviews of identified TB patients who were treated for pulmonary TB in Mumbai and had completed their anti-TB treatment in the past six months. A total of 82 patients consented to being interviewed using a pre-tested open-ended semi-structured interview schedule (Supplementary File 1). Pre-testing was conducted as per study protocol on six known TB cases from K/East ward who were excluded from the final study sample. Of the 82 patients that consented to be interviewed, 23 DR-TB patients were identified (28%), and these interviews were included in the present analysis only. The data from the remaining 59 patients has been previously published5.
Figure 1 shows the selection flowchart for the participants.
The figure depicts the selection of patients for inclusion in the study and subset analysis presented.
The 23 patients that were included in this study came from 10 of the 15 high burden TB wards namely: M/East (8 patients), H/East (2 patients), M/West (2 patients), F/North (2 patients), P/North (1 patient), G/North (2 patients), R/South (1 patient), L (1 patient), N (3 patients), S (1 patient).
All patient interviews were conducted at the participants’ residence by trained health researchers.
Patients were interviewed using a semi structured interview guide (Supplementary File 1) in their preferred local language (Hindi or Marathi) at a time and date convenient to them. Patient anonymity regarding name and address was maintained through a unique identification number. Interviews were audio recorded.
At the end of the interview, quantitative data were filled on physical formats by the researchers (Supplementary File 2). For the purpose of quality check, three levels of verification by listening to recorded interviews were conducted. First, each researcher team cross-checked the quantitative data forms of another research team. Further 25% interviews were cross-checked by senior researchers for errors, and finally a set of random 10% interviews were checked by consultants to the study.
The data was entered in CSPro v5, and exported into SPSS v19 (SPSS, Inc., Chicago, IL, USA) for analysis. The total time taken from onset of TB symptoms to first care-seeking and until initiation of DR-TB treatment was estimated by dates collected for various events and presented as medians, means and interquartile range (in days). Pathways for new and re-treatment patients were compared using independent t-test with significance established at P values ≤ 0.05.
Ethical approval was obtained from the Institutional Ethics Committee (IEC) of the Foundation for Medical Research (vide IEC no. FMR/IEC/TB/01/2013).
Verbal informed consent for answering the survey was obtained from individuals who underwent the HH survey in stage 1 sampling. Following the verbal consent, field researchers then contacted the patients over the phone to schedule in-depth interviews. On meeting the patients, written informed consent was first obtained for the in depth interviews after which 82 patients who consented were included in the semi-structured interview. In the case of minors, written consent was obtained from their care-givers (parents/guardians). The consent obtained included participation in the interview, digital audio recording and note keeping, reviewing of patient’s TB treatment-related documents and permission to publish anonymised data in any report, journal, etc.
Thirteen of the 23 patients interviewed (56%) were retreatment patients, of whom only four (31%) were advised drug sensitivity testing (DST). Nine (69%) of the retreatment patients were initiated on first line treatment before being diagnosed and treated as DR-TB. Of the 10 new patients with no past history of TB, only two were advised DST and the remaining eight (80%) were treated with first line anti TB medicines. Preference for Mumbai’s strong and robust public sector for TB treatment was seen among the interviewed patients, with a significant shift from first seeking care from the private sector (n=19, 83%) for initial symptoms, to approaching the public sector (n=16, 70%) for diagnosis and treatment of DR-TB.
Only four patients (17%) were diagnosed with DR-TB using molecular tests like CB NAAT and LPA, facilities for which were available in both, the public and private sectors. Sixteen patients (70%) were diagnosed using only culture based / phenotypic tests. A combination of molecular and phenotypic tests were used for diagnosis in only two patients (9%) and the remaining three (13%) were presumptively diagnosed using only chest x-ray and sputum examination for acid fast bacilli. Due to lack of phenotypic testing facilities in the public sector, where a majority of the patients were diagnosed, it is most likely that the samples were sent to private labs for testing.
Figure 2 depicts the median (mean) durations and interquartile range in days for time taken from onset of symptom to first point of care, first point of care to DR-TB diagnosis and from DR-TB diagnosis to initiation of DR-TB treatment, for the entire cohort and for new and retreatment patients.
The figure depicts the pathway to DR-TB care for patients from the entire cohort, along with new patients and retreatment patients.
After the patients first sought care, the average time taken to diagnose and initiate DR-TB treatment was 87 days (IQR 17-202) for the entire cohort (data not shown in figure). Further analysis was undertaken to see the median difference in pathways of new and retreatment DR-TB patients (Figure 2). The time taken from first care seeking to DR-TB diagnosis (p value = 0.041) and the total pathway duration (p value = 0.016) were significantly shorter for retreatment patients. However, the duration from onset of symptoms to first care seeking was almost similar for the two groups, indicating that patients with a past episode of TB were not seeking care earlier compared to new patients. Patients were further split into those diagnosed with DR-TB at presentation and those diagnosed after a course of first line treatment (Figure 3).
The figure depicts the pathway to DR-TB care for new and retreatment patients for patients diagnosed with DR-TB at presentation (A and C) and patients diagnosed after a course of first line treatment (B and D).
While no significant differences in pathway durations were observed after splitting the patients, due to the small number of patients in each group, new patients initially diagnosed and treated as drug susceptible patients showed the longest median pathway of eight months (Figure 3B). The study was not able to assess if the patients progressed from drug sensitive tuberculosis (DS-TB) to DR-TB or were incorrectly diagnosed with DS-TB. The shortest median pathway of one month was seen in retreatment patients who were diagnosed with DR-TB initially (Figure 3C).
With respect to the entire cohort the median pathways after seeking first access to care was 86 days (IQR 14-202) which is relatively shorter than that reported in a multistate study (128 days, IQR 103-173)6 but nevertheless long. Our study also throws light on patient related delay, seen specifically among retreatment patients who showed a similar time frame in accessing first care (20 days vs 27 days) on developing symptoms that were probably similiar to ttheir first disease episode. This could be due to patient denial or lack of information/counseling received from their TB care providers in the past5. Since it is more likely for a retreatment patient to be resistant at their second episode, DST testing is mandated. However, the failure in undertaking this in over 70% of patients exceeded the proportion (45%) reported in another study conducted in Andhra Pradesh, India7.
The unacceptably long pathways for diagnosis and treatment of DR-TB in Mumbai advocates for stronger implementation of early screening of patients for DR-TB through use of rapid gene-based technologies. Since patients with the least duration were the ones directly diagnosed with DR-TB, this advocates for the use of DR testing at the time of presentation of the patients to reduce their total pathway. This seems to be well on track, with the number of GeneXpert machines available in the city increasing from eight when the study was initiated in 2015, to 19 so far in 2017. There is also a new policy dated 1st Jan, 2018 which mandates all new cases to be tested with GeneXpert at time of presentation. Focus needs to be on people residing in vulnerable settings, contacts of DR-TB cases, immune-compromised patients and those living in compromised housing. Contemporary technologies need to be rapidly made available in the public sector and extended to patients seeking care from the private sector as well.
Raw data in Excel format of the 23 drug resistant TB cases identified in Mumbai and the semi structured interview guide that was used to collect the data from the identified DR-TB patients are available on OSF: http://doi.org/10.17605/OSF.IO/8CTBV8
Data are available under the terms of the Creative Commons Zero "No rights reserved" data waiver (CC0 1.0 Public domain dedication).
The Bill and Melinda Gates Foundation (OPP1091874) through Sambodhi Research & Communications Pvt. Ltd. to NM.
The funders had no role in study analysis, decision to publish, or preparation of manuscript.
The study was supported by the Bill and Melinda Gates Foundation through funds received by Sambodhi Research and Communication Pvt. Ltd. The authors are thankful to the Mumbai District Tuberculosis Control Society for the gracious endorsement for undertaking this study. We also thank all the field researchers from the Foundation for Medical Research (FMR).
Supplementary File 1: Semi structured interview schedule.
Click here to access the data.
Supplementary File 2: Quantitative data sheet.
Views | Downloads | |
---|---|---|
Gates Open Research | - | - |
PubMed Central
Data from PMC are received and updated monthly.
|
- | - |
Is the work clearly and accurately presented and does it cite the current literature?
Yes
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.
Is the work clearly and accurately presented and does it cite the current literature?
Yes
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?
Partly
Are all the source data underlying the results available to ensure full reproducibility?
Partly
Are the conclusions drawn adequately supported by the results?
Yes
References
1. Sreeramareddy CT, Qin ZZ, Satyanarayana S, Subbaraman R, et al.: Delays in diagnosis and treatment of pulmonary tuberculosis in India: a systematic review.Int J Tuberc Lung Dis. 2014; 18 (3): 255-266 PubMed Abstract | Publisher Full TextCompeting Interests: No competing interests were disclosed.
Reviewer Expertise: Tuberculosis, health care seeking, mixed methods research
Alongside their report, reviewers assign a status to the article:
Invited Reviewers | ||
---|---|---|
1 | 2 | |
Version 2 (revision) 10 May 18 |
read | read |
Version 1 19 Feb 18 |
read | read |
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. Consider the following examples, but note that this is not an exhaustive list:
Sign up for content alerts and receive a weekly or monthly email with all newly published articles
Register with Gates Open Research
Already registered? Sign in
If you are a previous or current Gates grant holder, sign up for information about developments, publishing and publications from Gates Open Research.
We'll keep you updated on any major new updates to Gates Open Research
The email address should be the one you originally registered with F1000.
You registered with F1000 via Google, so we cannot reset your password.
To sign in, please click here.
If you still need help with your Google account password, please click here.
You registered with F1000 via Facebook, so we cannot reset your password.
To sign in, please click here.
If you still need help with your Facebook account password, please click here.
If your email address is registered with us, we will email you instructions to reset your password.
If you think you should have received this email but it has not arrived, please check your spam filters and/or contact for further assistance.
Comments on this article Comments (0)