Human immunodeficiency virus (HIV)–associated cryptococcal meningitis (CM) is the commonest cause of adult meningitis in much of Africa [1–4]. Despite antifungal treatment, acute mortality in the developing world remains between 24% and 43% [5–7], and CM accounts for 10%–20% of all HIV-related deaths in sub-Saharan Africa [8]. The median time to death following hospital admission with CM is 10–13 days [6]. To develop evidence-based interventions, it is essential to determine the key predictors of mortality. Using data from a cohort of 501 patients with CM from Thailand, South Africa, Malawi, and Uganda, we describe the presenting clinical features and outcomes of patients with HIV-associated CM, and report the results of a predictive model used to identify the clinical and microbiological factors at baseline independently associated with mortality. We provide an analysis of factors associated with altered mental status, cerebrospinal fluid (CSF) fungal burden, CSF opening pressure (OP) at presentation, rate of clearance of infection, and immune reconstitution inflammatory syndrome (IRIS). METHODS The cohort comprised patients from 9 trials conducted from 2002 to 2010 at 5 sites (Table 1) in Thailand, South Africa, Malawi, and Uganda. The trials have been reported elsewhere, and represent all trials of HIV-associated CM published (at the time of analysis) using early fungicidal activity (EFA) as the primary outcome [5, 9–16]. A previous analysis of 262 patients explored the correlation between rate of clearance of infection and survival [17]. Combining the data from the constituent trials into a combined cohort was done to obtain the power needed to reliably determine the predictors of mortality in patients with HIV-associated CM. All trials were sponsored by St George's University of London and approved by the St George's Research Ethics Committee and local ethics committees. Table 1. Component Studies Contributing to the Combined Cohort Author and Type of Studya Site and Year No. of Subjects Induction Treatmentb ART Available EFA, log10 CFU/mL/d, Mean (SD) Brouwer et al [9] RCT Thailand 2002 64 AmB 0.7 mg/kg/d (n = 16) No −0.31 (0.18) AmB 0.7 mg/kg/d + 5-FC 100 mg/kg/d (n = 16) −0.54 (0.19) AmB 0.7 mg/kg/d + Fluc 400 mg/d (n = 16) −0.39 (0.15) AmB 0.7 mg/kg + 5-FC 100 mg/kg + Fluc 400 mg/d (n = 16) (All for 14 d) −0.38 (0.13) Bicanic et al [10] Cohort study South Africa 2005 54 AmB 1 mg/kg/d for 7 d then Fluc 400 mg/d (n = 49) Yes −0.48 (0.28) Fluc 400 mg/d for 14 d (n = 5) −0.02 (0.05) Bicanic et al [5] RCT South Africa 2005–2006 64 AmB 0.7 mg/kg/d + 5-FC 100 mg/kg/d (n = 30) Yes −0.45 (0.16) AmB 1 mg/kg/d + 5-FC 100 mg/kg/d (n = 34) (Both for 14 d) −0.56 (0.24) Longley et al [11] Cohort study Uganda 2005–2007 60 Fluc 800 mg/d (n = 30) Yes −0.07 (0.17) Fluc 1200 mg/d (n = 30) (Both for 14 d) −0.18 (0.11) Nussbaum et al [12] RCT Malawi 2008 41 Fluc 1200 mg/d (n = 20) Yes −0.11 (0.10) Fluc 1200 mg/d + 5-FC 100 mg/kg/d (n = 21) (Both for 14 d) −0.28 (0.17) Loyse et al [13] RCT South Africa 2006–2008 80 AmB 1 mg/kg/d + 5-FC 100 mg/kg/d (n = 21) Yes −0.41 (0.22) AmB 1 mg/kg/d + Fluc 800 mg/d (n = 22) −0.38 (0.18) AmB 1 mg/kg/d + Fluc 1200 mg/d (n = 24) −0.41 (0.35) AmB 1 mg/kg/d + Vori 600 mg/d (n = 13) (All for 14 d) −0.44 (0.20) Muzoora et al [14] Cohort study Uganda 2008–2009 30 AmB 1 mg/kg/d for 5 d + Fluc 1200 mg/d for 14 d (n = 30) Yes −0.3 (0.11) Jackson et al [15] RCT Malawi 2009–2010 40 AmB 1 mg/kg/d for 7 d + Fluc 1200 mg/d for 14 d (n = 20) Yes −0.39 (0.20) AmB 1 mg/kg/d for 7 d + Fluc 1200 mg/d and 5-FC 100 mg/kg/d for 14 d (n = 20) −0.49 (0.15) Jarvis et al [16] RCT South Africa 2007–2010 90 AmB 1 mg/kg/d + 5-FC 100 mg/kg/d (n = 31) Yes −0.49 (0.15) AmB 1 mg/kg/d + 5-FC 100 mg/kg/d + IFN-γ 100 µg days 1 & 3 (n = 29) −0.64 (0.27) AmB 1 mg/kg/d + 5-FC 100 mg/kg/d + IFN-γ 100 µg days 1, 3, 5, 8, 10, & 12 (n = 30) (AmB + 5-FC for 14 d in all arms) −0.64 (0.22) Abbreviations: 5-FC, 5-fluorocytosine; AmB, amphotericin B; ART, antiretroviral therapy; CFU, colony-forming units; EFA, early fungicidal activity; Fluc, fluconazole; IFN, interferon; RCT, randomized controlled trial; SD, standard deviation; Vori, voriconazole. a The 9 studies were conducted in 5 sites: Sappasitprasong Hospital, Ubon Ratchathani, Thailand; GF Jooste Hospital, Cape Town, and Edendale Hospital, Pietermaritzburg, South Africa; Kamuzu Central Hospital/University of North Carolina Project, Lilongwe, Malawi; and Mbarara University Hospital, Uganda. Exclusion criteria at all clinical trials were an alanine aminotransferase level >5 times the upper limit of normal (>200 IU/mL), neutrophil count 30 cm) or symptoms of raised intracranial pressure had more frequent lumbar punctures [18]. CSF cell count, protein, and glucose levels were determined. CSF interferon gamma (IFN-γ), tumor necrosis factor alpha (TNF-α), and interleukin 6 (IL-6) concentrations were measured in patients from the Thai and South African sites using the Luminex multianalyte platform and Bio-Rad cytokine kits [19]. Cryptococcal clearance was calculated as the decrease in log colony-forming units (CFU) per milliliter of CSF per day derived from the slope of the linear regression of log CFU per milliliter against time for each patient [9]. Baseline blood tests included hematology, renal and liver function, CD4 cell counts, and, where available, plasma HIV load. The primary outcome in all studies was rate of decrease in CSF cryptococcal CFU (ie, EFA). Secondary outcomes included mortality at 2 and 10 weeks. Cryptococcal meningitis IRIS (CM-IRIS) was diagnosed according to uniform criteria [20]. In patients who died, the presumed cause of death was ascertained by 2 study clinicians. Statistical Analysis Data were analyzed using Stata software, version 11 (StataCorp). Variables were compared using Kruskal-Wallis, χ2, χ2 for trend, Fisher exact, or t tests. Relationships between continuous variables were examined using the Pearson correlation coefficient or Spearman log-rank test. Multivariable logistic regression models were constructed using stepwise regression with the primary objective of determining the clinical and microbiological factors at baseline associated independently with all-cause mortality (as measured at 2 and 10 weeks). A predictive modeling strategy was used in which variables were selected for model inclusion based upon (1) a priori knowledge from previous studies (CD4 cell count), and (2) association with outcome in univariable analysis. Variables associated with mortality in univariable analysis (P ≤ .1) were included in the first fit of the multivariable model and retained, based on likelihood ratio testing, if they significantly improved model fit, to obtain the most parsimonious model identifying predictors of mortality. Clustering by individual study was accounted for using a hierarchical mixed effects model including a random-effects term for “study.” An a priori decision was made to adjust the multivariable model for amphotericin (AmB) vs fluconazole-based treatment as a potential confounder in the relationship between baseline factors and outcomes. Exploring the effect of treatment on outcome, after adjusting for other predictors, was a secondary objective. Patients with missing outcome data were censored from the main analysis, with sensitivity analyses performed assuming that all patients lost were either dead or alive. Further models were constructed to examine the baseline factors associated with altered mental status, baseline fungal burdens, and CSF opening pressure; to examine the impact of ART timing and IRIS on longer-term outcomes; and to describe the relationship between EFA and outcome. EFA was modeled both as a single linear term for each patient as previously described [17] and as a time-updated variable in a Cox regression. In the group with 1 year of follow-up data, Kaplan-Meier survival curves were compared using the Mantel-Haenszel log-rank test. RESULTS Baseline Characteristics and Outcome After screening 896 patients, 523 met eligibility criteria for inclusion in the clinical trials, consented to participation, and were included. Of these, we studied the 501 ART-naive patients with a first episode of CM (Tables 1 and 2). The median age was 34 years, and 52% were male. All had confirmed HIV infection; 76% were known to be HIV positive at time of presentation, diagnosed a median of 152 days (interquartile range [IQR], 44–745 days) earlier; the remainder tested HIV positive at study enrollment. Male patients presented with a longer median reported duration of symptoms than female patients (14 vs 10 days; P = .004). The median CD4 count was 23 cells/µL. Amphotericin B deoxycholate ([AmB] 0.7–1 mg/kg/day) induction treatment was used in 80% of patients, and 20% received fluconazole-based induction (median, 1200 mg/day) without AmB. All-cause mortality was 17% at 2 weeks and 34% at 10 weeks (Tables 3 and 4). Of patients in care at 2 weeks (n = 410), 244 were started on ART a median of 30 days (IQR, 26–42 days) after starting antifungal therapy. Nine patients were lost to follow-up at 2 weeks, and 17 at 10 weeks. Table 2. Baseline Characteristics of the Cohort Characteristic Variable No. % (No.) or Median (IQR) Demographics Age, y 499 34 (29–39) Sex, male 501 52% (260) History Concurrent tuberculosis 419 25% (123) Duration of symptoms, d 458 14 (7–21) Symptoms Headache 496 99% (489) Febrile symptoms 497 57% (280) Visual symptoms 493 51% (250) Hearing loss 415 14% (60) Seizures 496 19% (94) Nausea/vomiting 494 54% (266) Cough 494 35% (173) Signs Fever, >37.5°C 479 23% (112) Tachycardia, >100 bpm 491 19% (91) Hypotension, 20 bpm 463 19% (89) Altered mental status 499 25% (123) Meningism 492 75% (369) Papilledema 311 12% (36) Decreased visual acuity, 25 cm CSF 450 51% (230) Raised OP >30 cm CSF 450 38% (173) CSF white cell count, ×106/L 461 15 (1–57) CSF protein, g/dL 392 0.7 (0.4–1.3) CSF glucose, mg/dL 374 39.6 (25.2–50.5) CSF CRAG, titera 247 1:1024 (1:512–4096) QCC, log10 CFU/mLa 496 5.30 (4.5–5.9) CD4, cells/µL 456 24 (10–50) Log10 VL, copies/mL 368 5.15 (4.7–5.5) Outcomes 2-week mortality 492 17% (82) 10-week mortality 484 34% (163) Time admission to death, d 161 13 (5–310) Abbreviations: CFU, colony-forming units; CRAG, cryptococcal antigen; CSF, cerebrospinal fluid; IQR, interquartile range; OP, opening pressure; QCC, quantitative cryptococcal culture; VL, HIV load. a See Supplementary Figure 1 for a description of the relationship between CSF CRAG and QCC. Table 3. Associations Between Baseline Variables and 2-Week Mortality Variable Category No. 2-wk Mortality OR (95% CI), Univariable P Value AOR (95% CI), Multivariablea,b P Value Age 100 bpm 88 24% (21) 1.9 (1.1–3.3) Respiratory rate ≤20 bpm 368 13% (49) 1 .002 >20 bpm 87 26% (23) 2.6 (1.4–4.7) CD4 cell count 10 × 109/L 21 48% (10) 6.7 (2.6–17.7) 8.7 (2.5–30.2) CSF opening pressure ≤25 cm CSF 216 18% (38) 1 .488 >25 cm CSF 226 16% (37) 0.8 (.5–1.4) CSF white cell count ≤20 × 106/L 272 20% (54) 1 .017 >20 × 106/L 183 11% (20) 0.5 (.3–0.9) QCC 1st tertile 163 9% (15) 1 100 bpm 86 45% (39) 1.9 (1.2–3.1) Respiratory rate ≤20 bpm 363 30% (110) 1 .006 >20 bpm 84 45% (38) 2.0 (1.2–3.4) CD4 cell count 10 × 109/L 21 63% (13) 4.7 (1.8–12.2) 4.0 (1.3–12.6) CSF opening pressure ≤25 cm CSF 213 39% (83) 1 .009 1 .002 >25 cm CSF 223 30% (66) 0.6 (.4–.9) 0.4 (.3–.7) CSF white cell count ≤20 × 106/L 268 35% (93) 1 .461 >20 × 106/L 179 31% (55) 0.9 (.6–1.3) QCC 1st tertile 161 24% (38) 1 50 years (AOR, 1.4; 95% CI, 1.1–2.0; P = .02) and very high CSF opening pressure (>30 cm CSF; AOR, 1.8; 95% CI, 1.1–3.0; P = .02). Altered mental status was not associated with any other variables examined including baseline fungal burden, CD4 count, or CSF white cell count in adjusted analyses. Baseline CSF Fungal Burden CSF QCCs were negatively correlated with CD4 count, CSF white cell count, CSF protein, and CSF proinflammatory cytokines (IL-6, IFN-γ, and TNF-α). The strongest correlation was with CSF IFN-γ (Pearson r = −0.4, P 25 cm CSF) was present in 51% of the cohort (n = 230). Raised pressure was associated with papilledema (OR, 2.6; 95% CI, 1.1–5.8; P = .02); however, other than the association between very high CSF opening pressures (OP >30 cm) and mental status described above, there were no other significant associations between high OP and clinical variables. Raised OP correlated with increasing CSF TNF-α concentrations (Spearman r = 0.2, P = .008), but not with IFN-γ or IL-6. Although there was no significant correlation between QCC and baseline CSF OP, high baseline QCC was necessary but insufficient for development of a high day 1 and day 14 OP (Supplementary Figure 2). Early Fungicidal Activity EFA was associated with outcome, as shown previously among a subset of 262 patients [17]. A slope measurement was available in 450 of the 501 patients, and in 129 of the 163 patients who died. Mean EFA of those who died at 2 weeks was −0.24 (SD, 0.25) log10 CFU/mL/day vs −0.42 (SD, 0.25) log10 CFU/mL/day in survivors (P 30 cm) was associated independently with altered mental status, but was not contributory to altered mental status in the majority of cases; half of those with altered mental status did not have markedly raised pressures. Of note, altered mental status was not associated with CD4 count, CSF white cell count, or fungal burden. High CSF opening pressure was not associated with increased mortality in this cohort, in contrast to earlier reports [23]. This may have been a result of management: all patients routinely had 4 lumbar punctures over the first 2 weeks of treatment, and raised pressures were managed according to established guidelines [18]. A novel finding of this analysis was that raised CSF opening pressures at baseline, in patients managed according to these guidelines, were associated with improved outcomes at 10 weeks. It is possible that proinflammatory CSF cytokine responses (TNF-α was associated with raised pressure) may be protective in situations where raised OP is appropriately managed, or that large volume CSF drainage is beneficial over and above its role in reducing pressure [23]. These findings emphasize the importance of CSF pressure management in patients with CM, and highlight the need for widened access to manometers to manage pressure safely in centers in Africa with the highest burden of disease. Long-term survival in the cohort of South African patients with access to AmB and ART was good, provided patients survived the acute period. ART was usually started between 3 and 6 weeks after antifungal therapy. Within this time frame, there was no association between earlier ART initiation and the development of subsequent IRIS. Patients who developed IRIS did not have higher overall mortality. The majority of deaths after 2 weeks were attributed to other HIV-related illnesses that may have been preventable through earlier initiation of ART. In the context of amphotericin induction, ART initiation nearer to 3 rather than 6 weeks after starting antifungal therapy may prevent some of the later HIV-related mortality, while not substantially increasing the risk of IRIS. A potential limitation of this analysis, derived from multiple cohorts, is possible residual confounding due to unmeasured study specific effects, relating to temporal or geographic differences between studies. However a key strength of this cohort is the extensive prospectively collected baseline data, allowing adjustment to minimize confounding. There was little evidence of clustering by study within the hierarchical model, and the robustness of the key conclusions was further supported by consistency across univariable and multivariable analyses, and the sensitivity analyses performed. Levels of missing data among outcomes and the key predictor variables were low, reducing the risk of bias. In summary, these data provide a rationale for several strategies to improve outcomes. First, earlier diagnosis of CM should be possible, resulting in lower fungal loads at presentation and a reduction in mortality. Clinicians should have a low threshold for lumbar puncture in HIV-positive patients presenting with headache. Novel point-of-care antigen tests [24, 25] should now facilitate earlier diagnosis. Given the high proportion of patients presenting with CM who have already been diagnosed with HIV (76%), screening for subclinical infection with point-of-care antigen tests and preemptive antifungal treatment, along with early ART initiation, could prevent a substantial proportion of clinical disease from developing [26–28]. Second, increasing access to the most fungicidal AmB-based regimens is a priority in settings with a high incidence of CM [29–31], in particular sub-Saharan Africa. Last, prompt initiation of ART is required to address the substantial proportion of deaths in these patients that are HIV but not CM related. Supplementary Data Supplementary materials are available at Clinical Infectious Diseases online (http://cid.oxfordjournals.org/). Supplementary materials consist of data provided by the author that are published to benefit the reader. The posted materials are not copyedited. The contents of all supplementary data are the sole responsibility of the authors. Questions or messages regarding errors should be addressed to the author. Supplementary Data
