A four-year retrospective study was conducted at HKL and HUSM from June 2016 to June 2019. Both study sites were selected as primary centers for diagnosing PCM disease in Malaysia. Patient data were retrieved from the medical records unit and the hematology laboratory's laboratory information system in both hospitals. This study was authorized by the USM Human Research Committee (USM/JEPeM/19040237) and the Medical Research & Ethics Committee (NMRR-18-3904-45526 (IIR)) and complied with the Declaration of Helsinki. Patient medical information was kept confidential, and each patient's records were assigned a unique identical number. In 2021, statistics from the Global Cancer Observatory (GLOBALCAN) demonstrated that PCM is a rare disease in Malaysia. Given its infrequency and limited occurrence, we calculated the sample size using the guidelines outlined in Conroy (2015)15, which suggest that a suitable maximum sample size is typically 10% of the total identified cases. However, we recruited a larger sample size in this study (n=78) to conduct a retrospective study in two tertiary care centers. Newly diagnosed PCM cases were defined based on the updated Classification of Tumors of Hematopoietic and Lymphoid Tissue 201716. PCM cases were diagnosed with the existence of a clonal bone marrow plasma cell percentage equal to or greater than 10%, or a biopsy-proven plasmacytoma, and associated with one or more of the myeloma-defining events genuinely diagnosed in HUSM and HKL. The inclusion criteria encompassed all cases that had been diagnosed with PCM, as determined by the above criteria. Cases in which immunophenotyping assays were not performed, cases referred to HKL and HUSM for outsourced PCM, and relapsed cases were excluded.

BM aspirate samples were collected in EDTA anticoagulant tubes and processed within 12 hours post-collection. The samples were analyzed with the six-color flow cytometer BD FACSCanto II (BD Biosciences, Erembodegem, Belgium) using the myeloma panel antibodies. The gating markers (CD38, CD138, CD45), aberrant markers (CD19, CD56, CD117), and clonality evaluation (cytoplasmic and light chain Ig) were utilized. Briefly, 100 μl of count-adjusted anticoagulated bone marrow samples were treated with monoclonal antibodies in the dark at room temperature for 15 minutes. Then, the red blood cells were lysed and washed twice with PBS. The supernatant was discarded, and the cell pellet was resuspended in PBS. After discarding the supernatant, the cell pellet was then resuspended in PBS. Analyzed stained cells were swiftly identified with the BD FACSCanto II flow cytometer. Non-binding mouse isotype antibodies were utilized as a control experiment.

For the gating strategy, singlet exclusion was acquired by gating on forward scatter area (FSC-A) vs. forward scatter height (FSC-H) to exclude doublets. A live cell gate was used to gate on a live cell population and excluding debris and dead cells based on forward scatter (FSC) and side scatter (SSC) properties. A CD38 vs. CD138 plot was created by plotting CD38 (x-axis) vs. CD138 (y-axis) to identify PCM cells, followed by CD45 exclusion to exclude any remaining contaminating cells by gating out CD45-positive cells, as PCM cells are typically CD45-negative.

Besides, the aberrant marker analysis was detected by CD19, CD56, and CD117 expression via creating individual histograms or scatter plots for each aberrant marker to identify the presence or absence of these markers in the PCM cell population. The PCM cell clonality evaluation was assessed by Ig light chain analysis, in which cytoplasmic and surface immunoglobulin light chain stains were used to evaluate the clonality of the PCM cells. Then, histograms or scatter plots for each light chain (kappa and lambda) were created to assess the expression pattern. FACSDivaTM software was used to generate summary statistics for each population and marker. The graphs and plots were created for better visualization of the results. Internal controls of positive and negative controls were included to validate the staining and gating strategy. Compensation controls were used to ensure proper compensation by using single-stained controls for each fluorochrome. Neoplastic plasma cells were defined as CD38-positive and CD138-positive light-chain-restricted. Cells were considered positive when more than 20% of cells expressed the antigen profile of that marker. The percentage of positive cells was provided by the percentage of events above the cursor defined on the negative control. The cells were acquired by flow cytometer with the total acquisition events being about 20,000 to 30,000 nucleated cells for diagnosis assessment.

An additional parameter was used to examine the relationship between the immunophenotyping profile, prognostic variables, and clinical stages. Demographics (age, gender, and ethnicity), hematological parameters (FBC, ESR, and bone marrow plasma cell percentage), biochemical parameters (serum albumin, B2M, calcium, LDH, creatinine, paraprotein, and total protein), and molecular and cytogenetic assessment were examined. The three clinical stages including Stage I, Stage II, and Stage III were defined by the Multiple Myeloma ISS.

The statistical analysis was performed using the SPSS software version 26.0. Descriptive statistics were utilized to present the demographic characteristics, and the mean value along with the standard deviation (mean±SD) was used to express the numerical data, whereas the frequency and percentage (%) were employed to express the categorical data. The study examined the correlation between the manifestation of immunophenotypic markers and their hematological, biochemical, and cytogenetic anomalies, along with clinical stages via the Pearson Chi-square/Fisher Exact test. A p-value below 0.05 was used to determine statistical significance.

A total of 78 newly diagnosed PCM cases were recruited from HKL and HUSM between June 2016 and June 2019. Males (56.4%) outnumbered females (43.6%), resulting in a male-to-female ratio of 1.29:1. Malays constituted 73.6% of the cases, followed by Chinese (12.8%) and Indian (11.5%) ethnicities. The average age of PCM cases was 60 years, with the highest prevalence in the 61-70 age range.

Most of the study cases (73.1%) were associated with a normal WBC count (4-11x10⁹/L). A total of 10.3% and 16.7% of cases had leucopenia and leukocytosis, respectively. The study demonstrated that only 10.3% of cases had Hb >12.0, while 65.4% had anemia (Hb <10 g/dL), and 24.4% had mild to severe anemia (10.0 – 11.9 g/dL). Additionally, 7.7% and 16.7% of cases had thrombocytopenia (platelet count <100 x10⁹/L and 100 – 149 x10⁹/L, respectively), whereas 75.6% had normal platelet counts (>150 x10⁹/L). Our study found that 93.6% of cases had a bone marrow plasma cell percentage >10%, whereas 6.4% had <10%. More than half of the cases studied (63.3%) had elevated ESR (>100 mm/hour).

More than half of the cases (n=54, 69.2%) were successfully staged using the Multiple Myeloma ISS. Most cases were staged as Stage III (39.7%), followed by Stages II (24.4%) and Stage I (5.1%). Due to the lack of serum B2M, 24 cases (30.8%) were classified as unknown stages. Table 1 shows the demographics, MM ISS-based clinical staging, and hematological data of newly diagnosed PCM patients.

Table 1

Characteristics	n (%)
Gender
Male	44 (56.4)
Female	34 (43.6)
Age Group
<30	1 (1.3)
31-40	2 (2.6)
41-50	10 (12.8)
51-60	28 (35.9)
61-70	29 (37.2)
>70	8 (10.3)
Staging, ISS
I	4 (5.1)
II	19 (24.4)
III	31 (39.7)
Unknown	24 (30.8)
Parameters
White Blood Cell (x109/L) (n=78)
< 4.0	8 (10.3)
4.0- 11.0	57 (73.1)
≥ 11.1	13 (16.7)
Hemoglobin (gm/dL) (n=78)
<10.0	51 (65.4)
10.0-11.9	19 (24.4)
≥12.0	8 (10.3)
Platelet (x 109/L) (n=78)
<100	6 (7.7)
100-149	13 (16.7)
≥150	59 (75.6)
Bone marrow plasma cell % (n=78)
<10	5 (6.4)
10-59	47 (60.3)
≥60	26 (33.3)
*ESR (mm/hour) (n=49)
≤50	10 (20.4)
51-100	8 (16.3)
>100	31 (63.3)

Table 2

Parameters	n (%)
Albumin (gm/l)
< 35	52 (66.7)
≥ 35	26 (33.3)
Corrected Calcium (mmol/L)
> 2.75 ≤ 2.75	50 (64.1) 28 (35.9)
LDH (U/L)
< 300	26 (33.3)
≥ 300	52 (66.7)
Creatinine (μmol/L)
< 177	20 (25.6)
≥ 177	58 (74.4)
Total protein (g/L)
< 60	5 (6.4)
61 – 89	29 (37.2)
≥ 90	44 (56.4)
Serum paraprotein (g/L)
< 30	24 (30.8)
≥ 30	54 (69.2)
Serum B2M (mg/L)
<3.5	5 (8.9)
3.5-5.4	16 (28.6)
≥5.5	35 (62.5)

Table 4

Parameters	CD19
		Negative n (%)	Positive n (%)	χ2 (df)*	p-value
White cell count (x109/L)	78			-	0.839b
< 4.0		5 (62.5)	3 (37.5)
4.0 – 11.0		41 (71.9)	16 (28.1)
≥ 11.1		10 (76.9)	3 (23.1)
Hemoglobin (gm/dl)	78			2.534(2)	0.282a
< 10.0		39 (76.5)	12 (23.5)
10.0 – 11.9		13 (68.4)	6 (31.6)
≥ 12.0		4 (50.0)	4 (50.0)
Platelet (x109/L)	78			-	0.832b
< 100		4 (66.7)	2 (33.3)
100 – 149		9 (69.2)	4 (30.8)
≥ 150		43 (72.9)	6 (27.1)
Bone marrow plasma cell percentage (%)	78			-	0.172b
< 10		3 (60.0)	2 (40.0)
10 - 59		31 (66.0)	16 (34.0)
≥ 60		22 (84.6)	4 (15.4)
Albumin (g/dL)	78			0.791(1)	0.374a
< 35		39 (75.0)	13(25.0)
≥ 35		17 (65.4)	9 (34.6)
Corrected calcium (mmol/L)	78			0.003(1)	0.957a
> 2.75		36 (72.0)	14 (28.0)
≤ 2.75		20 (71.4)	8 (28.6)
LDH (U/L)	78			3.830(1)	0.050a
< 300		15 (57.7)	11 (42.3)
≥ 300		41 (78.8)	11 (21.2)
Creatinine (µmol/L)	78			4.402(1)	0.036a
< 177		18 (90.0)	2 (10.0)
≥ 177		38 (65.5)	20 (34.5)
Serum total protein (g/L)	78			-	0.104b
< 60		2 (40.0)	3 (60.0)
61 – 89		19 (65.5)	10 (34.5)
≥ 90		35 (79.5)	9 (20.5)
Serum paraprotein (g/L)	78			0.016(1)	0.900a
< 30		17 (70.8)	7 (29.2)
≥ 30		39 (72.2)	15 (27.8)
Serum B2M (mg/L)	56			2.667(2)	0.359a
<3.5		5 (100.0)	0 (0.0)
3.5-5.4		11 (64.7)	6 (35.3)
≥5.5		26 (76.5)	8 (23.5)
Types of light chain	78			-	0.717b
Kappa		35 (74.5)	12 (25.5)
Lambda		20 (66.7)	10 (33.3)
Inconclusive		1 (100.0)	0 (0.0)
Cytogenic abnormalities	39			0.253(1)	0.719a
Present		10 (76.9)	3 (23.1)
Absent		18 (69.2)	8 (30.8)

^aPearson Chi-square test was applied; ^bFisher Exact test was applied; ^df* degree of freedom

Table 5

Immunophenotypic markers	Staging			χ2 (df)*	p-value
	I (n/%)	II (n/%)	III (n/%)
CD138				-	-
Negative	0 (0.0)	0 (0.0)	0 (0.0)
Positive	4 (7.4)	19 (35.2)	31 (57.4)
CD38				-	-
Negative	0 (0.0)	0 (0.0)	0 (0.0)
Positive	4 (7.4)	19 (35.2)	31 (57.4)
CD56				2.430(2)	0.311a
Negative	2 (18.2)	2 (18.2)	6 (54.5)
Positive	2 (4.7)	16 (37.2)	25 (58.1)
CD117				1.963(2)	0.432a
Negative	0 (0.0)	8 (38.1)	13 (61.9)
Positive	1 (8.3)	5 (41.7)	6 (50.0)
CD45				2.859(2)	0.210a
Negative	2 (5.1)	12 (30.8)	25 (64.1)
Positive	2 (13.3)	7 (46.7)	6 (40.0)
CD19				1.557(2)	0.703a
Negative	4 (10.0)	14 (35.0)	22 (55.0)
Positive	0 (0.0)	5 (35.7)	9 (64.3)

^aPearson Chi-square test was applied, ^bFisher Exact test was applied, df* degree of freedom

All biochemical markers of cases showed an increasing trend, except for albumin. A proportion of 66.7% of cases had hypoalbuminemia (serum albumin <35g/l), high LDH (> 300U/L), high calcium (>2.75mmol/L), and substantially increased creatinine (>177 μmol/L). Hyperproteinemia (>90g/L) was seen in 56.4% of patients, while 6.4% had hypoproteinemia (60g/L). Serum total protein was normal in 37.2% of cases. Additionally, 69.2% of cases were associated with serum paraprotein levels more than 30 g/L, whereas 30.8% had values below 30g/L. Our study revealed that 62.5% of cases had a higher blood B2M level (>5.5mg/L), whereas 28.6% and 8.9% had a lower level (3.5-5.5mg/L and <3.5mg/L, respectively), as illustrated in Table 2.

Figure 1

Flow cytometry was used to assess immunophenotypic marker positivity in 78 cases. Gated at CD138 and CD38 demonstrated that all patients' plasma cells were positive, whereas other immunophenotypic markers expressed differently. Neoplastic plasma cells expressed CD19, CD45, CD56, and CD117 at 28.2%, 23.1%, 83.3%, and 25.6%, respectively. Each case had abnormal marker expression, and 60.3% had kappa light chain restriction, and 38.5% had lambda light chain restriction, indicating clonality, as illustrated in Figure 1. In our study, only one case possessed inconclusive light chain expression.

The cytogenetic anomalies revealed a total of 38 cases completed standard cytogenetic testing, and the status for 40 cases was unknown, perhaps owing to metaphase acquisition issues or unavailability of results from medical records. Table 3 shows the results of cytogenetic abnormalities and their types in our PCM cases. A total of 6 out of 13 cases had hypodiploidy, representing the most common cytogenetic abnormality. Specifically, out of 13 (16.7%) of 38 cases had aberrant cytogenetic abnormalities, whereas 25 (32%) had normal or no abnormalities identified, as shown in Table 3.

Several limitations arose during this study. First, the sample size was small, with only a few newly diagnosed PCM cases at both recruitment sites, HKL and HUSM, from June 2016 to June 2019. Moreover, most newly identified PCM cases at HKL were referrals from other hospitals and were thus excluded from this study. Therefore, interpreting the findings with caution is crucial, as they may not accurately reflect the entire PCM population in Malaysia. We also found that many cases could not achieve complete cytogenetic results due to inadequate metaphase quality, and some cases lacked CD117 results because the reagents were unavailable at HKL during the study.

To improve the study's sample size and robustness, it is recommended to include additional centers with newly diagnosed PCM patients. Utilizing molecular techniques, such as incorporating a Fluorescence in situ hybridization (FISH) panel in all PCM patients, is highly recommended for testing underlying cytogenetic and molecular abnormalities due to its enhanced sensitivity and specificity. Moreover, conducting more extensive studies with a larger number of PCM patients to assess the impact of various immunophenotypic markers expressed by clonal plasma cells on patient outcomes and genetic abnormalities could be beneficial.