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Pharmacoeconomic Analysis of Chemotherapy Regimens in Breast Cancer Management; An Oncology Pharmacoeconomical Approach

1, 2★, 3★ Corresponding author

  1. 1Department of Pharmacy Practice, Sri Adichunchanagiri College of Pharmacy, Adichunchanagiri University, B. G. Nagara, Mandya, KarnatakaINDIA.
  2. 2Department of Pharmacy Practice, Parul University, Vadodara, GujaratINDIA.
  3. 3Department of Clinical Pharmacy, Adichunchanagiri Hospital, B G Nagara, Mandya, KarnatakaINDIA.

CORRESPONDENCE

Rajesh Venkataraman

Department of Pharmacy Practice, Parul University, Vadodara, GujaratINDIA.

rajeshvenky_research@hotmail.com

Received: 02-05-2025; Revised: 21-07-2025; Accepted: 12-09-2025.

Volume 17, Issue 4 · pp. 970-979 · 2025 · DOI: 10.5530/jyp.20250162

ABSTRACT

Background: Pharmacoeconomic evaluation of breast cancer drugs is essential due to their high treatment costs. Comparing therapeutic options and associated expenses supports better decision-making and helps optimize resource utilization. Increased clinician awareness of pharmacoeconomic principles can enhance patient outcomes while reducing overall treatment costs. This study aims to evaluate the pharmacoeconomic aspects of different therapeutic regimens used in the management of breast cancer.Materials and Methods: A 12-month prospective observational and economic study was conducted at Bharath Hospital and Institute of Oncology (BHIO), Mysore, Karnataka. A total of 204 breast cancer patients receiving chemotherapy and meeting study criteria were included. Data from patient records and questionnaires were analyzed to evaluate the Pharmacoeconomics of chemotherapy regimens.Results: A total of 204 patients (mean age 52±8.9 years) were included. Adriamycin, Cyclophosphamide, and Paclitaxel (Regimen 1) were most prescribed (34.31%). Average management cost was ₹2,93,114.67; direct and indirect costs were ₹6,16,591.7 and ₹8,374.11, respectively. Adjuvant treatment averaged ₹3,25,807, and neoadjuvant ₹15,88,77.5 Regimen 1 showed most cost-effective, with 28.57% excellent and 68.57% moderate quality of life. Costs were significantly higher in adjuvant settings.Conclusion: Breast cancer treatment places a considerable economic strain on both patients and healthcare systems. Enhancing health insurance and resource-sharing strategies is crucial to reduce this burden. Additional support services may also be needed to ease patient expenses. Conducting pharmacoeconomic assessments of available treatment options can assist policymakers in allocating healthcare resources more efficiently for cancer management.

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INTRODUCTION

Cancer is a global health concern with high morbidity and mortality (Torre et al., 2016). Defined as uncontrolled cell growth and metastasis, it caused about 9.6 million deaths in 2018, ranking as the second leading cause of death (NCI, 2021; CDC, 2021). Common cancers in men include lung, prostate, colorectal, stomach, and liver, while in women breast, colorectal, lung, cervical, and thyroid cancers predominate (CDC, 2023).

Breast cancer develops when breast cells divide uncontrollably (Alkabban and Ferguson, 2022). Invasive ductal carcinoma accounts for 70-80% of cases, while lobular carcinoma is less frequent (Breastcancer.org, 2024; WHO, 2024). It represents over one in ten new cancer cases worldwide, affecting 12.5% of women and 0.5-1% of men (Cancer.Net, 2023; City of Hope, n.d.). Incidence increases with age, from 1.5 per 100,000 in women aged 20-24 to 421.3 per 100,000 at ≥65 years (Cancer.Net, 2023). In 2023, breast cancer caused 43,700 U.S. deaths, including 530 men (Breastcancer.org, 2024; WHO, 2024).

Surgery, either lumpectomy or mastectomy, is the primary treatment, usually followed by radiotherapy or chemotherapy (Cancer Research UK, 2024). Other options include chemotherapy, endocrine therapy, targeted therapy, monoclonal antibodies, and immunotherapy, depending on tumor type and stage (Kumar et al., 2018; Burstein et al., 2014). BCS or mastectomy with axillary staging improves local control in early-stage disease (Giuliano et al., 2017). Radiation lowers recurrence (Whelan et al., 2015). Chemotherapy regimens such as AC, FEC/FAC, TC, and taxanes improve survival (EBCTCG, 2012). HER2-positive disease benefits from trastuzumab±pertuzumab (Slamon et al., 2011), while triple-negative responds to pembrolizumab (Schmid et al., 2022). Supportive and palliative care enhance quality of life (Coleman et al., 2014).

Breast cancer also creates major economic burden. Costs include screening, prevention, treatment, surgery, and indirect losses like reduced productivity and premature death (Millar and Millward, 2007). Pharmacoeconomic assessments analyze direct medical, direct non-medical, and indirect costs. Chemotherapy costs vary due to equipment and supply differences (Sohi et al., 2021). In limited insurance settings, high costs restrict care access, making cost-effectiveness analyses vital for selecting affordable regimens with equivalent outcomes (Kashyap et al., 2020). Thus, our study aimed to assess and evaluate the often-overlooked part that is pharmacoeconomic of different regimens used in the breast cancer management.

MATERIALS AND METHODS

This study is a prospective observational and economic analysis conducted over a year duration time at Bharath Hospital and Institute of Oncology Mysore, Karnataka, a multi-specialty center offering comprehensive oncology services.

Study Criteria

Patients aged 18 years or older with Breast Cancer, receiving treatment in the oncology department, and providing written informed consent after explanation of the study procedures were included. Patients under 18, those with unstable medical or psychiatric conditions, or those unwilling to share required information (direct, indirect, or non-medical costs and QoL questionnaire) were excluded.

Sampling techniques and sample size calculation

A prospective random sampling method was applied, and the sample size was calculated to enroll minimum of 204 participants, based on a 5% margin of error, 50% population proportion, 0.05 precision, and a 95% confidence interval, considering a 13% prevalence of breast cancer in India (Mehrotra and Yadav, 2022).

Data collection

Patients meeting the inclusion criteria were enrolled, and data were collected using a structured form covering demographics (name, age, gender, socio-economic status), clinical details, history, prescribed regimen (drug, dose, route, frequency, duration), drug-related problems, and payment mode. Indirect costs were recorded with a validated questionnaire. Health-related Quality of Life (QoL) was assessed using a 25-item validated tool (Cronbach’s alpha: 0.883) addressing mobility, self-care, daily activities, pain, and psychological status (File S2). QoL was classified as very poor, poor, moderate, or excellent. Direct costs came from medical bills, while indirect costs were obtained through patient interviews.

Ethical approval

The study was conducted in accordance with Institutional Human Ethics Guideline. Duly signed of written Informed Consent form (File S3) by patients are involved with no patient’s interventions. Ethical approval was obtained from the Institutional Ethics Committee, Bharath Hospital and Institute of Oncology (BHIO), Mysore (File S4).

Data Analysis

Data were verified by the oncologist and entered into Microsoft Excel, then analyzed using SPSS v25.0 (IBM) and JMP Student Edition 18. Categorical variables were summarized as frequencies and percentages, while continuous variables were presented as Mean±Standard Deviation. Direct and indirect treatment costs were compared using the Bonferroni post hoc test and independent sample t-test.

RESULTS

Demographics Characteristics of the Patients

A total of 204 female patients were enrolled, mostly aged 41-50 years (35.3%) and 51-60 years (38.2%). 70% were from urban areas and 30% from rural regions. Most belonged to the middle-income group (62.7%), followed by high-income (22.5%) and low-income (14.7%). Payment modes included SAST (53.9%), ECSI (19.6%), cash (17.2%), allied insurance (5.4%), ECHS (2.5%), and railways (1.5%).

Diagnostic methods were mainly FNAC (98.03%), PET-CT (94.11%), IHC (87.25%), and mammography (80.39%). Most patients were diagnosed at Stage IV (26.47%), followed by Stage IIA (20.58%) and Stage IIIA (20.58%), with Stage I being least common (2.94%).

The predominant type was invasive ductal carcinoma (59.80%), followed by metastatic (16.6%), infiltrating ductal (18.62%), and invasive lobular carcinoma (4%). HER2-negative tumors accounted for 62.74%, with ER and PR-negative cases at 55.88% and 57.84%, respectively.

Surgery was the Primary management (70%) followed by Chemotherapy (37%), radiation (27%), targeted therapy (26%), and hormonal therapy (13%). Regimen 1 (paclitaxel, cyclophosphamide, Adriamycin) was most used (34.31%), followed by Regimen 2 (docetaxel, cyclophosphamide; 16.66%), while Regimen 7 (eribulin) was least used (3.92%). Shown in Table 1.

Pharmacoeconomic analysis of Chemotherapy regimens of Breast Cancer

Direct Medical Cost

The mean total direct medical costs came to Rs. 636841.7. Targeted therapy costs accounted for 32.5%, followed by Surgical treatment as primary treatment for breast cancer 19.30% cost radiation therapy costs (19.06%), chemotherapy costs (14.06%), hospitalization costs (6.09%), diagnostic costs (4.7%), chemo-port placement costs (3.17%), and hormonal therapy costs (0.29%). Shown in Table 2.

Direct Non Medical and Indirect Cost

The outcome of the questionnaire applied to the 204 patients Out of which for transport 31.37% spent <500, 37.25% spent 500-1000, 17.64% spent 1000-2000 and 13.72% spent >2000. The below table shows the mode of transport to the hospital by using cars 40.19%, buses 44.11%, rented taxis 11.76% and the remaining 3.92% motorbikes. Travel time was <60 min for 33.3% of patients, 60-90 min for 23.5%, 90-120 min for 32.4%, and >120 min for 10.8%. Meal costs were <₹150 for 22.5% of patients, ₹150-300 for 43.1%, and >₹300 for 34.3%. Time at hospital was <3 hr for 34.3%, 4-7 hr for 62.7%, and >8 hr for 2.9%.

Among the subject 80 missed their work due to illness while 124 continued working. Hospital visits were accompanied by a spouse (32.4%), son (40.2%), daughter (15.7%), sibling (8.8%), or relatives (2.9%). Productivity loss was reported by 10.8% of patients, while 89.2% had none. Additional medical costs were <₹5000 for 25.5%, ₹5000-10,000 for 2.9%, ₹10,000-20,000 for 23.5%, and >₹20,000 for 48.0%. Shown in Table 3.

Comparison of Total Cost between Different regimen Among Adjuvant Setting

A Bonferroni Post hoc test was used to compare the total cost of adjuvant regimens. Result shows that Regimen 5 which contain trastuzumab has significant more of total cost when compared to other regimens in adjuvant regimens. Shown in Tables 4 and 5.

Comparison of Total Cost Between Different Regimen Among Neo Adjuvant Settings

A Bonferroni post hoc test was used to compare the total cost of neoadjuvant regimens. The results shows that Regimen 6 which contains paclitaxel and trastuzumab has significant more of total cost when compared to other neoadjuvant regimens. Shown in Tables 6 and 7.

Comparison of Total Cost Between both Adjuvant and Neoadjuvant settings

Independent sample t test displays. The mean cost of Adjuvant Chemotherapy (ACT) was ₹3,25,807.65±92,943.47, which was significantly higher compared to Neoadjuvant Chemotherapy (NACT) at ₹1,58,877.50±54,059.61. Statistical analysis (t=5.24, p=0.001) confirmed that the difference in cost between ACT and NACT was highly significant, suggesting that ACT imposes a greater financial burden on patients compared to NACT shown in Table 8.

Cost Effectivness and outcome analysis

The comparative analysis of eight breast cancer treatment regimens highlights Regimens 1 and 8 as the most cost-effective, delivering high-quality outcomes at the lowest costs. Regimen 1 achieved a combined 97.14% of excellent and moderate QOL with a minimal poor outcome (2.85%) at ₹2.5 lakh, while Regimen 8 offered 100% moderate QOL with zero poor outcomes at an even slightly lower cost. Overall, the evaluation supports Regimens 1 and 8 as optimal choices for balancing treatment quality and cost-efficiency. Shown in Table 9.

Table 1: Distribution of Demographic Details and Clinical Parameters.
Demographic Details
VariablesFrequency (n=204)Percentage
Age
Less than 40 Years167.84%
41-50 Years7235.29%
51-60 Years7838.23%
61-70 Years3416.66%
Greater than 70 Years41.96%
Gender
Male00
Female204100%
Diagnostics Parameters
FNAC20098.03%
PET CET19294.11%
IHC17887.25%
Mammogram16480.39%
USG-Breast12460.78%
Biopsy4622.54%
X Rays4220.58%
2D Echo6632.35%
Types of Breast Cancer
IDC12259.80%
IFDC3416.66%
ILC104.90%
MBC3818.62%
Stage of Breast Cancer
Stage I62.94%
Stage IIA4220.58%
Stage IIB2813.72%
Stage IIIA4220.58%
Stage IIIB2411.76%
Stage IIIC83.92%
Stage IV5426.47%
Type of Treatment
Surgery14470.58%
Chemotherapy7637.25%
Targeted therapy4421.56%
Hormonal therapy2813.72%
Radiation therapy5627.45%
Type of Surgery
MRM3818.62%
MRM+AD6833.33%
BCS104.90%
BCS+AD2813.72%
NIL6029.41%
Description of Chemotherapy regimens
RegimenName of RegimenComposition of RegimenFrequency n=274%
1AC+PACLIAdriamycin, Cyclophosphamide and Paclitaxel7034.31%
2TCDocetaxel and Cyclophosphamide3416.66%
3PACLIPaclitaxel167.84%
4GEMCI+CARBOGemcitabine and Carboplatin188.82%
5TRASTUTrastuzumab2813.72%
6PACLI+TRASTUPaclitaxel and Trastuzumab104.90%
7ERIBULINEribulin83.92%
8OTHERSZoledronic acid, Fulvestarant, CMF, TC+Pacli209.80%
Details of Economic Status
Middle-Income Group12862.74%
High-Income Group4622.54%
Low-Income Group3014.70%
Details of Residence
Urban14270%
Rural6230%
Details of Mode of Payment
SAST11053.92%
ECSI4019.60%
CASH3517.15%
Allied Insurance Company115.39%
ECHS52.45
Railways31.47
Table 2: Cost Category of Direct Medical Cost.
Cost CategoriesTotal cost (Rs)Percentage (%)
Hospitalization cost38843.136.09
Pre-medication cost4236.390.68
Diagnostic cost30434.84.7
Surgical cost12323619.3
Radiation therapy cost121405.5519.06
Hormonal therapy cost1830.420.28
Chemotherapy cost89588.614.06
Targeted therapy cost207016.8132.5
Chemo-port placement cost202503.17
Total Cost636841.7100
Table 3: Direct Non-Medical and Indirect Costs.
CategoryValueNo. of subjectsPercentage (%)
Transportation cost<500 500-1000 1000-2000 >200064 76 36 2831.37 37.25 17.64 13.72
Mode of TransportCar Bus Taxi Motor bike82 90 24 840.19 44.11 11.76 3.92
Travel time to hospital<60 min 60-90 min 90-120 min >120 min68 48 66 2233.33 23.52 32.35 10.78
Cost of meals during hospital visit<150 150-300 >30046 88 7022.54 43.13 34.31
Time spent in hospital<3 hr 4-7 hr >8 hr70 128 634.31 62.74 2.94
Absence from workYes No80 12439.21 60.78
Accompanying personSpouse Son Daughter Brother or sister other66 82 32 18 632.35 40.19 15.68 8.82 2.94
Lost ProductivityYes No22 18210.78 89.21
Other expenses<5000 5000-10000 10000-20000 >2000052 6 48 9825.49 2.94 23.52 48.03
Table 4: Types of Treatment Regimens used in Adjuvant Setting.
Type of RegimennMean costStd. Deviation
152290042.481886.82
22828775.4174286.27
310279265.9652906.4
414272776.0999868.99
518618112.54155461.79
66432255.12161965.3
74378521.4684766.24
812306712.2832406.02
Total144325807.6592943.47
Table 5: Comparison of Cost of different regimens among Adjuvant Regimen.
RegimenRegimenMean diff.Std. Errort-testp-value95% CI lower limit95% CI upper limit
122266.9931918.0140.071-102390.01106923.99
310776.4447018.170.231-143392.95164945.83
417266.3140999.4310.421-117168.04151700.66
5-328070.1337237.683-8.81<0.001-450169.97-205970.3
6-142212.7258709.482-2.420.515-334717.1250291.69
7-88479.0670653.535-1.251-320147.21143189.09
8-16669.8858709.482-0.281-209174.29175834.53
238509.4550163.0960.171-155971.94172990.84
414999.3244571.080.341-131146.23161144.87
5-330337.1341137.244-8.03<0.001-465223.36-195450.89
6-144479.7161257.091-2.360.604-345337.5556378.14
7-90746.0572784.269-1.251-329400.73147908.63
8-18936.8761257.091-0.311-219794.72181920.97
346489.8756378.4530.121-178371.25191350.99
5-338846.5853704.949-6.31<0.001-514941.46-162751.69
6-152989.1670316.285-2.180.937-383551.4877573.17
7-99255.580557.424-1.231-363397.83164886.83
8-27446.3270316.285-0.391-258008.65203116.01
45-345336.4548522.846-7.12<0.001-504439.57-186233.33
6-159479.0366442.644-2.40.545-377339.9558381.89
7-105745.3777199.376-1.371-358876.89147386.14
8-33936.1966442.644-0.511-251797.11183924.73
56185857.4264189.6922.90.147-24616.23396331.06
7239591.0875269.0863.180.064-7211.15486393.3
8311400.2664189.6924.85<0.001100926.61521873.9
6753733.6687895.3560.611-234469.25341936.56
8125542.8478615.9961.61-132233.68383319.35
7871809.1887895.3560.821-216393.73360012.09
Table 6: Types of Regimens used in Neoadjuvant Settings.
Type of RegimennMean CostStd. Deviation
118135596.333347.69
2689917.327209.38
3657894.45130088.93
4457181.727444.82
510309056.2777730.89
64367485.3818652.88
74169806.8886758.38
8884082.0471243.95
Total60158877.5054059.61
Table 7: Comparison of Total Cost Between Different Regimen Among Neoadjuvant Settings.
RegimenRegimenMean diff.Std. Errort-testp-value95% CI lower limit95% CI upper limit
12-3576.9844134.073-0.081-163159.48156005.53
3-122298.1544134.073-2.770.33-281880.6537284.35
5-124889.7336925.215-3.380.083-258406.038626.57
6-231889.0851751.788-4.480.006-419016.15-44762.01
7-34210.5851751.788-0.661-221337.65152916.49
851514.2651751.78811-135612.81238641.33
23-118721.1754052.98-2.21-314169.0376726.68
5-121312.7548346.455-2.510.583-296126.6353501.12
6-228312.160433.068-3.780.033-446829.44-9794.76
7-30633.660433.068-0.511-249150.94187883.74
855091.2460433.0680.911-163426.1273608.58
35-2591.5848346.455-0.051-177405.45172222.3
6-109590.9360433.068-1.811-328108.27108926.42
788087.5760433.0681.461-130429.77306604.92
8173812.4160433.0682.880.262-44704.93392329.76
41-78414.5851751.788-1.521-265541.65108712.49
2-81991.5660433.068-1.361-300508.9136525.78
3-200712.7360433.068-3.320.095-419230.0817804.61
5-203304.3155387.822-3.670.043-403578.76-3029.86
6-310303.6666201.11-4.690.004-549677.42-70929.9
7-112625.1666201.11-1.71-351998.92126748.6
8-26900.3266201.11-0.411-266274.08212473.44
5790679.1555387.8221.641-109595.3290953.6
8176403.9955387.8223.180.13-23870.46376678.44
67197678.566201.112.990.204-41695.26437052.26
8283403.3466201.114.280.0144029.58522777.1
7885724.8466201.111.291-153648.92325098.6
Table 8: Comparison of Total Cost Between Adjuvant and Neoadjuvant Settings.
Types of TherapynMean Total costSDtp Value
ACT144325807.6592943.475.240.001*
NACT60158877.5054059.61
Table 9: Details of Pharmacoeconomic evaluation of breast cancer regimens.
RegimensName of RegimensCost Effective analysisCost outcome analysis
Average total direct CostAverage total indirect CostAverage overall CostPoor QOLModerate QOLExcellentQOLRankCommentHigh QoL
1AC+PACLI242624.837702.85250327.692.85%68.57%28.57%1stHigh QoL, Low Cost97.14%
2TC253386.88164.70261551.50.00%88.20%11.76%5thGood QoL, Moderate Cost99.96%
3PACLI259041.6512210271251.6512.50%75%12.50%7thAcceptable QoL, average cost87.50%
4GEMCI+CARBO2563248542.22264866.211.11%88.88%0.00%6thHigh QoL, slightly higher poor outcome88.88%
5TRASTU481674.58714.28490388.7814.28%50%35.71%8thMost expensive, poorest QoL85.71%
6PACLI+TRASTU39947.226400406347.2220%80%0.00%4thBest QoL, higher cost100%
7ERIBULIN266064.178100274164.170.00%100%0.00%3rdExcellent QoL, slightly higher cost100%
8Zoledronic acid, Fulvestarant, CMF, TC+Pacli241740.78480250220.70.00%100%0.00%2ndBest QoL, Low Cost100%

DISCUSSION

Breast cancer is one of the most common cancers in women and leading factor of cancer-related fatalities, placing a heavy financial strain on healthcare systems. This prospective observational study assessed the economic burden of various chemotherapy regimens used in breast cancer treatment (National Cancer Institute [NCI], 2021; Centers for Disease Control and Prevention [CDC], 2021; Breastcancer.org, 2023). A total of 204 patients were included over six months, with an average age of 52±8.9 years. These findings are in line with those of Singh et al., (2013), who reported a mean age of 48.67±8.32 years.

Most of the participants were from middle-income households. Invasive Ductal Carcinoma (IDC) was the predominant type, followed by Metastatic Breast Cancer (MBC), Infiltrating Ductal Carcinoma (IFDC), and Invasive Lobular Carcinoma (ILC).

Eight chemotherapy protocols were identified, with Adriamycin, Cyclophosphamide, and Paclitaxel being the most frequently used combination. This aligns with the report by Roy et al., (2012), who noted better disease control and improved quality of life with this regimen.

The mean direct cost per patient was ₹616,591.7, with targeted therapy accounting for 33.33% of this expenditure and premedication costs being the lowest. Transportation and meal expenses averaged ₹6,530.98 and ₹1,843.13, respectively, and 40.19% of patients primarily traveled by car. Comparable research by Afkar et al., (2021) reported mean direct costs of $3,960 in public hospitals and $10,050 in private hospitals. Lidgren et al., (2007) documented costs of 280,000 SEK ($39,000) for patients under 65 and 351,000 SEK ($48,900) during the first year after recurrence. Similarly, Kim et al., (2015) found that the total socioeconomic costs associated with breast cancer increased by 40.7%, from $668.49 million in 2007 to $940.75 million in 2010, with direct medical expenses increasing from $278.71 million to $399.22 million.

Cost-effectiveness analysis showed that Regimen 1 had an average total cost of ₹250,327.69, with 2.85% of patients reporting low quality of life, 68.75% moderate quality of life, and 28.57% high quality of life (Heidary et al., 2023).

CONCLUSION

This research analyzes the financial implications of breast cancer therapy. The treatment process often leads to significant expenses, with major cost drivers being surgical interventions and targeted medications. Among the regimens reviewed, AC+PACLI was most commonly administered and demonstrated both therapeutic effectiveness and acceptable cost benefits. A notable disparity was identified between Adjuvant Chemotherapy (ACT) and Neoadjuvant Chemotherapy (NACT), where ACT generated higher treatment-related costs. Many individuals managed part of their expenses through government-supported funding schemes, which reduced personal financial pressure. The results underline the need for strategies that reduce the monetary burden on patients and reveal how different chemotherapy approaches influence quality of life. Although moderate QOL was frequently reported, there was wide variation among patients, indicating the necessity for tailored and patient-oriented care plans. Detailed pharmacoeconomic evaluations of available regimens will assist policymakers in distributing healthcare resources efficiently and improving the overall management of breast cancer care.

Acknowledgement

We acknowledge and appreciate Sri Adichunchanagiri College of Pharmacy, Adichunchanagiri University, BG Nagara and Bharath Hospital Institute of Oncology, Mysore for the cooperation to conduct this study. Also, we thank patients participated in the study for their support.

Conflict of Interest

The authors declare that there is no conflict of interest.

Ethics Statement

Informed consent was obtained from all subjects involved in the study.

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Haidary, B. I., Venkataraman, R., & Pasha, I. (2025). Pharmacoeconomic Analysis of Chemotherapy Regimens in Breast Cancer Management; An Oncology Pharmacoeconomical Approach. Journal of Young Pharmacists, 17(4), 970-979. https://doi.org/10.5530/jyp.20250162

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