A retrospective evaluation of mean platelet volume as a discriminating factor in thrombocytopenia of hypoproductive and hyperdestructive aetiologies.
The MPV is a simple, non-invasive and reproducible method available in most healthcare centers, courtesy; the modern hematology cell analyzers.These machines measure the platelet count by impedance method. The data also computes the MPV. This study was conducted to assess and statistically analyze the role of MPV as discriminating factor in thrombocytopenias which involves the bone marrow (decreased platelet production/ hypoproductive) and in cases where the marrow is normal (peripheral destruction of platelets/ hyperdestructive).
MATERIALS AND METHODS: A retrospective study of 100 cases was undertaken in the Clinical Laboratory and Hematology division of Kasturba Hospital, Manipal. The study was conducted after obtaining the approval from the Ethics Committee, Kasturba Hospital, Manipal. The cases included were thrombocytopenias (defined by platelet count < 100 x [10.sup.3]/cu.mm.) selected from the software data on the LH 750 cell analyzer (Beckman-Fullerton) for the month of April 2013. The cases where the bone marrow was performed were also included. The blood samples were collected in ethylene diamine tetra-acetic acid (EDTA) anticoagulant vacutainers. The blood samples were subjected to a complete blood count analysis using LH 750 cell counter (Beckman-Fullerton). This is a five-part differential cell analyzer which gives a platelet count by impedance method. As platelets pass via an aperture by a streamlined flow, an electronic impulse is generated due to the alteration in the current flow between the electrodes. The amplitude of the pulse generated is proportional to the volume (MPV) and the number of pulses gives the platelet count. The reference range for MPV in normal subjects in this analyzer is 7-11fl. All the samples were analyzed within 3 hours of venipuncture to eliminate the possibility of platelet swelling in EDTA. The platelet count and the corresponding MPV of the 100 cases were recorded. The platelet count was confirmed under oil immersion field. Two hematopathologists who were blinded to the clinical diagnosis and MPV reported on the platelet counts. All bone marrow aspirates and biopsies were reported independently.
The thrombocytopenia was categorized into 2 main groups (7): Group A where thrombocytopenia showed a bone marrow disease and Group B where the thrombocytopenia was due to peripheral destruction. The group A yielded 26 cases while the group B had 76 cases.
Statistical analysis: The statistics were carried out using the SPSS software version 16.0 for windows (Chicago, IL, USA). Results were expressed as mean +/- 2 SD along with the range. Student's t test was applied to compare the parameters between groups A and B. P value <0.05 was considered artistically significant. The positive and negative predictive values, odds ratio and confidence intervals were tabulated. The sensitivity and specificity of MPV as predictors of marrow disease were assessed by performing receptor operating characteristic (ROC) curve analysis.
RESULTS: Of the 100 cases studied, bone marrow disease was diagnosed in 26 cases (group A) while 74 cases did not have a marrow disease (group B). Table 1 shows different aetiologies for thrombocytopenia for all the 100 cases.
Table 2 shows the number of cases in group A (with bone marrow disease) along with their mean MPV. Mean MPV suggests the mean of all the individual MPV in the 26 cases in group A. Acute lymphoblastic leukemia constituted the most number of cases, followed by megaloblastic anemia. All the six disease categories had a variable mean MPV with megaloblastic anemia having the highest mean MPV (9.68fl).
Table 3 shows the number of cases in group B (without bone marrow disease) along with their respective mean MPV. It was seen that all categories except malaria had a mean MPV more than 9fl. The mean MPV in cases of bone marrow disease (26 cases) was 8.95fl (SD: 1.07; range: 7.88-10.02 fl). The mean MPV in cases without bone marrow disease (74 cases) was 9.42fl (SD: 1.22; range: 8.22-10.64 fl). The student's t test showed a P value of 0.088; which was not statistically significant.
Table 4 demonstrates the comparison of negative predictive value for bone marrow disease at different MPV threshold levels. The higher the MPV, greater is the discriminant function for excluding bone marrow disease in patients with thrombocytopenia. A MPV of more than 12 fl has a negative predictive value of 100%. It also gradually declined as the MPV threshold decreased. Table 6 shows the comparison of positive predictive value of the MPV for marrow disease at different threshold levels. It was observed that the positive predictive value was variable when compared with different MPV thresholds and showed no particular pattern.
The analysis of ROC curve showed that a cut-off of 9.35 fl yielded a sensitivity of 69% and a specificity of 55% (figure 1)
DISCUSSION: Today's clinical medicine has taken many important strides and physicians are increasingly dependent on rapid laboratory tests to assess the risk of a specific disease entity. These diagnostic algorithms have partially or completely eclipsed conventional methods of diagnosis. Specific examples include Troponin levels in ischemic heart disease (7) and D-dimer assay in hemolytic anemia and venous thromboembolism (8). With reference to cell counters, the modern automated analyzers have aided in providing new parameters which are useful in rapid testing of diseases. MPV has been put to test by researchers in the recent years; yielding consistent results in distinguishing the two types of thrombocytopenia. (4,10,11) However, the wider utility of this factor has yielded variable results. (4,5,12) In the present study, the cases with thrombocytopenia due to a bone marrow disease had a lower mean MPV while the other group without marrow involvement had a higher mean MPV. However, the difference between the groups was statistically not significant.
It was noted in the present study that the cases with leukemias which are associated with marrow suppression had variable mean MPVs. The acute lymphoblastic leukemias and chronic leukemias had a mean MPV less than 9fl. In contrast, the acute myeloid leukemias had a higher mean MPV. The MPV in these cases were noted at the time of marrow diagnosis so that chemotherapy drugsdid not affect the test results. When the negative predictive value for bone marrow disease was analyzed at different MPV threshold levels, it was noted that an increase was in parallel with increasing MPV threshold. But a similar correlation did not exist with positive predictive value. This data hints that the positive predictivity for bone marrow disease by MPV was not reliable. The analysis of sensitivity and specificity of MPV was also not diagnostic as an indicator of marrow disease at a cut-off of 9.35 fl (sensitivity--69% and specificity--55%). Similar results were acknowledged by the studies conducted by Chandra et al (12).
The direction of research to determine the hypoproductive and hyperdestructive thrombocytopenia has veered towards other platelet indices Borkataky et alhave demonstrated that platelet distribution width (PDW) has discriminating property to determine the aetiology of thrombocytopenia. (13) Other researchers such as Niethammer et al have upheld the diagnostic value of platelet histogram maximum rather than MPV to differentiate between idiopathic thrombocytopenic purpura and hypoproductive thrombocytopenia. (14) Ntaios et al have found a combination of MPV and PDW superior to platelet-large cell ratio (P-LCR). (15) The present study is not without its limitations. The sample size was a small one and secondly, we did not analyze the other platelet indices apart from MPV, such as PDW. This was done intently as we wanted to test only a single parameter. Also, P-LCR was not provided by the autoanalyzer. Future research in this regard by binding these indices may lead to more definitive answers. A different approach was adopted by Kurata et al, who assessed reticulated platelets which are newly released from the marrow. (16) By using RNA-binding dyes and flow cytometric analysis, these immature platelets were successful as a discriminating guide to delineate the aetiology of thrombocytopenia. However, this test is expensive, requires extensive quality control measures and is relatively time consuming.
Few disclaimers have to be considered while one interprets MPV in isolation: a spurious increase in MPV contributed by red blood cell fragmentation which can be counted by the analyzer as a giant platelet, a combination of hypoproductive and hyperdestructive thrombocytopenia and splenic sequestration; where large platelets are entrapped in spleen but not released into the circulation. (10,17-18)
CONCLUSION: MPV is easily available in most five part differential counters and may provide a small initial window into the aetiology of thrombocytopenia. But it is limited by insufficient sensitivity and specificity. A bone marrow examination continues to be the gold standard to differentiate the hypoproductive and hyperdestructive thrombocytopenias. A combination of all the platelet indices and new parameters such as reticulated platelets and immature platelet fraction may be the way ahead to predict the cause of thrombocytopenia.
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[1.] Ruchee Khanna
[2.] Deepak Nayak M.
[3.] Chetan Manohar
[4.] Murli Dhar
PARTICULARS OF CONTRIBUTORS:
[1.] Associate Professor, Department of Pathology, Kasturba Medical College, Manipal, Manipal University.
[2.] Assistant Professor, Department of Pathology, Kasturba Medical College, Manipal, Manipal University.
[3.] Professor, Department of Pathology, Kasturba Medical College, Manipal, Manipal University.
[4.] Associate Professor, Department of Statistics, Manipal University.
NAME ADDRESS EMAIL ID OF THE CORRESPONDING AUTHOR:
Dr. Ruchee Khanna, Associate Professor, Department of Pathology, Kasturba Medical College, Manipal, Manipal University.
Date of Submission: 04/11/2013.
Date of Peer Review: 06/11/2013.
Date of Acceptance: 12/11/2013.
Date of Publishing: 19/11/2013
Table 1: Causes of thrombocytopenia in all 100 cases Cause for thrombocytopenia No. of cases Acute Lymphoblastic Leukemia 13 Megaloblastic Anemia 8 Acute Myeloid Leukemia 2 Aplastic Anemia 1 Chronic Lymphoproliferative Disease 1 Chronic Myeloid Leukemia 1 Sepsis 40 Liver disease * 6 Malaria 6 Dengue 14 Idiopathic Thrombocytopenic Purpura 5 Others 3 * without splenomegaly Table 2: Mean MPV in group A (with bone marrow disease) Disease category No. of MPV (fl, mean cases +/- 2sd) Acute Lymphoblastic Leukemia 13 8.44 +/- 0.92 Megaloblastic Anemia 8 9.68 +/- 0.98 Acute Myeloid Leukemia 2 9.50 +/- 1.83 Aplastic Anemia 1 -- Chronic Lymphoproliferative Disease 1 -- Chronic Myeloid Leukemia 1 -- Table 3: Mean MPV in group B (without bone marrow disease) Disease category No. of MPV (fl, mean cases +/- 2sd) Sepsis 40 9.28 +/- 1.17 Liver disease 6 9.98 +/- 2.18 Malaria 6 8.81 +/- 1.04 Dengue 14 9.55 +/- 1.01 Idiopathic 5 10.12 +/- 1.13 Thrombocytopenic Purpura Others 3 9.60 +/- 0.42 Table 4: Comparison of negative predictive value for marrow disease at different MPV threshold levels MPV No. of No. % of NPV threshold cases of pts. pts in (%) (fl) without this marrow group disease >12 2 2 2 100 >11.5 6 5 6 83.3 >11 8 8 8 100 >10.5 15 13 15 86.67 >10 22 19 22 86.36 >9.5 37 29 37 78.37 >9 61 49 61 80.32 >8.5 74 53 74 71.62 >8 84 63 84 75 >7.5 93 70 93 75.26 >7 100 74 100 74 MPV Odd's 95% CI threshold Ratio (fl) Lower Upper >12 -- -- -- >11.5 1.811 0.201 16.272 >11 -- -- -- >10.5 2.557 0.536 12.192 >10 2.648 0.713 9.828 >9.5 1.450 0.558 3.766 >9 2.286 0.921 5.676 >8.5 0.600 0.200 1.802 >8 1.363 0.424 4.379 >7.5 2.282 0.475 10.964 >7 -- -- -- Table 5: Comparison of positive predictive value for bone marrow disease at different MPV threshold levels MPV No. No. of % of PPV Odd's 95% CI threshold of pts. pts (%) Ratio (fl) cases with in marrow this disease group Lower Upper <12 98 26 26 26.53 -- -- -- <11.5 94 25 25 26.59 2.61 0.305 22.313 <11 92 25 25 27.17 1.48 0.383 5.739 <10.5 85 23 23 27.05 2.64 0.713 9.828 <10 78 23 23 29.48 1.45 0.558 3.766 <9.5 63 18 18 28.57 1.84 0.746 4.563 <9 39 13 13 33.33 1.06 0.387 2.932 <8.5 26 7 7 26.92 1.36 0.424 4.379 <8 16 5 5 31.25 2.28 0.475 22.313 <7.5 7 3 3 42.85 -- -- -- <7 0 0 0 -- -- -- --
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|Title Annotation:||ORIGINAL ARTICLE|
|Author:||Khanna, Ruchee; Deepak, Nayak M.; Manohar, Chetan; Dhar, Murli|
|Publication:||Journal of Evolution of Medical and Dental Sciences|
|Article Type:||Clinical report|
|Date:||Nov 25, 2013|
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