Vitamin D status in breast cancer cases following chemotherapy: A pre and post observational study in a tertiary hospital in Yogyakarta, Indonesia.

OBJECTIVES: To observe pre- and post-treatment vitamin D level and its association with treatment and concomitant factors in breast cancer patients treated with chemotherapy.
METHODS: We performed a pre-post observational analysis that nested in an ongoing prospective cohort study of breast cancer patients at Dr. Sardjito General Hospital, Yogyakarta, Indonesia. 136 subjects were recruited from the main study. Information on subjects' socio-demographic characteristics clinical status, and tumour profile was assessed at baseline. Number of chemotherapy cycles and chemotherapy-induced nausea vomiting (CINV) were also recorded. Vitamin D concentration was measured using ELISA methods at baseline and post-treatment. Vitamin D level of <20 ng/ml and <12 ng/ml were defined as deficiency and severe deficiency. Correlation between socio-demographic and clinical profile with baseline vitamin D was tested using Spearman correlation. Paired t-test was used to evaluate changes in post-treatment vitamin D concentration. The odds ratio for a subject to experience post-treatment vitamin D decrease was assessed based on number of chemotherapy cycles and CINV severity.
RESULTS: The mean vitamin D level before chemotherapy was very low (8.80±3.64 ng/ml) in the whole panel. Higher AST level were associated with lower vitamin D level at baseline (r = -0.188, p = 0.028). Severe deficiency was found in 82.4% subjects at baseline and the rate increased to 89.0% after chemotherapy. Eighty-five cases showed a decrease level whereas 51 showed a slight improvement. Overall, a significant decrease of the vitamin D level was observed after chemotherapy (median change 3.13±4.03 ng/ml, p <0.001). Subjects who received >6 cycles of chemotherapy were less likely to experience a decreased level of post-treatment vitamin D (OR = 0.436, 95% CI = 0.196-0.968, p = 0.039).
CONCLUSIONS: Indonesian breast cancer patients showed pre-existing severe vitamin D deficiency and deterioration of vitamin D after chemotherapy. Future research is needed to explore its implication towards patients' survival in the local setting. Evidence-based approach also needs to be taken to address this modifiable condition, including increasing awareness of the importance of maintaining vitamin D sufficiency both in patients and the general population.

Introduction

Breast cancer remains the most frequent cancer in women with 2.1 million new cases recorded in 2018 [1]. It is also the most frequent cancer and the second-highest cause of cancer-related mortality in Indonesia with 44.0 incidences and 15.3 death per 100.000 population [2]. Cases in Indonesia were more often present in younger patients and diagnosed at an advanced stage (IIIA-C and IV), contributing to the low 5-year survival rate (51.1%) [3-5].

New evidence has proven to be associated with breast cancer survival, including vitamin D. Poor vitamin D concentration was associated with poor breast cancer prognostic characteristics as lower vitamin D concentration was found in patients with poor differentiation, stage 4, and negative ER expression [6]. On the contrary, maintained vitamin D concentration was associated with a better clinical outcome due to its ability to inhibit abnormal cell growth and differentiation and to regulate local vitamin D synthesis in breast tissue [7-9]. Supporting evidence also observed that ≥23.6 ng/ml pre-diagnostic vitamin D concentration on newly diagnosed patients has 59% lower risk of breast cancer-related mortality Moreover, improvement of vitamin D was also correlated with lower risk of fatality (HR = 0,57, 95% CI = 0,43–0,75) [10].

Studies have observed that vitamin D levels might deteriorate due to chemotherapy, the treatment modality widely used in Indonesia [11, 12]. Chemotherapy regimens such as anthracycline, cyclophosphamide, and taxane are known to cause gonad toxicity and resting oocytes destruction, reducing estrogen expression and increasing vitamin D catabolism [13, 14]. Additionally, concomitant effects of chemotherapy were associated with reduced sun exposure, physical activity, and diet limitation, further adding to the low vitamin D level [15, 16].

To date, observation of vitamin D concentration in the Indonesian population was focusing on the population at risks such as children, adolescents, and pregnant women [17-19]. Although observation of vitamin D concentration in postmenopausal breast cancer patients has been done previously in Surabaya, Indonesia [20], the association between vitamin D level and breast cancer characteristics remains unexplored. No study evaluating post-treatment vitamin D changes has ever been done. Herein, we are aiming to observe vitamin D changes in Indonesian breast cancer patients treated with chemotherapy and its association with chemotherapy and concomitant factor.

Methods

Study design and participants

We performed a nested pre-post observational study assessing 25(OH)D changes on primary breast cancer patients registered in a prospective ongoing cohort. The main study analysed the risk of chemotherapy side effects and its effect on survival and quality of life in breast cancer patients. Subjects of the main study were histologically confirmed female breast cancer patients aged ≥18 years who were chemotherapy naïve and receiving their first chemotherapy in the Haematology and Medical Oncology Division, “Tulip”/Integrated Cancer Clinic, Dr. Sardjito General Hospital, Yogyakarta, Indonesia, from 2018–2022. No subjects in the cohort were in a terminal condition or with severe congestive heart failure. Among subjects enrolled in the main cohort, we only included those who have received their last chemotherapy cycle and completed post-treatment follow-up into the present study. Subjects who have incomplete blood sample were excluded. The main study was approved by the Medical and Health Research Ethics Committee of the Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada/Dr. Sardjito Hospital (reference number: KE/FK/0417/EC/2018) and was amended for the study reported in this manuscript (amendment approval with reference number: KE/FK/0432/EC/2020). Written informed consent was obtained before subjects’ enrolment.

Clinical data, breast cancer characteristics, and follow-up

Demographic and clinical data, including age, menarche, menopausal status, parity, education, occupation, insurance, BMI, and upper arm circumference was collected from the main study database. Baseline haemoglobin (Hb), albumin, leucocyte, aspartate transaminase (AST), and alanine transaminase (ALT) concentration measurements were performed within one week prior to subjects’ first chemotherapy cycle. Clinical staging was determined using the 7th edition of the American Joint Committee on Cancer (AJCC). Details on tumour profile and biomarkers expression were obtained through the patient’s histopathological examination result. Estrogen receptor (ER), progesterone receptors (PR), and human epidermal growth factor 2 (HER2) was defined according to the American Society of Clinical Oncology/College of American Pathologist (ASCO/CAP) guidelines [21, 22].

Subjects received chemotherapy as neoadjuvant treatment (before surgery), adjuvant treatment (after surgery), or palliative treatment with or without surgery, as planned by their respective oncologist. Most subjects in this study received AC-T (Doxorubicin-Cyclophosphamide-Taxane, 47.8%), EC-T (Epirubicin-Cyclophosphamide-Taxane, 11.8%), or FEC-T (5-Fluorouracyl-Epirubicin-Cyclophosphamide+Taxane, 10.3%) chemotherapy regimen. Ten subjects received TCb (Taxane-Carboplatin, 7,4%) chemotherapy regimen. Capecitabine was given for 10 subjects in total (7.4%), seven (5.2%) as single-agent therapy, two (1.5%) following Taxane, while one (0.8%) was given following Taxane and in combination with cyclophosphamide. Herceptin was used in the treatment of three subjects in total (2.2%), each following AC-T, EC-T, and FEC-T.

Follow-up was conducted within 2 weeks after the subjects’ last chemotherapy cycle as part of observation in the main study to evaluate the total chemotherapy cycles received. Chemotherapy-induced nausea and vomiting (CINV) episodes were recorded on each chemotherapy cycle evaluation. Based on the median of CINV episodes experienced by subjects, CINV was categorized as mild if one experienced it in no more than 4 treatment cycles and severe otherwise.

Vitamin D measurements

Vitamin D concentrations were measured from blood samples taken at baseline and post-chemotherapy follow-up using standard phlebotomy procedures. Blood samples were collected within one week prior to the date of first chemotherapy administration (baseline) and after the last chemotherapy dose (post-treatment), where possible. Covid 19 pandemic affected the timeliness of the biological sample collections, causing altered schedule in the blood sample taking, both at baseline and post-treatment observation points (ranged 0–147 days and 3–125 days, respectively). After being centrifugated, plasma samples were aliquoted and stored at -80°C until analysis. Prior to vitamin D measurements, no sample has undergone more than 2 freeze-thawing cycles. Vitamin D concentration was measured as 25(OH)D with ELISA method using DRG 25(OH)-Vitamin D kit (DRG, Marburg, Germany; Cat no. EIA-5396. The intra- and inter-assay coefficient of variability (%CV) was 4.7% and 10.2%, respectively. Sensitivity of the assay was 74.7% for 25-OH-Vitamin D2 and 100% for 25-OH-Vitamin D3. Sample storage and analysis were done at the Biobank and the Integrated Research Laboratory of the Faculty of Medicine, Public Health, and Nursing, Universitas Gadjah Mada, performed by research team member blinded to subjects’ personal and clinical characteristics. Vitamin D concentration was defined as sufficient (≥30 ng/ml), insufficient (20.0–29.9 ng/ml), deficient (12.0–19.9 ng/ml), and severely deficient (<12.0 ng/ml) [23-25].

Statistical analysis

It is estimated that at least 119 samples are needed to achieve 90% power and 5% two-sided level of significance to observe 2ng/mL mean difference in vitamin D concentration, assuming the standard deviation of the difference to be 6.67 ng/ml [26]. Kolmogorov-Smirnov test was performed to observe the distribution of all numeric variables. Demographic and clinical characteristics at baseline were explored using descriptive analyses. Independent t-test and ANOVA were used to observe differences of mean vitamin D among subjects with different characteristics. Independent t-test was also performed to compare mean vitamin D based on the duration of sample collection and the season when the sample was collected. The season was determined based on the date of sample collection and grouped into dry and rainy seasons according to the report of the national Meteorological, Climatological, and Geophysical Agency. The Spearman correlation analysis was employed to observe the association between baseline vitamin D concentration with the demographic and clinical profile. Missing data were excluded from bivariate analysis for the corresponding factor. Paired t-test was then performed to evaluate the changes in vitamin D concentration between baseline and post-chemotherapy. The odds ratio for a subject to experience a decrease in their post-chemotherapy vitamin D concentration was analysed based on the variance in the number of chemotherapies cycles and concomitant effect during treatment, namely CINV. P-value of the odds for chemotherapy duration and CINV severity was reported based on Pearson’s chi-square test. Shorter chemotherapy duration and less-severe CINV were used as the reference group. All analyses were performed with IBM SPSS Statistics 17.0 (IBM Inc., Armonk, USA) and a two-sided p-value of ≤0.05 was considered statistically significant.

Results

Characteristics of the study population

A total of 212 women who met the inclusion criteria have been registered in the main study by June 2021. Among them, 44 were still undergoing chemotherapy programs and thus were not included in the present study. A further 32 subjects were excluded because none of their post-chemotherapy blood samples were available, making a total number of 136 patients included in the nested study (Fig 1).

Fig 1

Flowchart of subjects’ inclusion process.

Flowchart showed subjects’ identification from the parenting study. Of the 212 participants already recruited in the main study, 44 were not included because they had not yet completed all planned chemotherapy cycles. Thirty-two participants were excluded because their blood samples were not available.

The median age of the subjects was 51 years old (Table 1). The median age of subjects’ menarche was 14 years old and more than half were already menopause by the time of the study (72, 52.9%). Among 67 (93.1%) subjects who provided information of their menopause, the median age of menopause is 50±6 years. The median duration of menopause is 7.91±10.5 years at enrolment. Aside from the seventeen subjects who had never given birth (17, 12.5%), most were multiparous (104, 76.5%). Most subjects were well educated (74, 54.4%), are working (74, 54.4%), and owned paid or private insurance (111, 81.6%). Subjects have a good clinical profile at enrolment, with 96.3% presented with ECOG 1 and the median value of all clinical parameters was observed within the normal range at baseline. Although underweight subjects dominated the study (51, 37.5%), the median BMI was within the normal category (20.91 kg/m2). Most subjects were diagnosed with ductal infiltrative breast cancer (115, 84.6%) and have poor histological differentiation (82, 60.3%). Most subjects were presented with locally advanced breast cancer (60, 44.1%). Subjects’ immunohistochemistry profiles showed that more subjects have positive ER and PR expression (81, 59.6% and 69, 50.7%, respectively), and negative HER2 expression (90, 66.2%).

Table 1

Baseline characteristics of study subjects (n = 136).

Baseline characteristics	Frequency N (%)
Age (years; median±IR)	51.00±13.00
Age of menarche (years; median±IR)	14.00±3.00
Menopause
Menopause	72 (52.9)
Pre-menopause	64 (47.1)
Age of first pregnancy (years; median±IR)	23.50±8.00
Parity
Nullipara	17 (12.5)
Primipara	15 (11)
Multipara	104 (76.5)
Education
Undereducated	62 (45.6)
Well educated	74 (54.4)
Occupation
Housewives	62 (45.6)
Workers	74 (54.4)
Insurance
Underprivileged insurance	25 (18.4)
Paid and private insurance	111 (81.6)
BMI (kg/m2; median±IR)	20.91±10.63
Underweight-normal (<25.00 kg/m2)	99 (72.8)
Overweight-obese (≥25.00 kg/m2)	37 (27.2)
Upper arm circumference (cm; median±IR)	27.00±6.00
Hb (mg/dL; mean±SD)	12.65±1.85
Albumin (g/dL; median±IR)	4.51±0.74
Leucocyte (x106/ul; median±IR)	7.09±2.23
AST (IU/l; median±IR)	20.00±11.00
ALT (IU/l; median±IR)	23.00±14.00
Histological type
Ductal infiltrative	115 (84.6)
Lobular infiltrative	9 (6.6)
Others	12 (8.8)
Grade
Well-moderately differentiated	34 (25)
Poorly differentiated	82 (60.3)
Missing	20 (14.7)
Tumor size
≤T1	13 (9.6)
T2	39 (28.7)
T3	42 (30.9)
T4	42 (30.9)
Stage
Stage 1–2	43 (31.6)
Stage 3	60 (44.1)
Stage 4	33 (24.3)
ER
Positive	81 (59.6)
Negative	53 (39)
Missing	2 (1.5)
PR
Positive	69 (50.7)
Negative	65 (47.8)
Missing	2 (1.5)
HER2
Positive	41 (30.1)
Negative	90 (66.2)
Missing	5 (3.7)
Number of chemotherapy cycles
≤6 cycles	43 (31.6)
>6 cycles	93 (68.4)
CINV
None-mild	76 (55.9)
Severe	60 (44.1)
Baseline vitamin D concentration (ng/ml; median±IR)	8.44±4.59
Sufficient	0 (0)
Insufficient	1 (0.7)
Deficient	23 (16.9)
Severely deficient	112 (82.4)

Abbreviation: IR: interquartile range; BMI: body mass index; ALT: alanine transaminase; AST: aspartate transaminase; ER: estrogen receptor; PR: progesterone receptor; HER2: human epidermal growth factor receptor 2; ACT: anthracycline-cyclophosphamide-taxane.

One-hundred and twenty-two subjects (89.0%) have undergone surgery prior to the first cycle of chemotherapy. The median duration of chemotherapy was 5 months with 12 (8.8%) subjects receiving treatment for longer than 6 months. Of all subjects, 101 (74.3%) received a combination of anthracycline, cyclophosphamide, and taxane during treatment. Chemotherapy regimens were given in more than 6 cycles in 93 subjects (68.4%). After evaluating the concomitant effect experienced by subjects during treatment, eight of them never experience any nausea or vomiting while mild and severe CINV was more common (68, 50% and 60, 44.1%, respectively).

Vitamin D profile at baseline

In this study, none of the subjects has normal vitamin D status. Median vitamin D at baseline was 8.44±4.59 ng/ml and was below the cut-off of severe deficiency on different patients’ and tumours’ characteristics (Tables 1 and 2). We found no significant difference in mean vitamin D levels among subjects with different menopausal status, parity, education, occupation, insurance, BMI, and tumour characteristics (S1 Table). Based on the median of age (51 years old), median baseline vitamin D is similar among younger and older subjects (p = 0.428). Median vitamin D also did not differ (p = 0.819) among subjects who were underweight (median±IR = 8.06±5.44 ng/ml), normal (median±IR = 9.10±5.27 ng/ml), overweight (median±IR = 9.68±3.16 ng/ml), and obese (median±IR = 8.23±2.82 ng/ml). A significant correlation was observed between baseline vitamin D concentration with AST level (r = -0.188, p = 0.028) (Table 2). Vitamin D concentration was not correlated with socio-demographic and other clinical profiles.

Table 2

Correlation between baseline vitamin D level with socio-demographic factors and clinicopathology characteristics (n = 136).

Predictors	Baseline vitamin Da (ng/ml; median±IR)	Spearman Correlation
		R	p-value
Age (years; median±IR)		0.096	0.266
Age of menarche (years; median±IR)		0.005	0.955
Menopause		0.086	0.317
Menopause	8.62±5.33
Pre-menopause	8.18±4.46
Age of first pregnancy (years; median±IR)		-0.012	0.895
Parity		-0.015	0.866
Nullipara	9.78±6.02
Primipara	5.69±6.11
Multipara	8.43±3.85
Education		0.059	0.496
Undereducated	8.21±3.50
Well educated	8.67±5.45
Occupation		0.003	0.974
Housewives	8.45±4.23
Workers	8.49±4.89
Insurance		0.030	0.729
Underprivileged insurance	8.06±4.73
Private insurance	8.50±4.51
BMI (kg/m2; median±IR)		0.083	0.336
Underweight-normal (<25.00 kg/m2)	8.45±5.31
Overweight-obese (≥25.00 kg/m2)	8.43±2.84
Upper arm circumference (cm; median±IR)		0.034	0.699
Hb (mg/dL; mean±SD)		-0.062	0.476
Albumin (g/dL; median±IR)		-0.095	0.308
Leucocyte (x106/ul; median±IR)		-0.005	0.959
AST (IU/l; median±IR)		-0.188	0.028b
ALT (IU/l; median±IR)		-0.144	0.096
Histological type		-0.040	0.644
Ductal infiltrative	8.45±4.91
Lobular infiltrative	3.74±5.73
Others	7.87±5.35
Grade		-0.051	0.585
Well-moderately differentiated	8.79±5.56
Poorly differentiated	8.26±4.72
Tumor size		0.124	0.149
≤T1	8.04±5.68
T2	7.94±4.53
T3	8.12±4.82
T4	9.21±4.31
Stage		0.025	0.776
Stage 1–2	8.43±3.43
Stage 3	8.31±4.93
Stage 4	9.68±6.41
ER		-0.110	0.205
Positive	8.42±4.77
Negative	8.51±5.16
PR		-0.063	0.473
Positive	8.43±4.64
Negative	8.51±4.88
HER2		0.106	0.227
Positive	8.59±4.11
Negative	8.43±4.88

Abbreviation: IR: interquartile range; 95% CI: 95% confidence interval; BMI: body mass index; ALT: alanine transaminase; AST: aspartate transaminase; ER: estrogen receptor; PR: progesterone receptor; HER2: human epidermal growth factor receptor 2.

Due to missing values, the counts of some variables did not add up to the total.

aIndependent t-test and ANOVA test were done to compare median vitamin D levels and no significant difference was found among groups. Results are presented in S1 Table.

bStatistically significant.

Post-chemotherapy vitamin D changes

A lower median vitamin D concentration was observed post-treatment (median±IR = 6.89±4.44 ng/ml) (Table 3). The paired t-test analysis found a significant change in the vitamin D concentration, as compared to the level measured at baseline (p <0.001). The median and interquartile value obtained from computing the absolute changes of vitamin D between the two observation points was 3.13±4.03 ng/ml. Even though the number of severely deficient subjects was already high at baseline (82.4%), the proportion rose to 89.0% after chemotherapy. Sixteen subjects (69.6%) who were deficient and the only subject who was insufficient at baseline become severely deficient by the end of observation. Although an increase in vitamin D concentration was observed in 51 subjects (37,5%), only 7 (6.25%) showed status improvement from severely deficient to deficient.

Table 3

Vitamin D concentration changes between baseline and post-chemotherapy in breast cancer patients (n = 136).

Time point	Vitamin D concentration	Paired T-test p-value
	(ng/ml; median±IR)
Baseline	8.44±4.59	p <0.001
Post-treatment	6.89±4.44

Abbreviation: IR: interquartile ratio; COV: coefficient of variability.

The median duration between sample collection with first chemotherapy was 8±7 days and 13±22 days with the last chemotherapy dose administration (S2 Table). Distance of blood sample collection was more than 14 days in 26 subjects (19.18%) at baseline and 62 subjects (45.60%) at post-treatment observation. On both observation points, we found no significant difference in vitamin D level between samples taken within 14 days and more than 14 days from the closest chemotherapy administration (S3 Table).

Seventy-one baseline samples (52.21%) and 78 post-treatment samples (57.35%) were taken in the rainy season. Median vitamin D level was similar between samples taken in the dry and rainy season, both in baseline (median±IR = 8.02±5.36 vs. 9.09±3.50 ng/ml, p = 0.078) and post-treatment observation (median±IR = 7.46±5.01 vs. 6.45±4.54 ng/ml, p = 0.344) (S4 Table).

Association between post-chemotherapy vitamin D level and chemotherapy factors

After chemotherapy, vitamin D concentration was decreased on 84 subjects (61.8%) (Table 4). Among them, most received treatment for less than 6 months (75, 89.3%) and received more than six chemotherapy cycles (n = 52, 61.9%). Vitamin D decrease was observed in 33 subjects who experienced severe CINV (39.3%) and 51 who experienced mild or did not experience CINV (60.7%). No significant difference was observed in the vitamin D level between different chemotherapy cycles and CINV severity (p = 0.381 and 0.338 respectively) (S5 Table).

Table 4

Association of chemotherapy cycles and nausea and vomiting with the decrease of post-treatment vitamin D concentration (n = 136).

Variables	Post-treatment vitamin Da				Pearson’s Chi Square
	Decrease		Increase/persist		OR (95% CI)	p-value
	n	%	n	%
Chemotherapy cycles
≤6 cycle	32	38.1	11	21.2	1.000	0.039b
>6 cycle	52	61.9	41	78.8	0.436
					(0.196–0.968)
CINV
None-mild	51	60.7	25	48.1	1.000	0.149
Severe	33	39.3	27	51.9	0.599
					(0.298–1.204)

Abbreviation: OR: Odd ratio; 95% CI: 95% confidence interval; CINV: chemotherapy-induced nausea and vomiting.

aIndependent t-test and ANOVA test were done to compare median vitamin D levels and no significant difference was found among subjects with different chemotherapy cycles and CINV severity groups. Results are presented in S5 Table.

bStatistically significant.

We observed that subjects who received more than 6 cycles of chemotherapy were less likely to have worse post-treatment vitamin D compared to those who received 6 cycles or less (OR = 0.436, 95% CI = 0.196–0.968, p = 0.039). Vitamin D level was less likely to decrease in subjects who experience severe CINV (OR = 0.599, 95% CI = 0.298–1.204, p = 0.149).

Discussion

Summary of key findings

This is the first study evaluating pre- and post-treatment vitamin D changes in Indonesian breast cancer patients and exploring factors associated with it. We found that Indonesian breast cancer patients have very low vitamin D concentration and experience a significant deterioration after chemotherapy. Among socio-demographic and clinical factors observed in our study, AST was the only factor associated with vitamin D concentration. Moreover, we discovered that patients who had more chemotherapy cycles were less likely to experience a decrease in their post-treatment vitamin D, emphasising the significance of chemotherapy effects towards vitamin D concentration in already deficient subjects.

Comparison of vitamin D profile with previous studies

The high prevalence of vitamin D deficiency (VDD) and low vitamin D concentration in breast cancer patients have been observed, both in European, Australian and Asian populations (mean ranging from 12.4 to 22.8 ng/ml) [6, 12, 27–29]. Post-treatment vitamin D deterioration has also been observed in previous studies in other populations [11, 12]. However, the median vitamin D concentration observed in this study was lower than previously reported.

Information on vitamin D status in the Indonesian general population are very limited and have only been assessed for the certain population at risk, such as pregnant women, newborn, children, and, as recently observed, among adult Covid-19 patients [17–19, 30, 31]. Although studies of vitamin D profile in Indonesian cancer patients remain limited, previous studies have highlighted the low vitamin D concentration (mean = 21.2 and 15.7 ng/ml) and high prevalence of VDD (60%) in healthy Indonesian women [32-34]. In accordance, our study shows very low vitamin D concentration at baseline with VDD observed in almost all subjects (99.4%), despite having good clinical profiles.

In addition, low vitamin D concentration was observed regardless of menopausal status, parity, education level, occupation, and insurance in this study. This result suggests the pre-existing poor vitamin D concentration in the general population. Moreover, this study also does not find the existence of seasonal influence toward subjects’ vitamin D status. Although Indonesia’s geographical location ensures year-round sun exposure, the climate, and high sun exposure encourage sun-protective behaviour, limiting UV B exposure and vitamin D synthesis [12, 34, 35]. Moreover, the Indonesian population has a tendency to dress modestly, covering most of the skin. Along with cultural belief to avoid sun exposure and skin tanning, this may lead to a lower vitamin D concentration in Indonesian women [35, 36].

Despite Indonesia and most of the South East Asian countries being thought to have a low risk of VDD due to its location near the equator, recent studies show otherwise [17, 35–37]. The lower vitamin D concentration was not only observed in the population living in South East Asia but also of its descent who live in Europe (mean = 22.1 ng/ml and 22.8 ng/ml, respectively). This suggests an influence of genetic variance on vitamin D metabolism that warrants further investigation [38, 39]. Aside from the difference in skin tone, the higher visceral adipose tissue (VAT) in South Asian compared to European descent is associated with higher sequestration and therefore lower vitamin D concentration [40]. The higher proportion of VAT was found in Asian population despite of lower BMI [41-43]. The stronger negative correlation between VAT with vitamin D level instead of the overall body fat might explain the low vitamin D across different BMI categories as observed in this study [40].

Vitamin D concentration observed in our study was lower than previously observed in locally advanced breast cancer women in Surabaya, Indonesia (median = 17.41 ng/ml) [20]. The previous study was done in smaller sample size and only include post-menopausal locally advanced breast cancer patients receiving CAF neoadjuvant treatment. Although the different patients’ characteristics presented in our study might provide vitamin D profile of Indonesian breast cancer patients in a wider scope, we were also unable to dismiss the possibility of different diets and sun behaviour between the two study samples also influencing the lower vitamin D status presented in this study.

The vitamin D measurement assay selected for this study have high sensitivity and specificity, and good comparability to similar vitamin D assays [44, 45]. All samples were kept in -80°C prior to analysis with no history of freeze-thaw. All samples, QC low, QC high, and standards from the kits were treated uniformly and concurrently, minimising any possible treatment biases of the assay. The vitamin D concentration of the samples falls within the range of the standard curve and low measurement results were not influenced by the type of assay used. Considering the similarly low vitamin D concentration observed in Korean breast cancer patients and the high prevalence of deficiency in various studies on different at-risk population in Indonesia, the very low vitamin D concentration observed in our study suggest the severity of vitamin D deficiency in Indonesian women [17, 18, 29, 30].

The only variable significantly correlate with vitamin D level at baseline was AST serum level. All subjects enrolled in the study had a good performance and clinical status, and none had any form of liver disorder at the beginning of the study. Despite median AST concentration being within the normal range, we found that higher AST was associated with lower vitamin D concentration. Although the association between vitamin D and AST has not been widely investigated in breast cancer patients, several studies have explored its correlation with liver disease. In line with our discovery, higher vitamin D concentration was associated with lower odds of higher AST in previous study (OR = 0.97, 95% CI = 0.93–1.00, p <0.05) [46]. While the exact mechanism needs to be further explored, increased AST concentration was associated with a disturbance of liver function, causing decreased expression of D binding protein and ineffective gastrointestinal vitamin D absorption, and in turn, decreased vitamin D concentration [8, 47–49].

Our study observed that subjects who received more than 6 chemotherapy cycles had lower odds to experience vitamin D decrease compared to patients who were only prescribed 6 cycles or less. Although more chemotherapy cycle does not necessarily mean a longer treatment duration, a study performed in Australian breast cancer women also find that patients’ mean vitamin D level was lower at 6th week observation compared to 12th week [12]. Chemotherapy, especially anthracycline, cyclophosphamide, and taxane which were mainly used in the treatment of subjects in this study, are known to cause gonad toxicity and resting oocytes destruction. This will in turn cause reduced estrogen expression and increased vitamin D catabolism [13, 50]. Vitamin D decreases have been observed in breast cancer patients receiving ACT, AC, and FEC-T [11, 14]. The chemotherapy regimen in this study is quite homogenous as treatments were given in accordance with the standard therapy regimen based on tumour characteristics. The high-frequency anthracycline and taxane used might cause the contradicting results observed.

Although not statistically significant, our study suggests that more severe CINV was associated with higher post-chemotherapy vitamin D concentration. CINV in cancer patients was associated with poor intake and worse nutritional status [51]. However, the correlation between CINV severity and vitamin D concentration as observed in this study could be explained by diet modification, as commonly encouraged in the local practice. A similar result was also observed by others [12]. Consumption of fortified food and supplement are often encouraged to help patients fulfil their nutritional needs despite intake limitation caused by CINV. Moreover, a previous preclinical study [52] shows higher intestinal absorption and hydroxylation in vitamin D deficient, suggesting a compensating mechanism might occur in low vitamin D concentration.

Clinical and population health applicability

Maintained vitamin D concentration was associated with a better clinical outcome in breast cancer patients. A previous study discovered that improvement of vitamin D was correlated with a lower risk of fatality (HR = 0.57, 95%CI = 0.43–0.75) [10]. This is due to its ability to inhibit abnormal cell growth and differentiation and to regulate local vitamin D synthesis on breast tissue [7-9]. To perform this function, vitamin D is needed at its normal concentration at 30 ng/ml [7].

One way to maintain and improve vitamin D sufficiency was through supplementation [53]. Nevertheless, it is essential to provide vitamin D supplementation in adequate dosage to avoid ineffective treatment due to unmet therapeutic dose [54] or toxicity due to excess dosage [15]. The low mean vitamin D concentration observed in our study suggests that a higher dose of vitamin D supplementation might be necessary. A higher dose of vitamin D supplementation has shown superior results in normalizing vitamin D concentration (30% vs 12.6% improvement, p = 0.003) [55]. Although the maximum dose of 10,000 IU/day has been found to be the no-observed-adverse-effect level (NOAEL), caution must be taken concerning the J-shaped relationship between vitamin D concentration and breast cancer prognosis as observed on vitamin D concentration above 44 ng/ml (HR = 1.63, 95% CI = 1.21–2.19) [7, 54]. Further study is warranted to determine the most suitable dose, duration, and preparation for Indonesian breast cancer patients.

Study strength and limitation

The strength of the study was the fact that it was conducted in a tertiary hospital in Yogyakarta, the region with the highest cancer prevalence in the country [56] where breast cancer was the most common [57, 58]. Thus, it was expected to be able to represent the regional breast cancer population. However, some limitations should be considered in the interpretation of our results. Sun behaviour, clothing coverage, skin tone, body fat distribution, and daily vitamin D intake were not observed and thus warrant further exploration. In addition, the chemotherapy used by subjects of our study were commonly prescribed in local practice. Further study with matching control and controlled chemotherapy variant should be done to elucidate the effect of different regimens on vitamin D changes.

Conclusion

Baseline vitamin D is very low in Indonesian breast cancer patient and decrease significantly afterward. Vitamin D concentration in breast cancer patients is associated with AST level while post-treatment vitamin D changes is associated with chemotherapy cycle. Although further study is needed to explore the dynamic of vitamin D changes during chemotherapy, treatment outcome, and the optimal vitamin D supplementation needed in the local population, our study provides important data to improve care for breast cancer patients, especially those receiving chemotherapy.

Comparison of baseline vitamin D level among different socio-demographic factors and clinicopathology characteristics (n = 136).

Abbreviation: IR: interquartile range; BMI: body mass index; ER: estrogen receptor; PR: progesterone receptor; HER2: human epidermal growth factor receptor 2.

(PDF)

Click here for additional data file.

Duration between sample collection and nearest chemotherapy administration (n = 136).

Abbreviation: IR: interquartile range.

(PDF)

Click here for additional data file.

Comparison of vitamin D level among different distances of sample collection from nearest chemotherapy administration (n = 136).

Abbreviation: IR: interquartile range.

(PDF)

Click here for additional data file.

Comparison of vitamin D level among different seasons at point of sample collection (n = 136).

Abbreviation: IR: interquartile range.

(PDF)

Click here for additional data file.

Comparison of post-treatment vitamin D level among different chemotherapy factors (n = 136).

Abbreviation: IR: interquartile range; CINV: chemotherapy-induced nausea vomiting.

(PDF)

Click here for additional data file.

Minimal data set.

(XLSX)

Click here for additional data file.

10 Feb 2022

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Additional Editor Comments:

In order to address the review in the best possible way, the following aspects should be clarified:

- how was the sample size calculated?

- define the "baseline" time for measuring the basal levels of vitamin D

- provide the coefficients of variability for the measurement of serum 25-OH-D

- avoid repeating the same results in the text and tables

- indicate in the tables (example table 2) if statistical tests have been performed between different groups and if the test is significant (eg vitamin D among nullipara, primipara and multipara).

- analyze in more detail the differences between baseline and post-chemothrapy using median value and interquartile range. Also statistically define the difference.

- consider the time elapsed between baseline and final dosing and assess whether the seasonality of the sampling may have influenced the result.

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27 Mar 2022

Dear Editor,

We are thankful for the positive feedback received from the editorial team, and for the opportunity to respond to the constructive points in our submitted manuscript. Please find below our point-by-point response to the feedback outlining, where relevant, the related changes we have made. We have uploaded revised versions of the manuscript as instructed, including both a clean copy and a track changes version, and additional supplementary files made accordingly.

Comments

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Response

Thank you for your remark. We have checked these requirements prior to submitting the revised manuscript.

2. Thank you for stating the following financial disclosure: “SHH received funding from Kementrian Riset, Teknologi dan Pendidikan Tinggi Republik Indonesia (ID) (2018) and Universitas Gadjah Mada (2020).” Please state what role the funders took in the study. If the funders had no role, please state: "The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript." If this statement is not correct you must amend it as needed. Please include this amended Role of Funder statement in your cover letter; we will change the online submission form on your behalf.

Response: We confirm that this study only received funding from the stated institutions and the funder indeed had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. We also included the statement in our cover letter.

3. In your Data Availability statement, you have not specified where the minimal data set underlying the results described in your manuscript can be found. PLOS defines a study's minimal data set as the underlying data used to reach the conclusions drawn in the manuscript and any additional data required to replicate the reported study findings in their entirety. All PLOS journals require that the minimal data set be made fully available. For more information about our data policy, please see http://journals.plos.org/plosone/s/data-availability. Upon re-submitting your revised manuscript, please upload your study’s minimal underlying data set as either Supporting Information files or to a stable, public repository and include the relevant URLs, DOIs, or accession numbers within your revised cover letter. For a list of acceptable repositories, please see http://journals.plos.org/plosone/s/data-availability#loc-recommended-repositories. Any potentially identifying patient information must be fully anonymized. Important: If there are ethical or legal restrictions to sharing your data publicly, please explain these restrictions in detail. Please see our guidelines for more information on what we consider unacceptable restrictions to publicly sharing data: http://journals.plos.org/plosone/s/data-availability#loc-unacceptable-data-access-restrictions. Note that it is not acceptable for the authors to be the sole named individuals responsible for ensuring data access. We will update your Data Availability statement to reflect the information you provide in your cover letter.

Response:

We have provided the minimal data set that were used to generate all tables and supplementary tables demonstrated the findings presented in the paper. The full de-identified dataset would not be able to be shared publicly due to restrictions imposed by the ethics committee as most of these are contain patient data, albeit de-identified, and it may be possible to determine the identify of participants given the extent of sociodemographic and clinical data available for each participant.

Should there be a request for data, this can be sent to the corresponding author (email: susanna.hutajulu@ugm.ac.id). Future researchers can contact the institutional ethics committee (email: mhrec_fmugm@ugm.ac.id) at Universitas Gadjah Mada, Indonesia, with data access queries as well.

In the revised manuscript we have uploaded the minimal data set as Supporting Information file. We also restated our data availability statement in the cover letter.

4. Please ensure that you refer to Figure 1 in your text as, if accepted, production will need this reference to link the reader to the figure.

Response: Thank you for your suggestion, the flow of subjects’ enrolment in the study as presented in Figure 1 is now cited in line 196.

Additional Editor comments

In order to address the review in the best possible way, the following aspects should be clarified

1. How was the sample size calculated?

Response:

Thank you for your question about the sample size calculation used in the study. The sample calculation was performed to assess the main outcome in the study, observing changes in post-treatment vitamin D level. The minimal sample size was calculated to compare two paired means using paired t-test analysis, using standard deviation of differences obtained from previous study by Gabr and Marei (2017). We calculated the minimal sample to present 90% power with 5% significance. Although the minimal sample size required is 119 subjects, all subjects meeting the inclusion criteria from the main study is included to increase the power of data presented, making the final number of samples of the study into 136 subjects. We have now added in lines 164-166 under Methods.

2. Define the "baseline" time for measuring the basal levels of vitamin D.

Response:

In this study, baseline blood sampling was taken within the time of subjects’ diagnosis until prior to the first dose of chemotherapy administration. The proposed timeline was within one week. However, during COVID 19 pandemic this timeline was altered. In some cases chemotherapy initiation was postpone while baseline blood sampling has already been performed, resulting in longer time space between sampling and chemotherapy administration. Same problem occured for post chemotherapy blood sampling when patients did not visit hospital in their planned schedule. Sampling timeline ranged 0-147 days before first chemotherapy and 3-125 days after the last chemotherapy. We now have made the definition of the baseline observation in the study clearer. It is now added in lines 144-150 under Methods.

3. Provide the coefficients of variability for the measurement of serum 25-OH-D.

Response:

Thank you for your query on the coefficients of variability in the study. The intra- and inter-assay coefficient of variability (%CV) was 4.7% and 10.2%, respectively. This information is now disclosed in lines 155-156 under Methods.

4. Avoid repeating the same results in the text and table.

Response:

Thank you for this comment. We have reviewed our manuscript and made necessary adjustments to avoid repetition of the results already presented in all tables and modified Fig 1 legend.

5. Indicate in the tables (example table 2) if statistical tests have been performed between different groups and if the test is significant (eg vitamin D among nullipara, primipara and multipara).

Response:

Thank you for your suggestion. In this study, we compared the mean vitamin D between groups using independent t-test and ANOVA test and found no significant difference on all variables observed. We have added this information accordingly under Methods in lines 169-172 and legends of Table 2 and Table 4. We have also added the result of between groups comparison of baseline vitamin D under Results in lines 236-238, citing the corresponding results presented as S1 Table, and comparison of post-chemotherapy vitamin D level in lines 288-290, citing S5 Table.

6. Analyze in more detail the differences between baseline and post-chemotherapy using median value and interquartile range. Also statistically define the difference.

Response:

Thank you for your advice to convey the differences of vitamin D level in more details. Under Results in lines 255-258, we explained that the paired t-test analysis found a significant change of the vitamin D concentration, as compared to the level measured at baseline (p <0.001). The median and interquartile value obtained from computing the absolute changes of vitamin D between the two observation points was 3.13±4.03 ng/ml.

7. Consider the time elapsed between baseline and final dosing and assess whether the seasonality of the sampling may have influenced the result.

Response:

We have performed additional analysis to evaluate the time elapsed between sample collection and the closest chemotherapy completion, as well as the seasonality of the samples in our study. The time elapsed was calculated as the days between the sample collection and the closest last chemotherapy administration to the subjects. For the seasonality analysis, we matched the date of the sample collection with the season as determined by the national Meteorological, Climatological, and Geophysical Agency for the area of Yogyakarta, where the study took place. The analysis was performed using independent t-test as described under Methods in lines 171-175 and presented in S3 and S4 Tables as cited under Results in lines 265-271.

We hope that, following our revisions, the manuscript is now suitable for publication in the PLOS ONE.

Yours sincerely,

Susanna Hutajulu, MD, PhD

Submitted filename: Response to Reviewers.docx

Click here for additional data file.

17 May 2022

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Academic Editor

PLOS ONE

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Comments to the Author

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Reviewer #1: (No Response)

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Reviewer #1: Partly

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Reviewer #1: Yes

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Reviewer #1: Yes

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Reviewer #1: Yes

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Reviewer #1: Manuscript ID PONE-D-21-36153

Title: Vitamin D status in breast cancer patients following chemotherapy: a pre and post

observational study in a tertiary hospital in Yogyakarta, Indonesia

In this study, the authors investigated To observe pre- and post-treatment vitamin D level and factors that influence its level changes after chemotherapy in breast cancer patients.

Comments for the Author:

1- The title is OK

2- In abstract: the objective differs from that of the text.

3- In Introduction is ok.

4- In methods:

Has the main study been published?

Better describe the inclusion and exclusion criteria in the present study.

Describe the sample size calculation

What is the time between the first and second serum vitamin D dosage?

5- In Results:

Age factor is important in terms of serum vitamin D values. What is the age range among the participants?

How many women were under 40 years of age?

How long is post-menopause?

What is the impact of weight on serum vitamin D values? Because 30% of women were obese.

In table 2, the presentation of the results is not clear.

In tables 2, 3 and 4, add statistical analysis with p value

6- In Discussion:

Could the type of test (ELISA) that was used for serum levels of vitamin D have influenced such low vitamin D results?

**********

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Reviewer #1: No

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26 May 2022

Dear Editor and Reviewer,

We are thankful for the positive feedback received from the reviewer, and for the opportunity to respond to the constructive points in our submitted manuscript. Please find below our point-by-point response to the feedback outlining, where relevant, the related changes we have made. We have uploaded revised versions of the manuscript as instructed, including both a clean copy and a track changes version, and additional supplementary files made accordingly.

Reviewer #1

1. The title is OK

Response

Thank you for your feedback.

2. In abstract: the objective differs from that of the text.

Response:

The objective in the Abstract previously stated as “to observe pre- and post-treatment vitamin D level and factors that influence its changes after chemotherapy in breast cancer patients”, is now changed into “to observe pre -and post-treatment vitamin D level and its association with treatment and concomitant factors in breast cancer patients treated with chemotherapy” (lines 28-30)”

3. In introduction is ok.

Response:

Thank you for reviewing this section.

4. In methods: Has the main study been published?

Response:

Thank you for your query on the main study. The prospective cohort is still ongoing, thus main data are still under collection. Nested studies exploring diagnostic delay in breast cancer (Hutajulu SH et al., PLoS One 2021) and patients’ experience (Prabandari et al., The Breast 2022) have been published as part of the main study.

5. In methods: Better describe the inclusion and exclusion criteria in the present study.

Response:

Thank you for your advice to elucidate the inclusion and exclusion criteria employed in the study. We try to make clear that the subjects included in our study are selected from an ongoing cohort with already selected criteria. Under Methods in lines 98-109, we now explain that “We performed a nested pre-post observational study assessing 25(OH)D changes on primary breast cancer patients registered in a prospective ongoing cohort. The main study analysed the risk of chemotherapy side effects and its effect on survival and quality of life in breast cancer patients. Subjects of the main study were histologically confirmed female breast cancer patients aged ≥18 years who were chemotherapy naïve and receiving their first chemotherapy in the Haematology and Medical Oncology Division, “Tulip”/Integrated Cancer Clinic, Dr. Sardjito General Hospital, Yogyakarta, Indonesia, from 2018-2022. No subjects in the cohort were in a terminal condition or with severe congestive heart failure. Among subjects enrolled in the main cohort, we only included those who have received their last chemotherapy cycle and completed post-treatment follow-up into the present study. Subjects who have incomplete blood sample were excluded.”

6. In methods: Describe the sample size calculation

Response:

Thank you for this suggestion. We performed the calculation of sample size to achieve the minimum number of samples for the main outcome. The minimal sample size was calculated for paired mean comparison using paired t-test analysis. The standard deviation of differences was obtained from a previous study by Gabr and Marei (2017), who found the mean difference between pre- and post-treatment vitamin D in Egyptian breast cancer patients to be 5.51 ng/ml (SD=6.67 ng/ml). We calculated the minimal sample to present 90% power with 5% significance. Although the minimal sample size required is 119 subjects, all subjects meeting the inclusion criteria from the main study are included to increase the power of data presented, making the final number of samples of the study 136 subjects. The sample size calculation is briefly explained under Methods in lines 170-172. We have also added the referenced study as a reference [26].

7. In methods: What is the time between the first and second serum vitamin D dosage?

Response:

Thank you for your question. We would like to clarify that no vitamin D supplementation was provided to the subjects as part of our study. However, we do perform the vitamin D measurement in two observation points, prior to- and after chemotherapy. The median duration between pre- and post-treatment sample collection in our study was 5.00±1.64 months. Although vitamin D changes between observation points are lower on samples taken more than 5 months apart (median±IR =2.46±3.31 ng/ml) as compared to less than 5 months (median±IR =3.59±4.12 ng/ml), we found that the difference is not statistically significant (p =0.055). While no significant difference in vitamin D concentration was found based on the duration of the delay in collecting blood samples (S3 Table), this delay prolongs the distance between pre- and post-treatment observation and might not represent the actual duration of the chemotherapy received by subjects. Instead, we report our findings by stratifying the vitamin D changes based on the number of chemotherapy cycles administered to better represent the neurotoxicity presumed to cause the decrease of vitamin D concentration in subjects.

8. In results: Age factor is important in terms of serum vitamin D values. What is the age range among the participants? How many women were under 40 years of age?

Response:

We agree that age is very important in regards to vitamin D levels. In our study, the median subjects’ age is 51±13 years old. The range of the age is 46, the youngest participant was 32 and the oldest was 78 years old. Based on the Spearman analysis result as presented in Table 2, age did not correlate with the baseline vitamin D level in our study (r =0.096, p =0.266). After stratifying based on the median age, the vitamin D level remains similar among younger and older subjects, both at baseline (p =0.428) and post-treatment (p =0.755). In our study, only 12 (8.82%) subjects were under 40 years old. Vitamin D however remains similar among groups under 40 and older (p =0.753). This result is added under Results in lines 248-249.

9. In results: How long is post-menopause?

Response:

Although 72 subjects were already menopause at the beginning of the study, only 67 (93.1%) were able to recall or have any documented examination results of their menopause. Among them, the median age of menopause is 50±6 years old. The median duration of menopause is 7.91±10.5 years when baseline vitamin D was measured. This result is now added under Results in lines 210-213.

10. In results: What is the impact of weight on serum vitamin D values? Because 30% of women were obese.

Response:

In our study, the low vitamin D level was observed in all subjects, and no difference was found among BMI categories. The median vitamin D did not differ (p =0.819) among subjects who were underweight (median±IR =8.06±5.44 ng/ml), normal (median±IR =9.10±5.27 ng/ml), overweight (median±IR =9.68±3.16 ng/ml), and obese (median±IR =8.23±2.82 ng/ml). However, we did not observe the body fat distribution of the subjects in our study. The higher proportion of visceral adipose tissue despite lower BMI in the Asian population and its stronger correlation with vitamin D instead of the overall body fat might explain the low vitamin D across different BMI as found in our study. This is now added under Results in lines 250-253 and Discussion in lines 369-372.

11. In results: In table 2, the presentation of the results is not clear.

Response:

Thank you for your remarks. In Table 2, we try to present the result of the Spearman correlation analysis result among the socio-demographic and clinicopathological characteristics of the subjects with their baseline vitamin D concentration. The value of baseline vitamin D, as well as the variable age, age menarche, age of first pregnancy, upper arm circumference, Hb, albumin, leucocyte, AST, and ALT, were analysed as continuous data. The variable menopause, parity, education, occupation, insurance, BMI, histological type, grade, tumor size, stage, ER, PR, and HER2 were analysed as categorical data, with the median vitamin D concentration of each category also presented in the table. The result is presented in Spearman rho and p-value. Among the factors observed, only AST shows a significant correlation. In addition to this analysis, we also compare the median vitamin D levels among different categories in each group using an independent t-test and ANOVA test. This result is presented in S1 Tables.

12. In results: In tables 2, 3 and 4, add statistical analysis with p value

Response:

Thank you for your advice. We now have added the statistical analysis corresponding to each p-value reported in Tables 2, 3, and 4.

13. In discussion: Could the type of test (ELISA) that was used for serum levels of vitamin D have influenced such low vitamin D results?

Response:

Thank you for expressing this concern. We choose the ELISA method to perform vitamin D analysis in our study due to its high availability in our country and to increase its reproducibility and the feasibility to apply the methods directly to clinical service in our setting. The kit we selected has high specificity (74.7% for 25-OH-D2 and 100% for 25-OH-D3) and good agreement with Diasorin LIAISON chemiluminescent immunoassay (CLIA) (R =0.919) and Roche Cobas (ECLIA) (R =0.948) in measuring vitamin D concentration. The respective assays have high correlations with liquid chromatography-tandem mass spectrometry (LC-MS/MS) (R =0.9455 and R =0.9102), which currently has the highest sensitivity and specificity in vitamin D measurement.

In performing the assay, we used low and high control in duplicates on each plate. The range of low and high control provided by the kit was 7.28-15.1 ng/ml and 37.9-78.7 ng/ml, respectively. In every plate, the low (ranged 7.02-11.57 ng/ml) and high (ranged 50.45-55.61 ng/ml) controls measured fell within the QC ranges. In addition, the assay was performed with 0-120 ng/ml standards which were provided in 6 concentrations; 0, 5, 15, 30, 60, and 120 ng/ml. In performing the assay, the lowest sample measured was 0.68 ng/ml and the highest sample measured was 25.16 ng/ml.

All samples were kept in -80 prior to analysis with no history of freeze-thaw. Furthermore, our plasma samples, QC low, QC high, and standards from the kits were treated uniformly and concurrently, minimising any possible treatment biases of the assay. Therefore, the vitamin D concentration of the samples in this study falls within the range of the standard curve and we are confident that the kit could not possibly contribute to the low values of the samples measured.

Considering the similarly low vitamin D concentration observed in Korean breast cancer patients in a study by Kim et al., in 2018 (median =12.94 ng/ml) and the high prevalence of deficiency in various studies in different at-risk Indonesian, the very low vitamin D concentration observed in our study suggest the severity of low vitamin D in Indonesian women. This information about the assay is now added under Methods in lines 170-172 and Discussion in lines 383-393.

Additional remarks

In the previous manuscript version, we mislabelled the stratified groups based on subjects’ menopausal status in Table 1. Necessary adjustments have been made in lines 4-5 of Table 1 and under Results in line 207. We confirm that this error does not affect other results presented in the manuscript.

We hope that, following our revisions, the manuscript is now suitable for publication in the PLOS ONE.

Yours sincerely,

Susanna Hutajulu, MD, PhD

Submitted filename: Response to Reviewers.docx

Click here for additional data file.

12 Jun 2022

Vitamin D status in breast cancer cases following chemotherapy: a pre and post observational study in a tertiary hospital in Yogyakarta, Indonesia

PONE-D-21-36153R2

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15 Jun 2022

PONE-D-21-36153R2

Vitamin D status in breast cancer cases following chemotherapy: a pre and post observational study in a tertiary hospital in Yogyakarta, Indonesia

Dear Dr. Hutajulu:

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