Abstract
Parainfluenza virus (PIV) infection is a significant cause of morbidity and mortality, especially in hematologic malignancy patients including hematopoietic stem cell transplantation (HCT) recipients. However, limited information is available for risk stratification in PIV-infected patients with hematologic malignancy with or without HCT. Patients with hematologic malignancy diagnosed with PIV from January 2009 to December 2018 were retrospectively included in a tertiary care hospital in Seoul, South Korea. Upper respiratory tract infection (URTI) was defined as the detection of PIV in a nasopharyngeal sample with URTI symptoms without new pulmonary infiltrates. Lower respiratory tract infection (LRTI) was defined as detection of PIV in either upper or lower respiratory tract samples with new pulmonary infiltrates, with or without hypoxia. PIV-associated mortality was defined as death with respiratory failure and persistent LRTI within 90 days after diagnosis. The study included 143 adult patients. Of these, 55 (38%) progressed to or initially presented with LRTI. Among these, 22 (40%) died from PIV-associated mortality. An immunodeficiency risk score was developed from associated risk factors using a multivariable Cox regression model. Patients were stratified into low (0–2), moderate (3–5), and high risk (6–8) groups with PIV-associated mortalities of 0%, 9%, and 67%, respectively (p < 0.005, Harrell’s C-index = 0.84). PIV infection can result in substantial mortality in patients with hematologic malignancy if it progresses to LRTI. The immunodeficiency risk score presented here may be useful for distinguishing moderate and high risk groups that might benefit from antiviral therapy.
Keywords: Parainfluenza virus, Hematologic malignancy, Immunodeficiency, Prediction model
Introduction
Parainfluenza virus (PIV) infection is one of the most common respiratory virus infections and is a significant cause of morbidity and mortality, especially in patients with hematologic malignancy including recipients of hematopoietic stem cell transplantation (HCT) [1–6]. Previous studies have identified various risk factors for the progression of PIV infection to pneumonia and attributable mortality in recipients of HCT [7–10]. In addition, the efficacy of ribavirin (aerosolized, intravenous, or oral) in previous studies showed mixed results [9, 11–14].
PIV infection in hematologic malignancy also results in significant mortality and morbidity in patients without HCT [5, 12]. It is therefore of clinical importance to identify groups at high risk of progression to lower respiratory tract infection and death, among patients with hematologic malignancy with or without HCT. Furthermore, since the heterogeneity of an individual patient’s risk might contribute to the mixed results of the efficacy of ribavirin, stratification of such patients by risk could reveal subgroups of patients who might benefit the most from antiviral therapy. However, limited data and tools are available for risk stratification of such patients. Therefore, in this study, we aimed to develop a risk prediction model and analyze the efficacy of ribavirin in each risk group.
Methods
Study population
A retrospective cohort study was conducted for adult (age ≥ 18) patients with hematologic malignancy who were diagnosed with PIV infection at a 2700-bed, tertiary care hospital in Seoul, South Korea, from January 2009 to December 2018. All patient records were previously de-identified and were reviewed through the electronic medical records database system Asan BiomedicaL Research Environment (ABLE). In cases of patients with recurrent PIV infections, only the first episode was analyzed. Comorbidity status of each patient was assessed using McCabe score and Charlson comorbidity index. This study was approved by the institutional review board in our hospital.
Definitions
Upper respiratory tract infection (URTI) was defined as the detection of PIV in a nasopharyngeal sample with URTI symptoms without new infiltrates in the lungs [7–9, 12, 13]. Lower respiratory tract infection (LRTI) was defined as the detection of PIV in either upper or lower respiratory tract samples with new pulmonary infiltrates, with or without hypoxia [12, 13]. PIV-associated mortality was defined as death with respiratory failure and persistent LRTI within 90 days after the diagnosis of PIV [5, 15]. Nosocomial infection was defined as infection occurring 7 or more days after admission [7, 11]. Coinfection was defined as significant pathogens identified on a nasopharyngeal swab/aspirate, sputum culture, bronchoalveolar lavage, or blood culture within 3 days before or after the first identification of PIV [13]. Steroid use was defined as intravenous or oral use of steroids within 2 weeks before or at the time of PIV diagnosis [9, 10].
Therapeutic interventions
Oral ribavirin was given to patients at the discretion of attending hematologists and infectious disease consultants with or without intravenous immunoglobulin (IVIG) at a dose of 500 mg/kg with various durations. Standard and droplet precautions and isolation procedures were applied to all patients.
Virological evaluation
PIV infection was diagnosed by multiplex reverse transcription-PCR (RT-PCR) using Seeplex RV15 ACE Detection (Seegene Inc., Seoul, Republic of Korea) and shell vial culture for parainfluenza virus (Diagnostic Hybrids, Inc., Athens, OH) with specimens obtained by nasopharyngeal swab/aspirate or bronchoalveolar lavage.
Statistical analysis
Statistical analysis was done with Python 3.7.3 (G. van Rossum, The Python Language Reference Manual, Network Theory Ltd., September 2003) using SciPy (Jones E, Oliphant E, Peterson P, et al. SciPy: Open Source Scientific Tools for Python, 2001-, http://www.scipy.org/ [Online; accessed 2019-10-22]) and Lifelines libraries (Davidson-Pilon C et al., doi:10.5281/zenodo.1252342). Categorical variables were analyzed with a Chi-squared test or Fisher’s exact test as appropriate. Continuous variables were analyzed with a Student’s t test or Mann-Whitney U test as appropriate. A significance level of 0.05 was employed for all analyses.
Development of immunodeficiency risk score
Risk factor analysis was performed with a Cox proportional hazards model. All variables subject to analysis in the multivariable model were tested for proportional hazard assumption, and variables that violated the assumption were analyzed as time-dependent variables. Points were assigned according to weighting criteria based on the coefficient of each risk factor in the Cox model. Score was calculated as the sum of all points. The cutoff values of scores for risk groups were defined according to a receiver operating characteristic curve with Youden index. PIV-associated mortality was compared among the risk groups using the Kaplan-Meier failure curves. The performance of this risk prediction model was assessed using the log-rank test and Harrell’s C-index.
Results
Clinical and hematologic characteristics of patients
A total of 143 patient records were reviewed and analyzed. Of these, 55 (38%) patients progressed to or initially presented with LRTI. Among these 55 patients, 22 (40%) died with persistent LRTI and respiratory failure within 90 days after diagnosis. The clinical and hematologic characteristics are shown in Table 1. Most characteristics were similar between the URTI and LRTI groups, with the exceptions of place of acquisition (p = 0.022), allogeneic hematopoietic stem cell transplantation (44% vs. 67%, p = 0.017), coinfection (17% vs. 35%, p = 0.029), steroid use (42% vs. 56%, p = 0.019), ribavirin use (35% vs. 60%, p = 0.006), and IVIG use (8% vs. 38%, p < 0.001).
Table 1.
Clinical and hematologic characteristics of all patients
| Total | URTI | LRTI | p value | |
|---|---|---|---|---|
| Characteristics | (n = 143) | (n = 88) | (n = 55) | |
| Age, median years (IQR) | 50 (34–58) | 49 (32–57) | 51 (38–61) | 0.120 |
| Male gender, n (%) | 67 (47) | 44 (50) | 23 (42) | 0.434 |
| Site of infection at diagnosis, n (%) | < 0.001 | |||
| Upper respiratory tract | 103 (72) | 88 (100) | 15 (27) | |
| Lower respiratory tract | 40 (28) | 0 (0) | 40 (73) | |
| Place of acquisition, n (%)a | 0.022 | |||
| Community | 45 (31) | 21 (24) | 24 (45) | |
| Nosocomial | 98 (69) | 67 (76) | 31 (55) | |
| Type of parainfluenza virus, n (%) | 0.370 | |||
| PIV 1 | 17 (12) | 10 (11) | 7 (13) | |
| PIV 2 | 2 (1) | 2 (2) | 0 (0) | |
| PIV 3 | 112 (78) | 71 (81) | 41 (74) | |
| PIV 4 | 12 (8) | 5 (6) | 7 (13) | |
| Diagnosis, n (%) | 0.166 | |||
| Acute myeloid leukemia | 92 (64) | 56 (64) | 36 (65) | |
| Acute promyelocytic leukemia | 1 (1) | 0 (0) | 1 (2) | |
| Acute lymphoblastic leukemia | 48 (34) | 32 (36) | 16 (29) | |
| Chronic lymphocytic leukemia | 1 (1) | 0 (0) | 1 (2) | |
| Aggressive NK-cell leukemia | 1 (1) | 0 (0) | 1 (2) | |
| HCT, n (%) | 76 (53) | 39 (44) | 37 (67) | 0.017 |
| Type of transplant | 0.372 | |||
| Allogeneic, siblings | 18/76 (24) | 7/39 (18) | 11/37 (30) | |
| Allogeneic, non-sibling, family member | 30/76 (40) | 17/39 (44) | 13/37 (35) | |
| Allogeneic, unrelated | 28/76 (37) | 15/39 (39) | 13/37 (35) | |
| Stem cell source | 0.423 | |||
| Bone marrow | 1/76 (1) | 0/39 (0) | 1/37 (3) | |
| Peripheral blood | 72/76 (95) | 38/39(97) | 32/37 (92) | |
| Unknown | 3/76 (4) | 1/39 (3) | 2/37 (5) | |
| Conditioning regimen, n (%) | 0.692 | |||
| Myeloablative with TBI | 1 (1) | 1/39 (3) | 0/37 (0) | |
| Myeloablative without TBI | 64 (84) | 34/39 (87) | 30/37 (81) | |
| Reduced intensity | 3 (4) | 3/39 (8) | 6/37 (16) | |
| Uncertain | 0 (0) | 1/39 (3) | 1/37 (3) | |
| GVHD, n (%) | 34/76 (45) | 17/39 (44) | 17/37 (46) | 0.981 |
| Type of GVHD | 0.799 | |||
| Acute | 8/76 (11) | 3/17 (18) | 5/17 (29) | |
| Chronic | 26/76 (34) | 14/17 (82) | 12/17 (71) | |
| Hematologic disease status, n (%) | 0.803 | |||
| Remission | 93 (65) | 59 (67) | 34 (62) | |
| Persistent/relapse | 48 (33) | 28 (32) | 20 (36) | |
| Uncertain | 2 (1) | 1 (1) | 1 (2) | |
| McCabe score, n (%) | 0.317 | |||
| Rapidly fatal | 135 (94) | 81 (92) | 54 (98) | |
| Ultimately fatal | 7 (5) | 6 (7) | 1 (2) | |
| Non-fatal | 1 (1) | 1 (1) | 0 (0) | |
| Charlson comorbidity index score, median (IQR) | 3 (2–4) | 3 (2–4) | 3 (2–4) | 0.423 |
| Coinfection, n (%)b | 34 (45) | 15 (17) | 19 (35) | 0.029 |
| Type of coinfection | 0.028 | |||
| Bacterialc | 6 (18) | 1/15 (7) | 5/19 (26) | |
| Virald | 20 (59) | 11/15 (73) | 9/19 (47) | |
| Fungale | 8 (24) | 3/15 (20) | 5/19 (26) | |
| Steroid use, n (%) | 68 (48) | 37 (42) | 31 (56) | 0.019 |
| Median dose (mg) per kilogram (IQR)f | 0.33 (0.19–0.63) | 0.36 (0.24–0.50) | 0.32 (0.17–0.87) | 0.001 |
| Immunosuppressant use g, n (%) | 64 (45) | 41 (47) | 23 (42) | 0.699 |
| Initial total WBC count, median (IQR) | 2500 (600–6000) | 2250 (600–5400) | 3000 (450–7100) | 0.459 |
| Initial ANC, median (IQR) | 1080 (75–3350) | 940 (78–3133) | 1360 (70–3865) | 0.314 |
| Initial ALC, median (IQR) | 570 (154–1308) | 559 (191–1302) | 570 (100–1309) | 0.359 |
| Initial monocyte count, median (IQR) | 225 (24–659) | 222 (25–662) | 230 (27–613) | 0.339 |
| Ribavirin use, n (%) | 64 (45) | 31 (35) | 33 (60) | 0.006 |
| Median dose (mg) per kilogram (IQR) | 16.4 (14.2–21.6) | 16.2 (13.6–20.9) | 16.5 (14.7–21.5) | 0.002 |
| Intravenous immunoglobulin use, n (%) | 28 (20) | 7 (8) | 21 (38) | < 0.001 |
Abbreviations: URTI, upper respiratory tract infection; LRTI, lower respiratory tract infection; PIV, Parainfluenza virus; HCT, hematopoietic stem cell transplantation; TBI, total body irradiation; GVHD, graft-versus-host disease; WBC, white blood cell; ANC, absolute neutrophil count; ALC, absolute lymphocyte count; IQR, interquartile range
aNosocomial infections were defined as those occurring 7 or more days after admission
bCoinfections were defined as significant pathogens identified on a nasopharyngeal swab/aspirate, sputum culture, bronchoalveolar lavage, or blood culture within 3 days before or after the first identification of parainfluenza virus
cIncludes Enterococcus faecium (n = 1), Pseudomonas aeruginosa (n = 1), Escherichia coli (n = 1), Streptococcus pneumoniae (n = 1), Stenotrophomonas maltophilia (n = 1), and Klebsiella pneumoniae (n = 1)
dIncludes rhinovirus (n = 5), RSV (n = 3), metapneumovirus (n = 3), adenovirus (n = 2), coronavirus (n = 2), and bocavirus (n = 2). PIV 1 and PIV 3 were found simultaneously on the nasopharyngeal PCR of one patient
eIncludes aspergillosis (n = 5, 4 probable IPA, 1 possible IPA), Candida tropicalis (n = 1), Pneumocystis jirovecii (n = 1)
fPeak dose of steroid used within 2 weeks before or at PIV diagnosis
gIncludes cyclosporin, cyclophosphamide, or intensive chemotherapy that renders patients nadir status at PIV diagnosis
Immunodeficiency risk factors
In a multivariable Cox proportional hazards regression analysis, neutropenia (absolute neutrophil count < 500 μL), age of 40 and above, allogeneic HCT, and LRTI at presentation were found to be significant risk factors independently associated with PIV-associated mortality (Table 2). The cutoff value of 40 years was included in the multivariable analysis because, among the age cutoff values include in a univariable analysis (30-year, 40-year, 50-year, 60-year and 70-year), this was the only value that resulted in a p value less than 0.1 (hazard ratio [HR], 3.38; 95% confidence interval [CI], 1.0–11.47; p = 0.05). Rituximab was used within 6 months (median, 3 months; interquartile range [IQR], 2.75–3 months) prior to the diagnosis of PIV infection in 4 patients (3 with acute lymphoblastic leukemia and 1 with acute myeloblastic leukemia), and it was not significantly associated with PIV-associated mortality in univariable analysis (HR, 3.52; 95% CI, 0.82–15.03; p = 0.09). Other immunosuppressants such as cyclosporin, cyclophosphamide, or intensive chemotherapy were not significantly associated with PIV-associated mortality in both univariable (HR, 1.01; 95% CI, 0.44–2.34; p = 0.97) and multivariable Cox regression analysis (HR, 0.584; 95% CI, 0.23–1.49; p = 0.261). Steroid use was not a significant risk factor in both univariable and multivariable analyses.
Table 2.
Immunodeficiency risk scores for patients with hematologic malignancy infected with parainfluenza virus
| Patients, n = 143 | PIV-associated mortality (90-day), n = 22 |
||||||
|---|---|---|---|---|---|---|---|
| Variables | n (%) | n (%) |
Adjusted HRa (95% CI) |
Coefficient | Weighing criteria | Points | |
| 1 | ANC < 500/μL | 61 (43) | 17 (28) | 11.13 (3.52–35.16) | 2.410 | > 2 | 3 |
| 2 | Age ≥ 40 yr | 96 (67) | 19 (20) | 4.56 (1.14–18.28) | 1.518 | 1–2 | 2 |
| 3 | Allogeneic HCT b | 53 (37) | 11 (21) | 3.39 (1.32–8.72) | 1.222 | 1–2 | 2 |
| 4 | LRTI at presentation | 40 (28) | 15 (38) | 1.03 (1.004–1.059) | 0.031 | 0–1 | 1 |
| Minimum possible score | 0 | ||||||
| Maximum possible score | 8 | ||||||
| Low risk | 0–2 | ||||||
| Moderate risk | 3–5 | ||||||
| High risk | 6–8 |
Abbreviations: LRTI, lower respiratory tract infection; HR, hazard ratio; CI, confidence interval; n, number; ANC, absolute neutrophil count; HCT, hematopoietic stem cell transplantation
aAdjusted for Charlson comorbidity index score and ribavirin use
bAll patients received allogeneic stem cell transplantation
Development of risk score model
For each risk factor, points were assigned according to the aforementioned calculations. To define score cutoff values for risk groups, sensitivity and specificity were calculated for each score as a cutoff value for a 90-day PIV-associated mortality (Table 3). For all scores, a score of 5 resulted in the maximal Youden index (0.62), and among the scores equal to or less than 5, a score of 2 resulted in the maximal Youden index (0.36) with 100% sensitivity (Fig. 1). According to these results, risk groups were defined as low risk (0–2), moderate risk (3–5), and high risk (6–8).
Table 3.
Sensitivity and specificity for cutoff values to predict PIV-associated mortality
| Score | Sensitivity (%) | Specificity (%) | Positive predictive value | Negative predictive value | Youden index |
|---|---|---|---|---|---|
| 0 | 100 | 3 | 0.16 | 1.00 | 0.03 |
| 1 | 100 | 5 | 0.16 | 1.00 | 0.05 |
| 2 | 100 | 34 | 0.22 | 1.00 | 0.34 |
| 3 | 95 | 46 | 0.24 | 0.98 | 0.41 |
| 4 | 86 | 60 | 0.28 | 0.96 | 0.46 |
| 5 | 68 | 94 | 0.68 | 0.94 | 0.62 |
| 6 | 27 | 96 | 0.55 | 0.88 | 0.23 |
| 7 | 14 | 100 | 1.00 | 0.86 | 0.14 |
| 8 | 0 | 100 | N/A | 0.85 | 0.00 |
| Score (≤ 5) | |||||
| 0 | 100 | 4 | 0.06 | 1.00 | 0.04 |
| 1 | 100 | 5 | 0.06 | 1.00 | 0.05 |
| 2 | 100 | 36 | 0.09 | 1.00 | 0.36 |
| 3 | 86 | 49 | 0.09 | 0.98 | 0.35 |
| 4 | 57 | 64 | 0.09 | 0.96 | 0.21 |
| 5 | 0 | 100 | N/A | 0.94 | 0.00 |
Abbreviations: N/A, not applicable
Fig. 1.
Receiver operating characteristic curve for all scores (a) and scores equal to or lower than 5 (b)
Prediction of PIV-associated mortality
In the univariable Cox proportional hazard model, risk group as an ordered factor was significantly associated with PIV-associated mortality (HR, 12.51; 95% CI, 5.37–29.37; p < 0.005). The Kaplan-Meier failure curves showed an increasing trend of PIV-associated mortality according to risk group with significant differences between the groups: 0% in the low risk group, 9% in the moderate risk group, and 67% in the high risk group. Harrell’s C-index for this prediction model was 0.84 (Fig. 2).
Fig. 2.
Kaplan-Meier curves for PIV-associated mortality by risk group
When this model was applied to the subgroup of allogeneic HCT recipients, mortality in each risk group showed similar results and tendency: 0% in the low, 9% in the moderate, and 57% in the high risk group with Harrell’s C-index 0.81 (Fig. 3).
Fig. 3.
Kaplan-Meier curves for PIV-associated mortality by risk group for HCT recipients
Efficacy of oral ribavirin according to risk group
Oral ribavirin use had no significant impact on PIV-associated mortality in all risk groups. Although more patients died in the ribavirin group than in the non-ribavirin group in the moderate risk group (5% vs. 14%; HR, 2.50; p = 0.27), the result was not statistically significant. Fewer patients died in the ribavirin group in the high risk group, but this was also not statistically significant. When stratified according to ribavirin dose, a similar trend was observed, yet the differences were significant in the moderate risk group in both < 15 mg/kg and > 20 mg/kg subgroups (Table 4). The median time from diagnosis to ribavirin use was 2 days (IQR, 1–4 days), with no significant difference (p = 0.196) between patients who died with LRTI and respiratory failure (median, 2 days; IQR, 2–4.5 days) and patients who did not (median, 2 days; IQR, 1–4 days).
Table 4.
PIV-associated mortality according to risk group and ribavirin use
| Risk group | n | PIV-associated mortality (90-day) n (%) |
n | PIV-associated mortality (90-day) n (%) |
HR (95% CI) |
|---|---|---|---|---|---|
| Ribavirin use, median (IQR) 16.4 mg/kg (14.2–21.6) | |||||
| No | Yes | ||||
| Low | 29 | 0 (0) | 12 | 0 (0) | N/A |
| Moderate | 43 | 2 (5) | 37 | 5 (14) | 2.50 (0.49–12.94) |
| High | 7 | 5 (71) | 15 | 10 (67) | 0.84 (0.29–2.48) |
| Ribavirin < 15 mg/kg, median (IQR) 12.9 mg/kg (10.6–14.4) | |||||
| No | Yes | ||||
| Low | 34 | 0 (0) | 7 | 0 (0) | N/A |
| Moderate | 55 | 2 (4) | 25 | 5 (20) | 5.25 (1.02–27.11) |
| High | 13 | 10 (77) | 9 | 5 (56) | 0.56 (0.19–1.65) |
| Ribavirin 15–20 mg/kg, median (IQR) 17.0 mg/kg (16.2–17.4) | |||||
| No | Yes | ||||
| Low | 37 | 0 (0) | 4 | 0 (0) | N/A |
| Moderate | 65 | 5 (8) | 15 | 2 (13) | 1.64 (0.32–8.41) |
| High | 18 | 14 (78) | 4 | 1 (25) | 0.21 (0.03–1.65) |
| Ribavirin > 20 mg/kg, median (IQR) 23 mg/kg (23.0–27.5) | |||||
| No | Yes | ||||
| Low | 38 | 0 (0) | 3 | 0 (0) | N/A |
| Moderate | 70 | 4 (6) | 10 | 3 (30) | 5.21 (1.16–23.34) |
| High | 17 | 11 (65) | 5 | 4 (80) | 1.25 (0.39–3.97) |
Abbreviation: LRTI, lower respiratory tract infection; n, number; N/A, not applicable; IQR, interquartile range
Discussion
In our cohort, 38% of all patients with PIV infection initially presented with or progressed later to LRTI, and 15% of patients who initially presented with URTI progressed to LRTI. In addition, 40% of patients who initially presented with or progressed to LRTI died due to respiratory illness within 90 days of diagnosis. The progression rate to LRTI and the mortality rate by respiratory failure of LRTI patients were similar to the findings of previous studies, 12–35% and 17–47%, respectively [4–7, 10, 12]. The immunodeficiency risk score developed here using previously known and prevalent risk factors [6–10, 12, 15] distinctly differentiates low, moderate, and high risk groups among patients who have hematologic malignancy with or without HCT and also within the subgroup of HCT recipients. Oral ribavirin showed no effect on the prevention of PIV-associated death in any risk group, even after stratification by dosage.
Shah et al. [15] previously reported a score model for respiratory syncytial virus (RSV) infection among HCT recipients to predict progression to LRTI and RSV-associated mortality combining known risk factors for immunodeficiency. PIV has comparable mortality and morbidity to RSV in immunocompromised patients, yet it differs in that a substantial portion of LRTI patients initially present with LRTI at the time of diagnosis [10]. Moreover, although previous studies have investigated risk factors for progression to LRTI and PIV-associated mortality in HCT recipients [7–10], to our knowledge, this study is the first to develop a score model to predict PIV-associated mortality among patients with hematologic malignancy with or without HCT.
Steroid use has been consistently suggested as a significant risk factor of progression to LRTI and PIV-associated mortality in many studies in a dose-dependent fashion, especially at a dose of more than 1 mg/kg [7, 9, 10, 13, 15]. However, in the present study, steroid dose was mostly under 1 mg/kg (median, 0.33 mg/kg; IQR, 0.19–0.63 mg/kg), and only those who received steroids before or at PIV diagnosis were deemed to have this factor, which might have led to the result that steroid use was not significant in both univariable and multivariable analyses.
Ribavirin, oral or aerosolized, has been shown to be efficacious for RSV treatment in HCT recipients [16], especially in the high risk group [15]. However, for PIV, except in several small studies [11, 14, 17], retrospective studies have not shown either oral or aerosolized ribavirin to prevent progression to LRTI and death with respiratory failure [7–10, 12, 13]. In the present study, oral ribavirin did not significantly reduce PIV-associated mortality in any risk group regardless of dosage. This finding is consistent with our previous study using propensity score matching to offset selection bias, which revealed that in hematologic malignancy patients with paramyxovirus infection, ribavirin was not associated with better outcomes [13]. Interestingly, more patients died in the ribavirin group in the moderate risk group at doses of under 15 mg/kg and over 20 mg/kg. The reason for these counterintuitive findings is unclear. However, selection bias may play a role. Nevertheless, we cannot rule out the possibility of an adverse effect of oral ribavirin therapy in critically ill patients with PIV infection.
It is noteworthy that Fludase (DAS181, Ansun BioPharma, Inc., San Diego, CA), a sialidase fusion protein, was efficacious against PIV in vitro and in small studies with HCT recipients [18–21]. Currently, phase 3 clinical trials of DAS181 in hospitalized patients with PIV infection are ongoing. This novel antiviral agent needs to be validated in a larger trial, and an immunodeficiency risk score might be helpful in selecting patients who would benefit the most from antiviral therapy.
The present study has several limitations. First, as a relatively small number of events (PIV-associated death) limited the analytic power of the Cox proportional hazards model, a few risk factors that were previously reported as significant might be excluded from the final model, such as low monocyte count, coinfection, and the status of hematologic malignancy [7, 10, 12]. In addition, some may argue that the heterogenous population including both HCT recipients and non-HCT patients with hematologic malignancy could result in missed analysis for the effect on infection severity of other potential factors. However, since both non-HCT recipients with hematologic malignancy and HCT recipients are at risk of PIV with similar mortality risk [12], we believe that our simple and practical prediction model might have clinical value.
Second, the effect size of significant risk factors might be overestimated due to a limited sample size. To offset such a statistical bias, the final model includes previously established risk factors, and points were assigned using risk factor coefficients, not hazard ratios. Finally, although the prediction model in the present study showed good performance, the possibility of overfitting cannot be ruled out since it was not validated using an external cohort. To ensure the generalizability of the model, external validation using a larger cohort is required.
Conclusions
PIV infection results in substantial mortality if it progresses to LRTI in patients who have hematologic malignancy with or without HCT, especially in moderate to high risk groups. The immunodeficiency risk score developed here may be employed as a useful tool to distinguish moderate and high risk groups who might benefit from antiviral therapy, not only among patients with hematologic malignancy but also HCT recipients. Oral ribavirin was not efficacious in preventing PIV-associated death in any risk group.
Author contributions
Sung-Han Kim as the corresponding author, designed, initiated the study, conducted manuscript writing/review, and has the final responsibility for the decision to submit for publication; Jeongsoo Lee collected and analyzed patients’ data, carried out the statistical analysis, manuscript writing, and built the final score model. Jiwon Jung, Min-Jae Kim, Yong Pil Chong, Sang-Oh Lee, Sang-Ho Choi, Yang Soo Kim, Jun Hee Woo, Eun-Ji Choi, Han-Seung Park, Jung-Hee Lee, Je-Hwan Lee, and Kyoo-Hyung Lee were involved in the study design, interpretation of results, and manuscript writing. All the authors participated in the review of the manuscript.
Compliance with ethical standards
Conflict of interest
There are no potential conflicts of interest for any authors.
Ethics approval and consent to participate
The protocols of this study were approved by the institutional review board of Asan Medical Center. All procedures followed were in accordance with institutional and national ethical standards and with the Helsinki Declaration of 1975, as revised in 2008. Informed consent was waived in view of the retrospective nature of the study. Confidentiality and anonymity of patient data was maintained throughout.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
References
- 1.Bowden RA (1997) Respiratory virus infections after marrow transplant: the Fred Hutchinson Cancer Research Center experience. Am J Med 102:27–30; discussion 42-23. 10.1016/s0002-9343(97)00007-7 [DOI] [PubMed]
- 2.Chemaly RF, Shah DP, Boeckh MJ. Management of respiratory viral infections in hematopoietic cell transplant recipients and patients with hematologic malignancies. Clin Infect Dis. 2014;59(Suppl 5):S344–S351. doi: 10.1093/cid/ciu623. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Ljungman P. Respiratory virus infections in bone marrow transplant recipients: the European perspective. Am J Med. 1997;102:44–47. doi: 10.1016/s0002-9343(97)00010-7. [DOI] [PubMed] [Google Scholar]
- 4.Pochon C, Voigt S. Respiratory virus infections in hematopoietic cell transplant recipients. Front Microbiol. 2018;9:3294. doi: 10.3389/fmicb.2018.03294. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Shah DP, Shah PK, Azzi JM, Chemaly RF. Parainfluenza virus infections in hematopoietic cell transplant recipients and hematologic malignancy patients: a systematic review. Cancer Lett. 2016;370:358–364. doi: 10.1016/j.canlet.2015.11.014. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Ustun C, Slaby J, Shanley RM, et al. Human parainfluenza virus infection after hematopoietic stem cell transplantation: risk factors, management, mortality, and changes over time. Biol Blood Marrow Transplant. 2012;18:1580–1588. doi: 10.1016/j.bbmt.2012.04.012. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Nichols WG, Corey L, Gooley T, Davis C, Boeckh M. Parainfluenza virus infections after hematopoietic stem cell transplantation: risk factors, response to antiviral therapy, and effect on transplant outcome. Blood. 2001;98:573–578. doi: 10.1182/blood.v98.3.573. [DOI] [PubMed] [Google Scholar]
- 8.Pinana JL, Hernandez-Boluda JC, Calabuig M et al (2017) A risk-adapted approach to treating respiratory syncytial virus and human parainfluenza virus in allogeneic stem cell transplantation recipients with oral ribavirin therapy: a pilot study. Transpl Infect Dis:19. 10.1111/tid.12729 [DOI] [PubMed]
- 9.Seo S, Xie H, Campbell AP, Kuypers JM, Leisenring WM, Englund JA, Boeckh M. Parainfluenza virus lower respiratory tract disease after hematopoietic cell transplant: viral detection in the lung predicts outcome. Clin Infect Dis. 2014;58:1357–1368. doi: 10.1093/cid/ciu134. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Seo S, Xie H, Leisenring WM, Kuypers JM, Sahoo FT, Goyal S, Kimball LE, Campbell AP, Jerome KR, Englund JA, Boeckh M. Risk factors for parainfluenza virus lower respiratory tract disease after hematopoietic cell transplantation. Biol Blood Marrow Transplant. 2019;25:163–171. doi: 10.1016/j.bbmt.2018.08.021. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Chakrabarti S, Collingham KE, Holder K, Fegan CD, Osman H, Milligan DW. Pre-emptive oral ribavirin therapy of paramyxovirus infections after haematopoietic stem cell transplantation: a pilot study. Bone Marrow Transplant. 2001;28:759–763. doi: 10.1038/sj.bmt.1703216. [DOI] [PubMed] [Google Scholar]
- 12.Chemaly RF, Hanmod SS, Rathod DB, Ghantoji SS, Jiang Y, Doshi A, Vigil K, Adachi JA, Khoury AM, Tarrand J, Hosing C, Champlin R. The characteristics and outcomes of parainfluenza virus infections in 200 patients with leukemia or recipients of hematopoietic stem cell transplantation. Blood. 2012;119:2738–2745. doi: 10.1182/blood-2011-08-371112. [DOI] [PubMed] [Google Scholar]
- 13.Park SY, Baek S, Lee SO, Choi SH, Kim YS, Woo JH, Sung H, Kim MN, Kim DY, Lee JH, Lee JH, Lee KH, Kim SH. Efficacy of oral ribavirin in hematologic disease patients with paramyxovirus infection: analytic strategy using propensity scores. Antimicrob Agents Chemother. 2013;57:983–989. doi: 10.1128/aac.01961-12. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Sparrelid E, Ljungman P, Ekelof-Andstrom E, et al. Ribavirin therapy in bone marrow transplant recipients with viral respiratory tract infections. Bone Marrow Transplant. 1997;19:905–908. doi: 10.1038/sj.bmt.1700752. [DOI] [PubMed] [Google Scholar]
- 15.Shah DP, Ghantoji SS, Ariza-Heredia EJ, Shah JN, el Taoum KK, Shah PK, Nesher L, Hosing C, Rondon G, Champlin RE, Chemaly RF. Immunodeficiency scoring index to predict poor outcomes in hematopoietic cell transplant recipients with RSV infections. Blood. 2014;123:3263–3268. doi: 10.1182/blood-2013-12-541359. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Foolad F, Aitken SL, Shigle TL, Prayag A, Ghantoji S, Ariza-Heredia E, Chemaly RF. Oral versus aerosolized ribavirin for the treatment of respiratory syncytial virus infections in hematopoietic cell transplant recipients. Clin Infect Dis. 2019;68:1641–1649. doi: 10.1093/cid/ciy760. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Casey J, Morris K, Narayana M, Nakagaki M, Kennedy GA. Oral ribavirin for treatment of respiratory syncitial virus and parainfluenza 3 virus infections post allogeneic haematopoietic stem cell transplantation. Bone Marrow Transplant. 2013;48:1558–1561. doi: 10.1038/bmt.2013.112. [DOI] [PubMed] [Google Scholar]
- 18.Guzman-Suarez BB, Buckley MW, Gilmore ET, et al. Clinical potential of DAS181 for treatment of parainfluenza-3 infections in transplant recipients. Transpl Infect Dis. 2012;14:427–433. doi: 10.1111/j.1399-3062.2012.00718.x. [DOI] [PubMed] [Google Scholar]
- 19.Moscona A, Porotto M, Palmer S, Tai C, Aschenbrenner L, Triana-Baltzer G, Li QX, Wurtman D, Niewiesk S, Fang F. A recombinant sialidase fusion protein effectively inhibits human parainfluenza viral infection in vitro and in vivo. J Infect Dis. 2010;202:234–241. doi: 10.1086/653621. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Salvatore M, Satlin MJ, Jacobs SE, Jenkins SG, Schuetz AN, Moss RB, van Besien K, Shore T, Soave R. DAS181 for treatment of parainfluenza virus infections in hematopoietic stem cell transplant recipients at a single center. Biol Blood Marrow Transplant. 2016;22:965–970. doi: 10.1016/j.bbmt.2016.02.011. [DOI] [PubMed] [Google Scholar]
- 21.Waghmare A, Wagner T, Andrews R, Smith S, Kuypers J, Boeckh M, Moss R, Englund JA. Successful treatment of parainfluenza virus respiratory tract infection with DAS181 in 4 immunocompromised children. J Pediatric Infect Dis Soc. 2015;4:114–118. doi: 10.1093/jpids/piu039. [DOI] [PMC free article] [PubMed] [Google Scholar]