Logistic Regression Analysis
In the multivariate analysis, headache, localized opacity, and mediastinal adenopathy were independently associated with an increased risk of TB (Table 1). The predictive ability and the calibration of the model were good (c-index = 0.85; Hosmer-Lemeshow statistic = 0.7, degree of freedom = 3, P = 0.88).
For PCP, independent predictors included CD4 cell counts ≤50 cells/mm3, diffuse shadowing, Sao2 <90%, and the absence of TMP-SMX prophylaxis (Table 2). The predictive ability of the model was good (c-index = 0.89), and the Hosmer-Lemeshow test showed an excellent calibration (0.97, df = 5, P = 0.97). When data were analyzed with the exclusion of biological results (ie, data available immediately on admission), diffuse shadowing, Sao2 <90%, and the absence of TMP-SMX prophylaxis remained independently associated with the risk of PCP (Table 3). The discrimination and the calibration of this simplified model were good (c-index = 0.87; Hosmer-Lemeshow statistic = 1.17, df = 4, P = 0.88).
Because of the small number of patients with TB (n = 27), we did not attempt to develop a prediction rule. We focused solely on patients with PCP. Using the clinical and radiographic variables that were independently associated with the risk of PCP, we created a score to differentiate PCP from other diseases in AFB smear-negative patients. The β-coefficients derived from the predictors were rounded to the nearest integer to make the scoring system simpler to use in routine clinical practice. Loss of fit due to the rounded coefficients was negligible (c-index = 0.87; Hosmer-Lemeshow statistic = 0.47, df = 4, P = 0.98).
The score is simply computed by a linear combination of the coefficients: PCP score = 2 × diffuse shadowing + 1 × Sao2 <90% and ≥80% or + 2 × Sao2 <80% − 2 × TMP-SMX prophylaxis.
Each factor was assigned the value of 1 if present or 0 if absent. PCP score ranged from −2 to +4.
The risk of PCP can thus be calculated in our population by the appropriate logistic transformation:
Table 3 displays, for each possible score, the frequency of PCP (observed risk of PCP) and the predicted risk of PCP in Cambodian patients.
These predicted risks of PCP were correlated to the prevalence of PCP in the population. Therefore, it is useful to calculate LRs, which measure the performance of the score, independent of the prevalence, to the extent that the prediction rules remain valid in different populations. The LRs ranged from 0.04 for the negative scores to 10.4 for the highest score (Table 3).
Validation (Vietnamese Sample)
Most of the 98 AFB smear-negative Vietnamese patients were men (76%) with a median age of 29 years (IQR 24-35) and a median BMI of 16.9 (IQR 15.6-18.2). The median CD4+ cell counts were 22 cells/mm3 (IQR 10-42), and 72% of the patients were in stage III or IV of the WHO classification for HIV infection. Few of these patients had knowledge of their HIV seropositivity on admission (16% vs 62% in Cambodia). None of them received antiretroviral therapy (vs 10% in Cambodia), and the administration of TMP-SMX prophylaxis was extremely limited (7% vs 39% in Cambodia).
Full investigations for TB and PCP were, respectively, performed in 83 and 69 AFB smear-negative patients (Fig. 1); TB was confirmed in 11 (13%) patients and PCP in 38 (55%) patients (1 coinfection with Escherichia coli).
The prevalence of PCP was similar in the Cambodia and Vietnam (53% and 55%, respectively) samples; therefore, the risk predicted by the score remained valid. The risk of PCP observed in this validation sample is given in Table 3. The LRs ranged from 0.08 to 6.7. When tested in this independent validation sample, the PCP-predicting score maintained correct predictive ability (c-index = 0.72) but showed poor calibration (Hosmer-Lemeshow statistic = 6.7, df = 2, P = 0.04). Figure 2 shows the percentage of PCP observed in the training and validation data sets plotted against the percentage of PCP predicted by the score. Unfortunately, the probability of PCP was not assessable for some values of the score (−2, −1, 1). The line produced for the validation sample is close to the diagonal, meaning that the predicted probabilities are good estimations, except for the score value = 3.
This study evaluated 291 Asian HIV-infected patients affected by AFB smear-negative pneumonia. These patients were young adults at an advanced stage of HIV infection with unequal use of PCP prophylaxis and antiretroviral treatment. Among Cambodian and Vietnamese patients in whom reference tests were performed, the prevalence of TB was, respectively, 16% and 13%, and the prevalence of PCP was 53% and 55%. A comparison with previous Southeast Asian studies (with prevalence of PCP ranging from 5% to 30%) is very difficult because these studies did not focus on AFB smear-negative patients and/or usually the diagnosis was made with clinical standards without laboratory confirmation.18-25
Predictors of AFB Smear-Negative TB
In our analysis, radiographic features predictive of AFB smear-negative TB were the presence of mediastinal adenopathy and localized opacity. The association of mediastinal adenopathy and TB was already well known in severely immunocompromised HIV-infected patients.26-28 As in other studies, cavitations were infrequent in our patients with AFB smear-negative TB.14,29,30 Interestingly, cavitations were mostly present in patients with bacterial pneumonia. Associated pleural effusion was observed in only 4 patients (1 TB), consistent with the previous findings that tuberculous pleuritis is more common in HIV-infected patients with ≥200 CD4 cells/mm3.27,28
Headache was the sole independent clinical predictor of AFB smear-negative TB. According to a Vietnamese study, headache might be the manifestation of tuberculous meningoencephalitis or metabolic disorder such as hyponatremia.31
Previous studies identified hemoptysis, weight loss, fever, and persistent cough (lasting longer than 2 weeks) without expectoration as clinical predictors of AFB smear-negative TB in African populations with high prevalence of HIV infection.14,29,30,32 However, in our study, hemoptysis was less common in TB than in other diseases (not significant). Likewise, the presence of cough was not a useful indicator of TB because it lacked sufficient specificity (present in 99% of the patients). Unfortunately, data on duration of cough, which could have increased the specificity of the factor, were unreliable. Indeed, the interval of time between the onset of pneumonia and admission was indefinite because of confusion between the symptoms of pneumonia and those of AIDS. This is especially true because the majority of patients in the study were at late stage of HIV disease. Temperature at admission was also unreliable because of the frequent and uncontrolled use of antipyretics.
The c-index and Homer-Lemeshow test showed good fit of the model; however, it is well known that goodness-of-fit tests are less powerful for moderate sample sizes.33 Because of the low power of the statistical comparison (27 TB), we cannot exclude other factors as potential predictors, and developing a score seemed not acceptable.
Predictors of PCP and Scoring System
Diffuse shadowing on radiography was the strongest predictor of PCP [odds ratio (OR) = 7.0, P < 10−3]. Low Sao2 (≤90% and <80%) was statistically associated with an increased risk of PCP (OR = 3.3 and OR = 9.1, respectively, P = 0.005). Eighty percent of patients with Sao2 ≤90% and 91% with Sao2 <80% had PCP. This result, consistent with previous reports, highlights the usefulness of the noninvasive and safe Sao2 measurement.34-37 The equipment required for Sao2 monitoring is inexpensive, portable, does not require a specialized operator, and provides results immediately available.36 Other studies have found high respiratory rate as useful predictor of PCP.24,38 Further studies should evaluate if this feature could provide an alternative measure when a pulse oxymeter is unavailable. Dyspnea was more common in patients with PCP but was not an independent predictor (P = 0.06). Indeed, dyspnea may result from hypoxemia as in PCP but also from anemia as in TB. The only laboratory data independently associated with the presence of PCP were low CD4 cell counts. However, the high level of immunosuppression in the whole population (82% of the patients had CD4 cell count <50 cells/mm3) lessens the relevance of this factor.
A study carried out in the United Kingdom has found that exercise-induced oxygen desaturation, interstitial infiltrates, absence of PCP prophylaxis, and symptoms triad of dyspnea, cough, and fever as useful predictors of PCP in HIV-infected patients.35 In the Unites States, independent predictors of PCP in HIV-positive patients presented with respiratory disease were exertional dyspnea, interstitial infiltrate, and presence of oral thrush.39 However, in our patients hospitalized at a more advanced stage of the disease, hypoxemia was present at rest, opacities were diffuse in 90% of the cases, and it was impossible to disentangle alveolar and interstitial patterns.
We developed a PCP score that includes low Sao2, absence of TMP-SMX prophylaxis, and diffuse shadowing. This score, based on rounded coefficients, provides a simple and rapid assessment of the probability of PCP in AFB smear-negative patients with advanced HIV disease.
PCP score ranges from −2 to +4. Using this score with a cutoff of ≥+3 to identify patients with PCP, we would have correctly classified 55 of 84 PCP (sensitivity = 65%) and 68 of 76 excluded PCP (specificity = 89%) in the Cambodian sample. Using ≥+2 as a cutoff would have increased the sensibility to 89% but lowered the specificity to 74%. In the Vietnamese sample, sensitivity and specificity would have been 43% and 77%, respectively, for a cutoff ≥+3 and 97% and 46% for a cutoff ≥+2. The LRs ranged from 0.04 to 10.4. Considering the Cambodian sample, the score seemed to be particularly useful for 31% of the patients with extreme values (+4 and negative scores), for whom estimated probabilities are robust (respectively, 92% and 4%), and helpful for 46% (+3 and 0). The scoring system was of limited use for 23% of the patients with intermediate scores (+1 and +2). We would like to emphasize that the score allows for the identification of patients needing further investigation for PCP. Indeed, among patients with intermediate scores, it may be desirable to perform induced sputum or BAL when available.
Owing to possible biases in 1-center population sampling,40 we performed an independent validation study in a different center located in another country. The probability of PCP was not assessable for some values of the score (−2, −1, and +1) not met by the patients of the validation sample. The score maintained a good predictive ability, but Hosmer-Lemeshow statistic showed a lack of fit. The absence of important predictors in our model could explain this weakened performance in a population with different case mix. However, no other clinical predictors of PCP could be identified in the Vietnamese population. The sample size may also be too small to perform a correct validation. Comparison of observed to predicted probabilities indicated that the model did not perform satisfactorily for the score +3. This discrepancy might be the consequence of the small size of the validation sample; for example, with 14 patients presenting a score +3, minor variations in the number of PCP could strongly impact the observed risk of PCP.
There are certain limitations to this study. First, 62 patients who did not undergo BAL were not included in the PCP statistical analyses, which could lead to selection biases. Statistical comparisons pointed out that the mortality rate was significantly higher in this group but did not show any difference between the population included in the analyses and the population without BAL. Second, although WHO recommends the examination for AFB on repeated sputum, only 1 sputum was collected for most of the patients. Consequently, this score should be calculated in patients directly after obtaining a first negative sputum. This fits well with observed clinical practice, as the score can be computed directly at admission, allowing for early identification of PCP. Third, this hospital-based study involved highly immunocompromised patients; it is unclear whether these findings may be applied to general practices.
This study confirms that PCP is of major importance in HIV-positive patients with “AFB smear-negative pulmonary disease” in Southeast Asia. The PCP-predicting score, based on few clinical and radiographic predictors available on admission to hospital in low-income countries, will optimize the identification of patients with PCP, allowing timely therapy. However, other validation studies would be required in similar and different settings to confirm these initial findings.
We wish to thank Pamela Snupf for rereading the manuscript.
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Keywords:© 2008 Lippincott Williams & Wilkins, Inc.
HIV; Pneumocystis jiroveci pneumonia (PCP); pulmonary tuberculosis (TB); acid-fast bacillus (AFB) smear-negative sputum; prediction rule; Southeast Asia