Dear Editor,
Experimental animal work indicates that neutrophils play a key role in the immune response to mycobacteria[1,2]. They appear protective against early infection[3], but in established disease neutrophilia associates with pathology[1,4]. In humans, higher neutrophil counts at tuberculosis diagnosis predict slower sputum conversion to negative during therapy[5,6], but the overall prognostic significance of neutrophilia in human tuberculosis remains elusive. We therefore aimed to analyse this phenomenon in a study powered to detect an independent relationship with mortality.
Tuberculosis patients were identified by database/case-note review at Newham University Hospital Trust (NUHT) and King’s College Hospital (KCH), London, UK. All patients diagnosed between 1999 and 2006 were eligible for inclusion in analysis of neutrophilia at baseline; those with a recorded outcome of successfully completing treatment or death were included in analysis of determinants of mortality. Healthy contacts of tuberculosis cases were recruited from the same hospitals.
Data were extracted on patient age, sex, ethnicity, co-morbidity, use of immunosuppressive medication, HIV status and site of disease. Laboratory data were collected from samples taken on the date of tuberculosis diagnosis: serum sodium, bilirubin and albumin concentrations, peripheral blood haemoglobin concentration, peripheral blood neutrophil, monocyte, lymphocyte and platelet counts. Blood culture results were recorded where performed. Protocols were approved by the Barking and Havering NHS Research Ethics Committee, UK (REC 08/H0702/25) and North East London Research Ethics Committee, UK (REC P/02/146).
We calculated that 584 patients (34 dying and 550 survivors) would be required to detect a 3-fold difference in mortality in the presence of neutrophilia with 80% power (5% significance level), assuming a 15% prevalence of neutrophilia and a death:survival ratio of 1:16 (parameters derived from preliminary analysis). We aimed to include twice this number to allow for missing data.
Comparisons of proportions utilised chi-square tests. Comparisons of non-Gaussian continuous data (neutrophil counts, age) utilised Mann-Whitney tests. To investigate demographic or clinical associations with neutrophilia in tuberculosis patients, neutrophil counts were treated as a categorical dependent variable for binary logistic regression: ≥7.5×109/L or <7.5×109/L. Analysis of predictors of mortality used death/survival as the binary dependent variable. Multivariate regression was performed using all significant (p<0.05) predictors from univariate analysis. Age was divided into strata pre-analysis. Laboratory parameters were also assigned pre-analysis into categorical predictors since relationships were not anticipated to be linear and both high and low values are usually pathological. A distinction was made between pathological neutropenia (<1 ×109/L) and mild, usually benign ethnic, neutropenia. Predictors with >25% missing values (HIV status and co-morbidity) were assigned a separate group of ‘unknown’ to enable inclusion of patients with missing data in multivariate analyses. Bootstrapping analysis used simple (non-stratified) sample selection. Analyses were performed using SPSS Versions 18-21.
1236 tuberculosis patients were identified; 855 had recorded neutrophil counts and data for all demographic variables except HIV status and co-morbidity (see above). There was no difference in age (p=0.29), sex distribution (p=0.80), ethnic distribution (p=0.07) or neutrophil count (p=0.55) between included patients and excluded patients for whom this information was available. 49 patients were transferred or lost to follow-up and 88 patients lacked data for one or more laboratory parameters resulting in 718 patients entering case fatality analysis.
Pulmonary tuberculosis was the commonest disease site (49.4%), and HIV infection was known to be present in 13.5% of the 855 patients. 214 contacts were also analysed. Cases and contacts did not differ in sex distribution (57.3% vs. 50.5% male respectively, p=0.07) but did differ in age (median age 33 vs. 30 years respectively, p=0.002) and ethnic distribution (11.6% vs. 16.4% respectively were white, 19.3% vs. 33.6% South Asian, 59.8% vs. 40.7% black and 9.4% vs. 9.3% other ethnic origin; p<0.001).
Neutrophilia (peripheral blood neutrophil count ≥7.5 ×109/L) was commoner in patients with active tuberculosis disease than in healthy contacts (158/855 (18.5%) vs. 8/214 (3.7%)). The adjusted Odds Ratio[aOR] for neutrophilia among cases vs. contacts, controlling for age and ethnicity, was 6.13 (95% Confidence Interval[CI] 2.94-12.82), p<0.001). Median neutrophil count was also higher in cases than contacts (4.65 (Interquartile range[IQR] 3.17–6.75) vs. 3.66 (IQR 2.78–4.78) ×109/L, p<0.0001).
Analysis of 297 blood cultures performed on tuberculosis patients revealed three pathogenic bacteria other than M.tuberculosis (one methicillin-resistant Staphylococcus aureus, one Proteus vulgaris and one unidentified coliform). Only the patient with Proteus had concomitant neutrophilia.
We next sought to identify any associations with neutrophilia at tuberculosis diagnosis (Table 1). In multivariate analysis, white ethnicity increased odds of neutrophilia compared to black ethnicity (aOR 1.75, 95% CI 1.03–3.03, p=0.036). Pulmonary disease was associated with increased odds of neutrophilia compared to peripheral lymph node tuberculosis (aOR 2.56, 95% CI 1.25–5.26, p=0.011). HIV infection reduced odds of neutrophilia compared to HIV-uninfected (aOR 0.50, 95% CI 0.26–0.97, p=0.039); however, this result is confounded by pathological neutropenia (5 of 13 patients (38.5%) with neutrophil count <1 ×109/L were HIV-infected, and removing all pathologically neutropenic patients from analysis negates the association between HIV positivity and absence of neutrophilia).
Table 1. Associations with neutrophilia and mortality in tuberculosis patients.
| Analysis of Neutrophilia (n = 855) | Analysis of mortality (n = 718) | |||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Univariate analysis | Multivariate analysis | Univariate analysis | Multivariate analysis | |||||||||||
| Number (%) with neutrophilia | OR | p-value | OR | 95% CI | p-value | Number (%) Dead | OR | p-value | OR | 95% CI | p-value | |||
| Sex | Male (n = 490) | 99 (20.2%) | 1 | Male (n = 408) | 29 (7.1%%) | 1 | ||||||||
| Female (n = 365) | 59 (16.2%%) | 0.76 | 0.133 | Female (n = 310) | 13 (4.2%%) | 0.57 | 0.103 | |||||||
| Age (years) | < 20 (n = 102) | 16 (15.7%) | 0.95 | 0.869 | 0.98 | 0.53 –1.80 | 0.951 | < 20 (n = 82) | 0 (0%%) | N/A | N/A | |||
| 20 –39 (n = 471) | 77 (16.3%%) | 1 | 1 | 20 –39 (n = 390) | 6 (1.5%%) | 1 | 1 | |||||||
| 40 – 59 (n = 196) | 40 (20.4%%) | 1.31 | 0.210 | 1.28 | 0.83 –1.97 | 0.274 | 40 – 59 (n = 165) | 26 (12.7%%) | 9.33 | < 0.001 | 8.73 | 2.88 –26.44 | < 0.001 | |
| ≥ 60 (n = 86) | 25 (29.1%%) | 2.10 | 0.006 | 1.75 | 0.99 –3.10 | 0.055 | ≥ 60 (n = 81) | 15 (18.5%%) | 14.55 | < 0.001 | 8.68 | 2.30 –32.71 | 0.001 | |
| Ethnicity | White (n = 99) | 30 (30.3%%) | 1 | 1 | White (n = 88) | 13 (14.8%%) | 1 | 1 | ||||||
| South Asian a (n = 165) | 33 (20.0%%) | 0.58 | 0.059 | 0.71 | 0.39 –1.30 | 0.272 | South Asian a (n = 120) | 6 (5.0%%) | 0.30 | 0.021 | 0.57 | 0.16 –2.05 | 0.385 | |
| Black b(n = 511) | 81 (15.9%%) | 0.43 | 0.001 | 0.57 | 0.33 –0.97 | 0.036 | Black b(n = 439) | 20 (4.6%%) | 0.28 | 0.001 | 0.52 | 0.18 –1.52 | 0.233 | |
| Other (n = 80) | 14 (17.5%%) | 0.49 | 0.050 | 0.59 | 0.28 –1.23 | 0.157 | Other (n = 71) | 3 (4.2%%) | 0.26 | 0.039 | 0.45 | 0.09 –2.34 | 0.344 | |
| Site of disease | Pulmonary (n = 422) | 92 (21.8%%) | 1 | 1 | Pulmonary (n = 362) | 27 (7.5%%) | 1 | |||||||
| Peripheral LN only (n = 99) | 9 (9.1%%) | 0.36 | 0.005 | 0.39 | 0.19 –0.80 | 0.011 | Peripheral LN only (n = 84) | 2 (2.4%%) | 0.30 | 0.108 | ||||
| Central Nervous System (n = 39) | 8 (20.5%%) | 0.93 | 0.852 | 0.86 | 0.38 –1.98 | 0.863 | Central Nervous System (n = 31) | 2 (6.5%%) | 0.86 | 0.837 | ||||
| Miliary (n = 23) | 5 (21.7%%) | 1.00 | 0.994 | 1.04 | 0.36 –2.96 | 0.948 | Miliary (n = 18) | 1 (5.6%%) | 0.73 | 0.764 | ||||
| Other extra-pulmonary (n = 272) | 44 (16.2%%) | 0.69 | 0.069 | 0.69 | 0.46 –1.03 | 0.071 | Other extra-pulmonary (n = 223) | 10 (4.5%%) | 0.58 | 0.155 | ||||
| Immuno-suppressives c | No (n = 804) | 148 (18.4%%) | 1 | No(n = 679) | 41 (6.0%%) | 1 | ||||||||
| Yes (n = 51) | 10 (19.6%%) | 1.08 | 0.831 | Yes (n = 39) | 1 (2.6%%) | 0.41 | 0.384 | |||||||
| Co-morbidity d | No (n = 564) | 103 (18.3%) | 1 | No(n = 468) | 20 (4.3%) | 1 | 1 | |||||||
| Yes (n = 53) | 11 (20.8%) | 1.17 | 0.655 | Yes (n = 42) | 7 (16.7%) | 4.48 | 0.002 | 5.94 | 1.65 –21.37 | 0.006 | ||||
| Unknown (n = 238) | 44 (18.5%) | 1.02 | 0.940 | Unknown (n = 208) | 15 (7.2%) | 1.74 | 0.116 | 1.18 | 0.45 –3.10 | 0.732 | ||||
| HIV status | Uninfected (n = 280) | 58 (20.7%) | 1 | 1 | Uninfected (n = 243) | 9 (3.7%) | 1 | 1 | ||||||
| Infected (n = 115) | 13 (11.3%) | 0.49 | 0.029 | 0.50 | 0.26 –0.97 | 0.039 | Infected (n = 105) | 11 (10.5%) | 3.04 | 0.017 | 1.46 | 0.39 –5.42 | 0.575 | |
| Unknown (n = 460) | 87 (18.9%) | 0.89 | 0.549 | 0.76 | 0.50 –1.14 | 0.178 | Unknown (n = 370) | 22 (5.9%) | 1.64 | 0.219 | 1.17 | 0.37 –3.76 | 0.788 | |
| Serum sodium | < 130 mmol/L (n = 60) | 10 (16.7%) | 4.94 | < 0.001 | 1.01 | 0.37 –2.74 | 0.982 | |||||||
| 130 –140 mmol/L (n = 591) | 23 (3.9%) | 1 | 1 | |||||||||||
| > 140 mmol/L (n = 67) | 9 (13.4%) | 3.83 | 0.001 | 4.59 | 1.18 –17.86 | 0.028 | ||||||||
| Serum bilirubin | ≤ 17 μmol/L (n = 614) | 29 (4.7%) | 1 | 1 | ||||||||||
| > 17 mmol/L (n = 104) | 13 (12.5%) | 2.88 | 0.003 | 1.52 | 0.57 –4.05 | 0.398 | ||||||||
| Serum albumin | ≥ 30 g/L (n = 584) | 14 (2.4%) | 1 | 1 | ||||||||||
| < 30 g/L (n = 134) | 28 (20.9%) | 10.76 | < 0.001 | 4.43 | 1.79 –11.00 | 0.001 | ||||||||
| Peripheral blood haemoglobin | ≥ 11.5 g/dL (n = 346) | 9 (2.6%) | 1 | |||||||||||
| < 11.5 g/dL (n = 372) | 33 (8.9%) | 3.65 | 0.001 | 2.34 | 0.81 – 6.76 | 0.116 | ||||||||
| Peripheral blood platelet count | <150 × 109/L (n = 52) | 16 (30.8%) | 10.43 | < 0.001 | 3.75 | 1.25 –11.22 | 0.018 | |||||||
| 150 - 400 × 109/L (n = 465) | 19 (4.1%) | 1 | 1 | |||||||||||
| > 400 × 109/L (n = 201) | 7 (3.5%) | 0.85 | 0.712 | 0.47 | 0.15 –1.47 | 0.192 | ||||||||
| Peripheral blood neutrophil count | < 1 × 109/L (n = 13) | 3 (23.1%%) | 7.11 | 0.005 | 0.73 | 0.05 –9.80 | 0.813 | |||||||
| 1 - 1.99 × 109 / L (n = 50) | 2 (4.0%%) | 0.99 | 0.987 | 0.54 | 0.08 –3.71 | 0.528 | ||||||||
| 2 -7.49 × 109/L (n = 519) | 21 (4.0%%) | 1 | 1 | |||||||||||
| ≥ 7.50 × 109 / L (n = 136) | 16 (11.8%%) | 3.16 | 0.001 | 2.93 | 1.17 –7.34 | 0.022 | ||||||||
| Peripheral blood lymphocyte count | < 1 × 109 / L (n = 252) | 33 (13.1%%) | 7.35 | < 0.001 | 3.24 | 1.24 –8.44 | 0.016 | |||||||
| 1 -4 × 109 / L (n = 448) | 9 (2.0%%) | 1 | 1 | |||||||||||
| > 4 × 109 / L (n = 18) | 0 (0%%) | N/A | N/A | |||||||||||
| Peripheral blood monocyte count | < 0.2 × 109/ L (n = 38) | 11 (28.9%%) | 7.91 | < 0.001 | 1.51 | 0.43 –5.35 | 0.524 | |||||||
| 0.2 -0.8 × 109 / L (n = 490) | 24 (4.9%%) | 1 | 1 | |||||||||||
| > 0.8 × 109 / L (n = 190) | 7(3.7%%) | 0.74 | 0.497 | 0.92 | 0.31 –2.69 | 0.876 | ||||||||
Includes Indian, Sri Lankan, Pakistani and Bangladeshi.
Includes Black African, Black Caribbean and Black Other.
Corticosteroids, azathioprine or cyclosporin.
Identified co-morbidities: renal failure, hepatic failure, previous ischaemic cardiovascular events, diabetes mellitus, hypertension, sickle cell disease, respiratory failure, arthritis (unspecified), inflammatory bowel disease, celiac disease, ankylosing spondylitis.
OR = Odds ratio. CI = confidence interval. LN = lymph node. HIV = human immunodeficiency virus.
Table 1 also summarises results from logistic regression analysis on predictors of mortality (n=718). Neutrophilia was present in 16/42 (38.1%) patients who died and 120/676 (17.8%) survivors and was an independent risk for case fatality in multivariate analysis (aOR 2.93, 95% CI 1.17–7.34, p=0.022). Bootstrapping analysis (1000 samples) confirmed the result’s robustness (aOR 2.93, 95% CI 1.16–12.03, p=0.018). Further laboratory parameters predicting fatality were hypernatraemia, hypoalbuminaemia, thrombocytopenia and lymphopenia. Increased age and the presence of co-morbidity other than HIV were also associated with increased risk of death, but receiving immunosuppressive medication was not.
Our study yielded some important new findings. A modest neutrophilic response was common in tuberculosis: even survivors with active tuberculosis had higher median neutrophil counts than healthy contacts. Others have reported that higher blood neutrophil counts correlate with sputum M.tuberculosis Polymerase Chain Reaction positivity and, especially, smear positivity[7], while separate studies discovered higher neutrophil counts associating with slower conversion of sputum culture to negative[5,6]. Together with the higher prevalence of neutrophilia in patients who die (reported here), these results suggest that, broadly speaking, the neutrophil count in tuberculosis positively correlates with bacillary load.
It is therefore important to know which other factors associate with neutrophilia in human tuberculosis. We found no convincing evidence that non-tuberculous bacteremia explained this phenomenon, since only one out of 158 instances of neutrophilia was associated with a pathogenic non-mycobacterial species in blood culture. Lower risk of neutrophilia with isolated peripheral lymph node disease probably reflects lower mycobacterial load and less systemic inflammation. The finding that white ethnicity independently predicts neutrophilia may be biologically important in tuberculosis and help to explain the previous finding that European ethnic origin is a risk factor for death independently of age[8]. Indeed, the lowest case fatality in our study was seen with neutrophil counts in the range 1–1.99 ×109/L, likely to largely reflect benign ethnic neutropenia. The apparent effect of HIV in reducing risk of neutrophilia is explained by pathological neutropenia, a well-described complication of HIV [9]. Indeed, pathological neutropenia (<1 ×109/L) was associated with higher case fatality as compared to normal range neutrophil count. In addition to the association with HIV infection, this can be seen in the context of severe, disseminated tuberculosis [10].
Our study has some limitations. 381 potentially eligible patients were excluded, but their demographics and neutrophil counts were similar to included patients. Co-morbidity and HIV status were poorly documented necessitating an ‘unknown’ coding category. Tuberculosis cases and contacts were not formally matched; in particular they differed in age and ethnic distribution, but the odds of neutrophilia were much higher in the former even after adjustment for these factors.
In summary, we have demonstrated that neutrophilia in tuberculosis independently associates with increased risk of mortality. Interestingly, abrogating the immunopathological neutrophil response in some animal models improves outcome in acute infection [4]. Similar strategies might therefore have therapeutic application in humans with severe tuberculosis.
Acknowledgements
Funding: Department of Environmental Health, London Borough of Newham, London, UK; Wellcome Trust Grant WT087754.
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