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| ORIGINAL CONTRIBUTION - CLINICS IN HEMATOLOGY |
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| Year : 2016 | Volume
: 3
| Issue : 3 | Page : 125-130 |
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Role of soluble transferrin receptor and soluble transferrin receptor index in diagnosing iron deficiency anemia in patients with chronic kidney disease
Dipendra Kumar Gupta1, Rajeev Krishna Choudhary2, Monica Sharma1, Sumita Saluja1, Bhupender Gupta2
1 Department of Hematology, Vardhman Mahavir Medical College and Safdarjung Hospital, New Delhi, India
2 Department of Medicine, Vardhman Mahavir Medical College and Safdarjung Hospital, New Delhi, India
| Date of Web Publication | 27-Feb-2017 |
Correspondence Address:
Dr. Dipendra Kumar Gupta
Department of Hematology, Vardhman Mahavir Medical College and Safdarjung Hospital, New Delhi
India
 Source of Support: None, Conflict of Interest: None  | Check |
DOI: 10.4103/2349-0977.201006
Background: Approximately 25–38% of chronic kidney disease (CKD) patients with anemia suffer absolute or functional iron deficiency. This deficiency is estimated and monitored primarily through two iron indices, viz., transferrin saturation (TSAT) and serum ferritin. However, both these parameters suffer from several lacunae and search continues to establish more true measures. This study enquires into the role of soluble transferrin receptors (sTfR) and ratio of sTfR and log ferritin index (sTfR index) as potential measures of the true iron status in patients. Material and Methods: This prospective cross-sectional study comprised a total of 126 CKD patients with anemia on erythropoietin (EPO) undergoing hemodialysis (HD). Of these 126 patients, 55 had iron deficiency anemia (IDA). Estimations of serum iron, TSAT, serum ferritin, and sTfR and sTfR, indices were performed in each patient. Bone marrow aspiration (BMA) was carried out to determine cellularity, cytomorphology, and myeloid: erythroid (M/E) ratio, and was stained with Prussian blue stain. The results of the bone marrow iron status were taken as the gold standard. Subsequently, receiver operating characteristic (ROC) curve analysis was carried out to assess the discriminative power of the sTfR and sTfR indices for evaluation of iron status in patients with CKD. Results: The cut-off value of sTfR index at its maximum sensitivity (71.8%) and specificity (62%) was found to be 1.39, whereas that of sTfR at its maximum sensitivity (63.6%) and specificity (64.8%) was 3.00. Statistically significant correlations were found between sTfR index (Pearson correlation (r) = –0.379) and serum iron (r = –0.38; P < 0.01), TSAT (r = –0.31; P < 0.01), and serum ferritin (r = –0.399; P < 0.01). sTfR was found to correlate significantly (r = –0.445) with serum iron (P < 0.01), TSAT (r = –0.365; P < 0.01), and hemoglobin (r = –0.179; P = 0.04) but not with serum ferritin (r = 0.12; P = 0.153). Conclusion: sTfR and sTfR index values are useful tools for assessment of iron status in patients with CKD, however, they are at best complementary to the existing indices of serum ferritin and TSAT. Between sTfR and sTfR index, the latter has a greater discriminating power. Keywords: Chronic kidney disease, erythropoietin, hemodialysis, iron deficiency anemia, ratio of soluble transferrin receptor and log of ferritin, soluble transferrin receptor
How to cite this article:
Gupta DK, Choudhary RK, Sharma M, Saluja S, Gupta B. Role of soluble transferrin receptor and soluble transferrin receptor index in diagnosing iron deficiency anemia in patients with chronic kidney disease. Astrocyte 2016;3:125-30 |
How to cite this URL:
Gupta DK, Choudhary RK, Sharma M, Saluja S, Gupta B. Role of soluble transferrin receptor and soluble transferrin receptor index in diagnosing iron deficiency anemia in patients with chronic kidney disease. Astrocyte [serial online] 2016 [cited 2023 Mar 29];3:125-30. Available from: http://www.astrocyte.in/text.asp?2016/3/3/125/201006 |
| Introduction | |  |
Of CKD patients, approximately 25–38% are affected with anemia and suffer with absolute or functional iron deficiency (ID).[1] A multifactorial process, this iron deficiency may stem out of (a) increased iron losses due to chronic bleeding from uremia-associated platelet dysfunction, frequent phlebotomy, and blood trapping in the dialysis apparatus; (b) impaired dietary iron absorption; and (c) impaired iron release from body stores stocked in the reticuloendothelial cells. While the first two pathophysiologic processes result in a true iron deficiency, the third causes a functional iron deficiency.
Until now, the definition of absolute iron deficiency has primarily rested on two indices – TSAT, which is a measure of circulating iron and serum ferritin, which is a marker of body iron stores.[2] However, in CKD, these indices are not quite consistent.[3] Irrespective of body iron stores, TSAT drops or increases in CKD. At the same time, serum ferritin, an acute phase reactant, despite the depletion of iron stores, may be normal or high.[4]
In this confounding setting, the true measure of absolute iron deficiency is a bone marrow aspiration. However, being an invasive test, it is best substituted by a reliable noninvasive laboratory test. In the recent years, two new indices have evoked interest – (i) sTfR and (ii) sTfR index.[5],[6]
The sTfR relates to transferrin receptors (TfR), a homodimeric type II cell membrane protein.[5] When TfR undergoes proteolysis, sTfR is one of the many fragments released into the circulation. This sTfR circulates in the blood complexed to ferritin.[7],[8] Studies have demonstrated that to comply with an increased iron demand for erythropoiesis in IDA, the synthesis of TfR on erythroid precursors increases, such that the cells can compete for iron more efficiently. This causes an elevation in the sTfR values. This increase in sTfR occurs rather early in IDA and is manifest during the subclinical state itself.[9],[10],[11],[12] On the other hand, the sTfR index is a mathematical construct and is calculated as the ratio of sTfR to the logarithmic transformation of ferritin level.[6]
This study explores the significance sTfR and sTfR index in estimation of IDA in CKD patients.
| Materials and Methods | | |
This nonrandomized, observational, cross-sectional study carried out at a tertiary care public teaching hospital between 2012 and 2013 comprised 126 CKD patients aged ≥12 years with anemia undergoing HD and on EPO. These patients were categorized into stages 0–5 of CKD; whereas anemia was diagnosed as per the WHO guidelines. Patients with primary bone marrow disorder, hepatocellular damage (aspartate aminotransferase >45 U/L, alanine aminotransferase >60 U/L), malignancy, and infections were excluded.
Venous blood samples were drawn in each study participant to evaluate the complete blood count (CBC), serum iron, total iron binding capacity (TIBC), TSAT, serum ferritin, and sTfR. While Sysmex SS300 system was used to determine the CBC, dipyridyl method with colorimetric analysis was used for the estimation of serum iron and TSAT; Beckman Coulter ® Access 2 immunoassay method was employed for the estimation of sTfR and serum ferritin. Concurrently, sTfR index was calculated as a ratio of sTfR to the logarithm ferritin level.
BMA was carried out to determine cellularity, cytomorphology, and M/E ratio, and was stained with Prussian blue stain to grade marrow hemosiderin stores from 0 to 6+ [Table 1]. The results of the bone marrow iron status constituted the gold standard.
The results were statistically analyzed. sTfR was compared with the gold standard test i.e., bone marrow iron stores for sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). Receiver operating characteristic (ROC) curves were plotted, and the area under the curve (AUC) was calculated to assess the discriminating power of sTfR and sTfR index as tools to evaluate the iron status of CKD patients. The optimal cut-off value of sTfR was worked out by the ROC curve and was compared with the previous optimum cut-off point cited in the literature. Analyses of correlation of each parameter were performed with Pearson's correlation coefficient (r). The test results were expressed by the correlation coefficient (r) and level of significance (P), with the level of statistical significance being P ≤ 0.05.
| Results | | |
Of the 126 patients, 76 (60.3%) were males and 50 (43.6%) females. The age of patients ranged 15–78 years, and the mean age was 38.63 ± 15.29 years. Eighty-eight (70%) patients had diabetes, while 38 (30%) were nondiabetic. All patients were on HD with a mean duration of dialysis of 17.8 ± 15.7 months. On CKD staging, 56 (44%) were in stage 5, 39 (31%) in stage 4, and 31 (25%) in stage 3. On the BMA iron staining, 55 (43.6%) patients had IDA, while 71 (56.3%) did not.
The mean hemoglobin (Hb) of the population was 7.81 ± 1.7 g/dL. The mean Hb in IDA was 7.33 ± 1.65 g/dL, whereas in the non-IDA group, it was 7.56 ± 1.47 g/dL in patients with BMA iron score of 1; and 8.93 ± 1.57 g/dL in non-IDA patients with BMA iron score 2 + and 3+ [Table 2] and [Table 3]. | Table 2: Biochemical and hematological parameters in the study population (n=126)
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 | Table 3: Correlation of Demographic, Biochemical, and Hematological Parameters with wBone Marrow Iron Stores in the Study Population (n=126)
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The mean sTfR was 3 ± 0.99 µg/mL. While the mean sTfR in IDA was 3.28 ± 1.01 µg/mL, that in non-IDA with BMA score 1 + was 2.84 ± 0.66 µg/mL and with BMA score 2 + and 3 + was 2.70 ± 1.19 µg/mL [Table 3].
In comparison, the mean sTfR index was 1.36 ± 0.57. While the mean sTfR index in IDA was 1.57 ± 0.69, that in non-IDA with BMA score 1 + was 1.27 ± 0.33 and with BMA score 2 + and 3 + 1.11 ± 0.44 [Table 3].
The obtained results were plotted in a ROC curve [Figure 1] and [Figure 2]. sTfR index was found to have the largest AUC (AUC 0.682; 95% CI 0.584–0.779). This, in turn, was followed by TSAT (AUC 0.658, 95% CI 0.563–0.752), S. Ferritin (AUC 0.655, 95% CI 0.559–0.751), sTfR (AUC 0.651, 95% CI 0.552–0.750), and TIBC (AUC 0.636, 95% CI 0.536–0.737). | Figure 1: ROC curves of sTfR, sTfR index, TIBC, and MCHC in the study population.
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 | Figure 2: ROC curves of S. Ferritin, TSAT, S. Iron, MCV, and MCH in the study population.
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In comparison, MCV (AUC 0.492, 95% CI 0.389–0.595), MCHC (AUC 0.531, 95% CI 0.430–0.632), MCH (AUC 0.552, 95% CI 0.450–0.654), and S. Iron (AUC 0.609, 95% CI 0.510–0.709) were found to have a far smaller AUC.
The cut-off value of sTfR at its maximum sensitivity of 63.6% and specificity of 64.8% was 3 with a PPV of 59% and NPV of 69%. The cut-off value of S. Ferritin at its maximum sensitivity (67.3%) and specificity (67.6%) was 195 with a PPV of 27% and NPV of 38%. The cut-off value of sTfR index at its maximum sensitivity (71.8%) and specificity (62%) was 1.39 with a PPV of 62% and NPV of 70%. The cut-off value of TSAT at its maximum sensitivity (61.8%) and specificity (62%) was 28.5 with a PPV of 32% and NPV of 44%. The cut-off value of TIBC with its maximum sensitivity (52.7%) and specificity (67.6%) was 272.5 with a PPV of 59% and NPV of 69%.
A statistically significant correlation (r = –0.445) was observed between sTfR and S. Iron (P < 0.01) [Table 4]; sTfR and TSAT (r = –0.365; P < 0.01) and sTfR and hemoglobin (r = –0.179; P = 0.04).
Likewise, a statistically significant correlation was found between sTfR index and S. Iron (r = –0.38; P < 0.01), TSAT (r = –0.31; P < 0.01), and S. Ferritin (r = –0.40; P < 0.01) [Table 5]. | Table 5: Correlation of sTfR index with S. Iron, TSAT and S. Ferritin (n=126)
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No significant correlation was observed between serum iron values and TIBC (r = –0.09; P = 0.316). However, a significant correlation was observed between S. Iron and TSAT (r = 0.82; P < 0.01) [Table 6].
Likewise, no significant correlation was found between TIBC and serum ferritin (r = –0.072; P = 0.423) [Table 7].
| Discussion | | |
Anemia affects 60–80% of patients with CKD and carries a considerable prognostic significance.[1] It is associated with reduction in the quality of life, and is a significant risk factor for an early death. This anemia is multifactorial and is primarily caused by insufficient production of erythropoietin in the diseased kidneys. However, a number of other culpable factors including iron deficiency, chronic inflammation, hyperparathyroidism, and blood loss all contribute to anemia in these patients.[13] A true, early, and accurate identification of anemia and its underlying pathophysiologic processes is, therefore, central to its effective clinical management and promoting improved survival rates. For instance, in patients, where the erythropoietin deficit is compounded by a concomitant iron deficit, treatment singly with recombinant human erythropoietin shall be non-responsive.[14]
This landscape of anemia being compounded by iron deficit in CKD patients is rather common and occurs in approximately 25–38% CKD patients with anemia. In these patients, there is a dire need to identify the iron deficit–be it absolute or functional. Determining this deficit in CKD patients is, however, rather challenging since the currently acceptable markers, i.e., TSAT and serum ferritin have been found to be fallible.[3] Irrespective of body iron stores, TSAT drops in CKD. Concurrently, serum ferritin, an acute phase reactant, despite the depletion of iron stores, may present itself as normal or high.[4]
Therefore, there is a need to recognize possible new markers, and, at the same time, continuously monitor the benefits and limitations of the older markers, such that better, more effective tools can be identified which can determine the iron stores of the body.
This study explored into the significance of two hitherto new and less used indices: sTfR and sTfR index. The study found that the mean sTfR values in patients with IDA (bone marrow iron score 0) were significantly higher than that in patients of the non-IDA group (P = 0.004). This indicates that sTfR values can faithfully reflect iron deficit. Although several studies have demonstrated that a deficit of erythropoietin in CKD patients can raise sTfR values,[15] in the present study, this effect stood well negated since all 126 patients were receiving erythropoietin therapy. It is, therefore, fair to conclude that iron deficit in CKD patients with IDA, even singly, acts as an impetus for increasing the sTfR values and can be held useful as an independent tool to identify ID. However, large multicentre studies need to be conducted to determine this significance, since till date, even the mean sTfR values in the Indian population remain unidentified.
The significance of sTfR index in the study was even greater. The sTfR index in the iron depleted group (bone marrow iron score 0) was found to be 1.5 ± 0.69, which was significantly higher (P = 0.0003) than that in the non-IDA CKD patients (sTfR index 1.19). This strength of sTfR index is reflected in it carrying the largest AUC, sensitivity (71.8%), specificity (62%), PPV (62%) and NPV (70%) among the various parameters investigated in the study. This virtue of sTfR index is possibly related to two factors. The anemia in CKD is partly related to inflammatory activity, which also tends to cause a rise in serum ferritin.[4] This phenomenon contradicts the drop in serum ferritin that should expectedly occur in IDA. However, when a sTfR index is calculated, it negates this fallacy since sTfR, per se, is not affected by the inflammatory activity; and the ratio of sTfR with log of ferritin thereby because a truer representative of ID outmaneuvering the limitation of serum ferritin.
The study also evaluated serum ferritin and TSAT for their usefulness in the diagnosis of ID. Both were found to be reliable: serum ferritin ≤195µg/l and TSAT ≤28.5% correlated significantly with IDA in the study group. This leads us to cautiously assert that serum ferritin ≤195µg/l can be taken as a diagnostic marker of absolute iron deficiency and can be the basis for initiating iron therapy in patients of CKD on hemodialysis and EPO therapy. Furthermore, although serum ferritin outscores sTfR in its sensitivity (67.3% vs. 63.6%) and specificity (67.6% vs. 64.8%) significantly, it pales in comparison with sTfR in relation to its PPV (27% vs. 59%) and NPV (38% vs. 69%). As regards TSAT, its AUC (0.658) was found to be superior to S. Ferritin (AUC = 0.655), and sTfR (AUC = 0.651), and inferior to the sTfR index (0.682). Its sensitivity was 61.8%, specificity 62%, PPV 32%, and NPV 44%.
The study records a significant correlation between sTfR and serum iron (r = –0.445; P < 0.01); sTfR and TSAT (r = –0.365; P < 0.01); and sTfR and hemoglobin (r = –0.179; P = 0.04). Likewise, a significant correlation was found to exist between sTfR index and serum iron (r = –0.38; P < 0.01), TSAT (r = –0.31; P < 0.01), and serum ferritin (r = –0.40; P < 0.01); and also between serum iron and TSAT (r = 0.82; P < 0.01). On the contrary, however, no significant correlation was found between serum iron and TIBC (r = –0.09; P = 0.316) and between TIBC and serum ferritin (r = –0.072; P = 0.423).
| Conclusion | | |
Even though no single parameter is specific and sensitive enough to reliably assess the iron status in CKD patients, both sTfR and sTfR index values are useful tools. Together with the existing indices of serum ferritin and TSAT, they can play a valuable complementary role. Between sTfR and sTfR index–the two relatively new and less used indices–the latter has a greater discriminating power to define body's iron status in CKD patients.
Financial support and sponsorship
Nil.
Conflicts of interest
There are no conflicts of interest.
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[Figure 1], [Figure 2]
[Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 6], [Table 7]
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