| Literature DB >> 22116091 |
Eric Walter Pefura Yone1, André Pascal Kengne, Christopher Kuaban.
Abstract
Objectives High rates of antituberculosis treatment discontinuation have been reported in some areas of Africa. The aim of this study was to determine the rate, time to and determinants of antituberculosis treatment default in Yaounde. Design This was a retrospective cohort study based on hospital registers. Tuberculosis treatment default or antituberculosis treatment discontinuation was defined as any interruption of treatment for at least 2 months following treatment initiation. Sociodemographic and clinical predictors of treatment discontinuation were investigated with the use of Cox regressions models. Setting This study was carried out in the tuberculosis diagnosis and treatment centre at Yaounde Jamot Hospital, which serves as a referral centre for tuberculosis and respiratory diseases for the capital city of Cameroon (Yaounde) and surrounding areas. Participants All (1688) patients started on antituberculosis treatment at the centre between January and December 2009 were enrolled. Outcome measures were antituberculosis treatment default and time to treatment default. Results Of the 1688 included patients, 337 (20%) defaulted from treatment, 86 (5.1%) died, treatment failed in 6 (0.4%) and 104 (6.2%) were transferred. Therefore, treatment was successfully completed in 1154 (68.4%) patients. Median duration to treatment discontinuation was 90 days (IQR 30-150), and 62% of treatment discontinuation occurred during the continuation phase. Hospitalisation during the intensive phase (adjusted HR 0.69; 95% CI 0.54 to 0.89) and non-consenting for HIV screening (1.65; 1.24 to 2.21) were the main determinants of defaulting from treatment in multivariable analysis. Conclusions The default incidence rate is relatively high in this centre and treatment discontinuation occurs frequently during the continuation phase of treatment. Action is needed to improve adherence to treatment when received on an ambulatory basis, to clarify the association between HIV testing and antituberculosis treatment default, and to identify other potential determinants of treatment discontinuation in this setting.Entities:
Year: 2011 PMID: 22116091 PMCID: PMC3225586 DOI: 10.1136/bmjopen-2011-000289
Source DB: PubMed Journal: BMJ Open ISSN: 2044-6055 Impact factor: 2.692
Characteristics of patients with tuberculosis according to treatment outcome at Yaounde Jamot Hospital in 2009
| Characteristics | Categories | Total | Outcomes of tuberculosis treatment | |||||
| Success | Failure | Death | Defaulted | Transferred | p Value | |||
| N (%) | 1688 | 1155 (68.4) | 6 (0.4) | 86 (5.1) | 337 (20.0) | 104 (6.2) | ||
| Age, years | ≤15 | 39 (2.3) | 33 (84.6) | 0 (0) | 0 (0) | 5 (12.8) | 1 (2.6) | <0.031 |
| >15–59 | 1554 (92.1) | 1067 (68.7) | 5 (0.3) | 75 (4.8) | 310 (19.9) | 97 (6.2) | ||
| ≥60 | 95 (5.6) | 55 (57.9) | 1 (1.1) | 11 (11.6) | 22 (23.2) | 6 (6.3) | ||
| Median (IQR) | 32 (25–42) | 32 (24–42) | 35 (26–48) | 45 (32–54) | 32 (25–42) | 35.5 (24–42) | <0.001 | |
| Men | 954 (56.5) | 650 (68.1) | 4 (0.4) | 50 (5.2) | 195 (20.4) | 55 (5.8) | 0.882 | |
| Residence | Urban | 1423/1662 (85.6) | 995 (69.9) | 5 (0.4) | 72 (5.1) | 283 (19.9) | 68 (4.8) | <0.001 |
| Rural | 239/1662 (14.4) | 144 (60.3) | 1 (0.4) | 13 (5.4) | 47 (19.7) | 34 (14.2) | ||
| Place of screening | This centre | 1625 (96.3) | 1115 (68.6) | 6 (0.4) | 84 (5.2) | 319 (19.6) | 101 (6.2) | 0.269 |
| Elsewhere | 63 (3.7) | 40 (63.5) | 0 (0) | 2 (3.2) | 18 (28.6) | 3 (4.8) | ||
| Setting of intensive phase of treatment | Hospitalisation | 1098 (65.0) | 772 (70.3) | 3 (0.3) | 69 (6.3) | 179 (16.3) | 75 (6.8) | <0.001 |
| Outpatient | 590 (35.0) | 383 (64.9) | 3 (0.5) | 17 (2.9) | 158 (26.8) | 29 (4.9) | ||
| Clinical forms | PTB+ | 1231 (72.9) | 860 (69.9) | 6 (0.5) | 16 (4.5) | 239 (19.4) | 70 (5.7) | 0.012 |
| PTB− | 168 (10.0) | 95 (56.5) | 0 (0) | 16 (9.5) | 45 (26.8) | 12 (7.1) | ||
| ETB | 289 (17.1) | 200 (69.2) | 0 (0) | 14 (4.8) | 53 (18.3) | 22 (7.6) | ||
| Type of patient | New cases | 1543 (91.4) | 1059 (68.6) | 5 (0.3) | 81 (5.2) | 299 (19.4) | 99 (6.4) | 0.20 |
| Retreatment cases | 145 (8.6) | 96 (66.2) | 1 (0.7) | 5 (3.4) | 38 (26.2) | 5 (3.4) | ||
| HIV serology | Not done | 241 (14.3) | 122 (50.6) | 2 (0.8) | 20 (8.3) | 72 (29.9) | 25 (10.4) | <0.001 |
| Negative | 942 (55.8) | 703 (74.6) | 4 (0.4) | 17 (1.8) | 166 (18) | 50 (5.4) | ||
| Positive | 497/1419 (35) | 330 (65.3) | 0 (0) | 49 (9.7) | 97 (19.2) | 29 (5.7) | ||
| Sputum smear conversion | Yes | 1378/1471 (93.7) | 1072 (77.8) | 0 (0) | 13 (0.9) | 229 (16.6) | 64 (4.6) | <0.001 |
| No | 93/1471 (6.3) | 77 (82.8) | 4 (4.3) | 0 (0) | 10 (10.8) | 2 (2.2) | ||
Data are number (%) unless otherwise indicated.
Treatment success indicates cured+completed.
At the end of the intensive phase (applicable only to patients with smear-positive tuberculosis).
ETB, extra-pulmonary tuberculosis; PTB+, smear positive pulmonary tuberculosis; PTB−, smear negative pulmonary tuberculosis.
Figure 1Time to treatment discontinuation.
Figure 2Duration of follow-up for treatment discontinuation (days).
HRs and 95% CIs for predictors of antituberculosis treatment discontinuation from Cox regression analysis
| Characteristics | Basic models | Final models | ||
| HR (95% CI) | p Value | HR (95% CI) | p Value | |
| Age (per year) | 1.01 (1.00 to 1.01) | 0.121 | 1.01 (1.00 to 1.01) | 0.133 |
| Sex (women vs men) | 0.96 (0.77 to 1.20) | 0.723 | 0.99 (0.79 to 1.23) | 0.922 |
| Hospitalised intensive phase | 0.58 (0.46 to 0.72) | <0.0001 | 0.69 (0.54 to 0.89) | 0.004 |
| Residence (urban vs rural) | 0.92 (0.67 to 1.26) | 0.596 | – | – |
| Clinical form of tuberculosis | ||||
| Positive smear (reference) | 1.00 (reference) | 1.00 (reference) | ||
| Negative smear | 1.59 (1.15 to 2.21) | 0.005 | 1.25 (0.89 to 1.76) | 0.192 |
| Extra-pulmonary | 0.99 (0.73 to 1.34) | 0.948 | 0.96 (0.71 to 1.30) | 0.780 |
| Unknown status for HIV | 1.28 (1.17 to 1.41) | <0.0001 | 1.65 (1.24 to 2.21) | 0.0007 |
Basic models are adjusted for age and sex, and final models are further adjusted for all significant predictors in the basic models.
All Cox models are stratified by type of patient (ie, new patient, retreatment) to account for differences in the duration of treatment.