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Availability of anticancer medicines in public and private sectors, and their affordability by low, middle and high-income class patients in Pakistan

BMC Cancer201818:14

https://doi.org/10.1186/s12885-017-3980-3

Received: 10 August 2017

Accepted: 22 December 2017

Published: 3 January 2018

Abstract

Background

Availability and affordability of anticancer medicines is a matter of great concern especially for low and middle income countries e.g., Pakistan. Prime focus of this study was to evaluate the availability of anticancer medicines in public and private sectors, and their affordability among patients with different income levels.

Methods

A descriptive, cross-sectional survey was conducted in 22 cancer care hospitals (18 public hospitals and 04 private hospitals) and 44 private pharmacies in Punjab, Pakistan. All (n = 4400) participants were ≥18 years of age. Data were collected at different intervals and analyzed by using Statistical Packages for Social Sciences (IBM SPSS Statistics for Windows, Version 21.0. Armonk, NY: IBM Corp.)

Results

A total of 4913 patients were approached, and 4400 responded to the survey (response rate = 89.6%). Non-hodgkin lymphoma (12.3%), breast cancer (8.6%), and leukemia (7.6%) were the most prevailing cancers. Conventional medicines like cisplatin, cyclophosphamide, and etoposide were the most prescribed medicines. Oncologists were reluctant to prescribe newer anticancer medicines due to high prices. Originator brands (OBs) were more readily available (52.5%) but less affordable (53.4%); whereas, lowest price generics (LPGs) were less available (28.1%) but more affordable (67.9%). Anticancer medicines were more affordable by the high income class patients than the low income class patients.

Conclusion

The availability of both OBs and LPGs was greater at private hospitals and pharmacies as compared to public hospitals. The high income class had more affordability of both OBs and LPGs; however, LPGs were more affordable for all income classes.

Keywords

CancerAnticancer medicinesAvailabilityAffordabilityOriginator brandLowest price generics

Background

Cancer is amongst the most expensive and lethal non-communicable diseases globally [1]. In 2016, the most prevailing cancers in Pakistan were breast cancer (21.8%), leukemia (6.3%), hodgkin lymphomas (4.9%) and non-hodgkin lymphoma (4.7%) of the total reported cases [2]. However, the actual prevalence of cancer may be greater than this due to lack of availability of proper registry system in Pakistan. Presently, the management of cancer mainly relies upon the availability and affordability of anticancer medicines. In recent years, the emergence of newer anticancer medicines has rapidly and substantially caused an expansion not only in the repertoire but also in the average per month cost of these therapeutic agents. Cancer treatment demands substantial cost i.e., ranging from $4500 to >$10,000 per month [3, 4], thus posing huge burden on patient and healthcare system.

The heath sector of Pakistan is regulated by the provincial governments. The government health coverage is inadequate and negligible in terms of public health insurance and employer benefits. Therefore, majority of the population have to bear their health expenses on their own [5]. In 2004, a “National Action Plan for Prevention and Control of Non-Communicable Diseases and Health Promotion” [6] was developed with the collaboration of World Health Organization (WHO). This plan was designed to cover various aspects e.g., capacity enhancement of healthcare system, up-gradation of cancer registration, and making an organizational network at local, provincial and national levels. For accomplishing all such goals the WHO cancer coordinator for Pakistan has also developed a National Cancer Control Council. Because of financial constraints the government of Pakistan was unable to contribute in this program and all strategies were merely dependent on the funding from the WHO [7].

Several factors which affect the accessibility of any therapeutic agent have an impact on patient’s pocket and subsequently cause a considerable delay in the commencement of therapy [8]. Some of these factors may include (a) the extent to which a drug is reimbursed or subsidized, (b) the allocation of budget by the public sector for the purchase of medicines, (c) licensing of medicines for manufacturing and import, (d) implication of evidence-based guidelines, and (e) procurement by the government hospitals and insurers [9]. The need of pre-approval for the provision of subsidized medicines and “mark-up values” by the hospitals, wholesale dealers, pharmacists, and physicians may also contribute in making the prices extremely high [10, 11].

Pricing of medicines in Pakistan are regulated by the Drug Regulatory Authority of Pakistan (DRAP) which works under Federal government, though no transparent price calculation formula is mentioned in the Drugs Act, 1976 [12]. According to a survey conducted by the WHO, the prices of originator brands (OBs) and lowest-price generics (LPGs) were 3.36 and 2.26 times more than the international retail price in Pakistan. Moreover, a sudden rise in price of 15% in November 2013 further burdened the patients [13].

The affordability of anticancer medicines is a grave problem for most of the Pakistani patients. Since 45.5% of the Pakistani population lives below the poverty line [14] so the expenses pertaining to healthcare are unaffordable for an average income person. The availability and affordability of anticancer medicines in Pakistan are surrounded by evidence based three common issues which include: (i) formulary limitations; anticancer medicines have not been mapped in the form of formulary, (ii) actual availability; inadequate provision of health services due to shortage or poor availability of medicines [13, 15] and (iii) the barriers like resources and affordability associated with the access of newer anticancer medicines. Moreover, inflation (Consumer Price Index (CPI) inflation: 1.3% on year-on-year basis in September 2015) and low affordability leads to an underuse of effective medicines. Despite of several measures adopted by the Ministry of National Health Services, regulations and coordination of affordability of medicines is still a problem owing to the expansion of OBs, and ongoing variation and inconsistency of prices of medicines in the country. The availability of essential generic medicines is only 15% and 31% in the public and private sector healthcare facilities, respectively. Even though the LPGs are used but still the cost of treatment for chronic illnesses is unaffordable for middle-income and low-income people of Pakistan [1618]. This holds true not only for Pakistan but for other countries as well. A study conducted across 49 European countries elucidated that there are disparities in the availability of cancerous medicines, which are responsible for their inequitable access [19].

The unavailability or unaffordability issues would not only aggravate the underlying disease but also lead to the inequities between the patients. Up till now, numerous studies focusing on the gravity of underlying problems have been conducted in multiple countries, excluding Pakistan. The aim of current study is to assess the availability of anticancer medicines in public and private sectors, and their affordability by high, middle, and low-income class patients.

Methods

Study design and settings

A descriptive, cross-sectional study design was employed. There are total 23 (18 public and four private sector tertiary care) hospitals in Punjab province of Pakistan which provide services to cancer patients. Out of these 23 hospitals, seven were specialized cancer-care hospitals. One hospital was excluded from the survey because it provides services solely to the pediatrics. Survey was carried out in 22 cancer-care hospitals and 44 private pharmacies in Punjab, a province of Pakistan. Data were collected from the pharmacies and cancer patients attending selected hospitals and evaluated according to the objectives of study.

Study population and sample size

The population under study was cancer patients aged ≥18 years, who visited the selected cancer-care hospitals for routine examinations. According to the latest Pakistani census, the population of the surveyed province consisted of 101,391,000 individuals [20]. The minimum sample size was 4147 as calculated by the Raosoft sample size calculator [21] based on cancer prevalence in Pakistan. With contingency of 5% for non-response and inappropriate responses, the final sample was calculated to be 4400.

Data collection and outcome variables

A total of 4913 cancer patients were approached over a six month period (1st January, 2017 to 30th June, 2017), 4400 patients consented to participate (response rate = 89.6%). Data was collected at different intervals from the selected cancer-care hospitals.

A data collection form was designed for this study which consisted of three main parts: (1) socio-demographic characteristics, (2) diagnosis and (3) recommended medicines. The reliability of the survey tool was assessed by conducting a pilot study. Piloting was undertaken using data from 100 patients. After piloting, the data collection form was restructured.

Measurements

Socio-demographic characteristics

Socio-demographic characteristics given in Table 1 were recorded for each participant. Those participants who were retired (taking pension) or running a business were classified as employed and housewives were considered as unemployed. The data was obtained through face to face questioning of patients. To avoid biasness, the data regarding employment status and income level of the participants was validated by using online tax payer verification system of Federal Board of Revenue (FBR) [22].

Diagnosis and prescribing pattern

The type of cancer and all the medicines present in each prescription were noted on a pre-designed performa sheet. Anticancer medicines having more than one active ingredient were not evaluated. The most commonly prescribed anticancer medicines were categorized according to the prescribing trend; low (prescribed to <5% of the selected patients), medium (prescribed to ≥5% of the selected patients but <10%) and high (prescribed to >10% of the selected patients).

Availability of anticancer medicines and their per month cost

Forty anticancer medicines were chosen for the survey. These anticancer medicines were selected on the basis of, (a) pilot study in which local needs and cancer burden was assessed, (b) literature review, and (c) the opinions of various experts. During the survey, if medicines were present at the pharmacy settings then they considered as available.

The availability of anticancer medicines was evaluated in public hospitals, private hospitals, and private pharmacies. For the assessment of prices associated with these medicines, Pharmaguide 2016, was consulted [23]. The process of data collection was done by trained pharmacy students under the supervision of survey manager and principal investigator. Principal investigator checked the collected and completed Performa’s on weekly basis. If any information was found missing then a follow up visit to the respective setting was conducted. Before initiation of the process of data collection, medical superintendents/directors were contacted by the principal investigator. In this way a good cooperation was established between the team of investigators and the staff members of the selected settings. To avoid report biasness (e.g. up coding, less availability of medicine to gain attention for budget increase, etc.), the drugs were said to be available if they were present in the settings and the patients could avail them on prescription. Also, the formulary list and purchase records were assessed for data validation. For each medicine, data were collected on the basis of per unit price, and availability of OBs and LPGs. On the basis of standard guidelines and the recommended treatment, per unit price of anticancer agents were transformed into per month cost.

Furthermore, the following criteria were used to describe the availability of medicines:

Absent: 0% of facilities: these medicines were not found in any facility surveyed;

Low: <50% of facilities: these medicines were hard to find;

Fairly high: 50–74% of facilities: these medicines were available in many facilities;

High: >75% of facilities: good availability.

Affordability of anticancer medicines

According to the WHO and Health Action International (HAI) methodology, for the assessment of affordability we have to calculate that “the income of how many days is required to purchase the medicines for 30 days (in case of chronic condition e.g. cancer)”. Generally, if the total cost of therapy for 1 month is equal to or less than the wage of 1 day then it is said to be affordable.

A study published by Rasha Khatib et al. [24] defined it as; “if the combined cost of therapy is <20% of household capacity-to-pay then it can be considered as affordable.” In this study this concept modified and affordability was measured for each prescribed medicine by low, middle, and high income class of patients through this formula;
$$ Affordability=\frac{\%\ast \mathrm{of}\ \mathrm{household}\ \mathrm{capacity}\ \mathrm{to}\ \mathrm{pay}}{Per\ month cost of the medicine}\times 100 $$

* If 1 medicine was prescribed it was 20%, if 2 medicines were prescribed it was 10%, if 3 medicines were prescribed it was 6.7% and if 4 medicines were prescribed it was 5% of household capacity to pay.

Statistical analysis

Statistical Package for Social Sciences (IBM, SPSS Statistics for Windows, version 21.0. Armonk, NY: IBM Corp.) was used for data analysis. Descriptive statistics such as frequencies, percentages, and mean were used to present the data.

Results

Four thousand four hundred cancer patients were investigated in the study. Just over half (55.4%, n = 2436) of the participants were male, and 39.3% (n = 1731) were aged 18–39 years. 67.9% (n = 2987) were married, 67.8% (n = 2981) had secondary education level and 40.7% (n = 1791) had income status of upper class. 61.9% (n = 2723) respondents were employed and three-quarters (73.2%, n = 3291) were urban residents (Table 1).
Table 1

Characteristics of the study population

Variables

Male (n = 2436)

Female (n = 1964)

Total (n = 4400)

n (%)

n (%)

n (%)

Age (years)

18–39

959 (39.4)

772 (39.3)

1731 (39.3)

40–64

780 (32.0)

866 (44.1)

1646 (37.4)

≥65

697 (28.6)

326 (16.6)

1023 (23.3)

Civil Status

Single

84 (3.4)

43 (2.2)

127 (2.9)

Married

1722 (70.7)

1265 (64.4)

2987 (67.9)

Widowed

370 (15.2)

514 (26.2)

884 (20.1)

Divorced

260 (10.7)

142 (7.2)

402 (9.1)

Education level

Primary (≤10 years)

503 (20.6)

0 (0.0)

503 (11.4)

Secondary (11–13 years)

1389 (57.0)

1592 (81.1)

2981 (67.8)

Tertiary (≥14 years)

544 (22.3)

372 (18.9)

916 (20.8)

Annual income

Low class (PKR0–299,999)

662 (27.2)

481 (24.5)

1143 (26.0)

Middle class (PKR300,000–999,999)

842 (34.6)

624 (31.8)

1466 (33.3)

Upper class (PKR ≥ 1,000,000)

932 (38.3)

859 (43.7)

1791 (40.7)

Employment Status

Employed

2138 (87.8)

585 (29.8)

2723 (61.9)

Unemployed

298 (12.2)

1379 (70.2)

1677 (38.1)

Residence

Rural

855 (35.1)

326 (16.6)

1181 (26.8)

Urban

1581 (64.9)

1638 (83.4)

3219 (73.2)

Number of medicines

1

67 (2.8)

157 (8)

224 (5.1)

2

1768 (72.6)

1204 (61.3)

2972 (67.5)

3

559 (22.9)

532 (27.1)

1091 (24.8)

4

42 (1.7)

71 (3.6)

113 (2.6)

The most common cancers diagnosed among participants were; non-hodgkin lymphoma (NHL) (12.3%, n = 540), breast cancer (8.6%, n = 378) and leukemia (7.6%, n = 334) (Table 2).
Table 2

Cancer cases diagnosed in the study population

Sr. No

Cancer

ICD-10

Male (n = 2436)

Female (n = 1964)

Total (n = 4400)

n (%)

n (%)

n (%)

1

Bladder

C67

42 (1.7)

32 (1.6)

74 (1.7)

2

Brain

C70–72

111 (4.6)

70 (3.6)

181 (4.1)

3

Breast

C50

378 (19.2)

378 (8.6)

4

Cervix uteri

C53

142 (7.2)

142 (3.2)

5

Colorectal

C18–21

131 (5.4)

43 (2.2)

174 (4.0)

6

Corpus uteri

C54

71 (3.6)

71 (1.6)

7

Gallbladder

C23–24

110 (4.5)

71 (3.6)

181 (4.1)

8

Hodgkin lymphoma

C81

149 (6.1)

43 (2.2)

192 (4.4)

9

Kidney

C64–66

178 (7.3)

114 (5.8)

292 (6.6)

10

Larynx

C32

111 (4.6)

70 (3.6)

181 (4.1)

11

Leukemia

C91–95

221 (9.1)

113 (5.8)

334 (7.6)

12

Lip, oral cavity

C00–08

110 (4.5)

70 (3.6)

180 (4.1)

13

Liver

C22

111 (4.6)

70 (3.6)

181 (4.1)

14

Lung

C33–34

186 (7.6)

104 (5.3)

290 (6.6)

15

Non-Hodgkin lymphoma

C82–85

363 (14.9)

177 (9.0)

540 (12.3)

16

Esophagus

C15

107 (4.4)

71 (3.6)

178 (4.0)

17

Ovary

C56

141 (7.2)

141 (3.2)

18

Pancreas

C25

111 (4.6)

70 (3.6)

181 (4.1)

19

Prostate

C61

220 (9.0)

220 (5.0)

20

Stomach

C16

65 (2.7)

43 (2.2)

108 (2.5)

21

Thyroid

C73

110 (4.5)

71 (3.6)

181 (4.1)

The most commonly prescribed anticancer medicines were: cisplatin (49.5%, n = 2177), etoposide (25.8%, n = 1137), and cyclophosphamide (19.9%, n = 877). The detailed description about the prescribed anticancer medicines is given in Table 3.
Table 3

Anticancer medicines prescribed to study participants

Sr. No

Medicine and Dose

ATC Code

f (n = 9893) %a

Trend

OB

Per month cost

LPG

Per month cost

1

Anastrozole 1 mg tab

L02BG03

71 (1.6)

Low

Anastrozole (Novartis)

6000

Femizet (Atco)

5130

2

Bicalutamide 50 mg tab

L02BB03

109 (2.5)

Low

Casodex (ICI)

12,642

Calutide (A. J. Mirza)

4308

3

Bleomycin 15 mg inj

L01 DC01

42 (1.0)

Low

Bleomycin (Pharmedic)

9960

Bemocin (Atco)

8000

4

Capecitabine 500 mg tab

L01 BC06

258 (5.9)

Medium

Xeloda (Roche)

25,000

NA

NA

5

Carboplatin 150 mg inj

L01XA02

206 (4.7)

Low

Carpsol (Pfizer)

6681

Carboplatin (Atco)

3000

6

Cisplatin 50 mg inj

L01XA01

2177 (49.5)

High

Cisplasol (Pfizer)

3099

Platosin (Pharmachemie)

1750

7

Cyclophosphamide 500 mg inj

L01AA01

877 (19.9)

High

Cyclomide (Pharmedic)

5625

Cyclophosphamide (S. Ejazuddin)

3000

8

Cyproterone Acetate 50 mg tab

G03HA01

66 (1.5)

Low

Androcur (Bayer)

3588

NA

NA

9

Cytarabine 100 mg inj

L01 BC01

342 (7.8)

Medium

Cytosar (Pfizer)

2700

Cytarabine (Highnoon)

1785

10

Dacarbazine 200 mg inj

L01AX04

74 (1.7)

Low

Duticin (Al-Habib)

2700

Darbazine (Pharmedic)

2500

11

Dactinomycin 0.5 mg inj

L01DA01

71 (1.6)

Low

Dactinomycin (Al-Habib)

28,616

Dactinofin (Pharmedic)

23,520

12

Daunomycin 20 mg inj

L01DB02

111 (2.5)

Low

Daunoblastina (Pfizer)

6750

D-Blastin (Pharmedic)

5700

13

Docetaxil 80 mg inj

L01CD02

18 (0.4)

Low

Taxotere (Sanofi aventis)

76,000

Docekebir (Oncogene)

74,400

14

Doxorubicin 50 mg inj

L01DB01

385 (8.8)

Medium

Adriblastina (Pfizer)

4495

Doxorubicin (Al- Habib)

3170

15

Epirubicin 50 mg inj

L01DB03

427 (9.7)

Medium

Farmorubicin (Pfizer)

13,270

Anthracin (Atco)

9510

16

Etoposide 100 mg inj

L01CB01

1137 (25.8)

High

Etoposide (Pfizer)

7150

Lymphoside (CCL)

4950

17

Fludarabine phosphate 50 mg inj

L01BB05

180 (4.1)

Low

Fludara (Sanofi aventis)

66,313

Fludakebir (Oncogene)

46,400

18

Flourouracil 500 mg inj

L01 BC02

502 (11.4)

High

Pharmauracil (Pharmedic)

1944

Secouracil (S. Ejazuddin)

176

19

Gemicitabine 1 g inj

L01 BC05

685 (15.6)

High

Gemzar (Eli lilly)

64,020

Gemita (Atco)

41,650

20

Hydroxyurea 500 mg cap

L01XX05

43 (1.0)

Low

Hydra (Medinet)

1200

Hydrine (Al-Habib)

1168

21

Ifosfamide I gminj

L01AA06

71 (1.6)

Low

Ifosfamin (Pharmedic)

12,000

Fosfamin (CCL)

12,000

22

Imatinibmesylate 400 mg tab

L01XE01

67 (1.5)

Low

Glivec (Novartis)

140,000

NA

NA

23

Irinotecan 100 mg inj

L01XX19

181 (4.1)

Low

Campto (Pfizer)

133,480

Irinocan (Pharmedic)

71,250

24

Lapatinib 250 mg tab

L01XE07

43 (1.0)

Low

Tykerb (GSK)

201,650

NA

NA

25

Letrozole 2.5 mg tab

L02BG04

71 (1.6)

Low

Femara (Novartis)

8720

Letara (A.J. Mirza)

5100

26

Mercaptopurine 50 mg tab

L01BB02

111 (2.5)

Low

Mercaprine (Pharmedia)

741

Purinetone (Al- Habib)

630

27

Methotrexate 10 mg tab

L01BA01

72 (1.6)

Low

Emthexate (Pharmachemie)

817

Unitrexate (Al-Habib)

410

28

Mitomycin 10 mg inj

L01 DC03

71 (1.6)

Low

Mitocin (Pharmedic)

2256

Mitomycin (S.Ejazuddin)

232

29

Mitoxantrone 20 mg inj

L01DB07

43 (1.0)

Low

Mitoxantrona (Atco)

4000

NA

NA

30

Nilotinib 200 mg cap

L01XE08

43 (1.0)

Low

Tasigna (Novartis)

456,000

NA

NA

31

Oxalplatin 100 mg inf

L01XA03

288 (6.5)

Medium

Oxitan (Atco)

60,000

Eloxatin (Sanofi aventis)

52,500

32

Paclitaxel 260 mg inf

L01CD01

71 (1.6)

Low

Intaxel (Atco)

34,600

Paclixil (A.J. Mirza)

34,600

33

Pazopanib 400 mg tab

L01XE11

67 (1.5)

Low

Votrient (GSK)

176,666

NA

NA

34

Sorafenib 200 mg tab

L01XE05

43 (1.0)

Low

Nexavar (Bayer)

465,600

NA

NA

35

Sunitinib 50 mg cap

L01XE04

67 (1.5)

Low

Sutent (Pfizer)

392,640

NA

NA

36

Tamoxifen 20 mg tab

L02BA01

71 (1.6)

Low

Tamox (Pharmedic)

600

Tamooxe (Al-Habib)

450

37

Thalidomide 100 mg cap

L04AX02

43 (1.0)

Low

Thalido(Atco)

6000

NA

NA

38

Vinblastine 10 mg inj

L01CA01

42 (1.0)

Low

Velbastine (Al-Habib)

4165

Vinblas (Pharmedic)

2800

39

Vincristine 2 mg inj

L01CA02

522 (11.9)

High

Pharmacristine (Pharmedic)

1580

Vincristine Gador (Seignior)

1124

40

Vinorelbine 50 mg inj

L01CA04

71 (1.6)

Low

Vinelbine (Atco)

33,480

Vinkebir (Oncogene)

33,480

aPercentages given with respect to the total sample size of patients. ATC = Anatomical Therapeutic Chemical; f = Frequency; OB = Originator brand; LPG = Lowest price generic; NA = Not available. Note: The specialists were reluctant to prescribe medicines such as bevacizumab, cabazitaxel, cetuximab, erlotinib, idarubicin, pemetrexed, rituximab, ruxolitinib, temozolomide, topotecan, and trastuzumab due to their much higher prices

Availability of anticancer medicines (originator brands and lowest price generics)

The mean availability of anticancer medicines in both public and private sectors was found to be 52.5% for OBs, while 28.1% for LPGs. Furthermore, study revealed a fairly high availability for OBs while generally low availability for LPGs. The availability of Fluorouracil (97%), Etoposide (95.5%), Methotrexate (95.5%) and Tamoxifen (95.5%) was maximal among the OBs; whereas, Gemicitabine (81.1%), Bleomycin (56.1%) and Doxorubicin (56.1%) had the highest availability amongst LPGs in all study settings (see Table 4).
Table 4

Availability of anticancer medicines in public and private sectors in Punjab, Pakistan

Sr. No

Medicine and Dose

Public hospitals (n = 18)

Private hospitals (n = 4)

Private pharmacies (n = 44)

All (n = 66)

OB

LPG

OB

LPG

OB

LPG

OB

LPG

1

Anastrozole 1 mg tab

0 (0.0)

0 (0.0)

1 (25.0)

0 (0.0)

4 (9.1)

2 (4.5)

5 (7.6)

2 (3.0)

2

Bicalutamide 50 mg tab

0 (0.0)

0 (0.0)

1 (25.0)

0 (0.0)

3 (6.8)

1 (2.3)

4 (6.1)

1 (1.5)

3

Bleomycin 15 mg inj

10 (55.6)

8 (44.4)

4(100)

2 (50.0)

41 (93.2)

27 (61.4)

55 (83.3)

37 (56.1)

4

Capecitabine 500 mg tab

4 (22.2)

NA

4 (100)

NA

21 (47.7)

NA

29 (44.0)

NA

5

Carboplatin 150 mg inj

13 (72.2)

5 (27.8)

4(100)

1 (25.0)

33 (75.0)

29 (65.9)

50 (76.0)

35 (53.0)

6

Cisplatin 50 mg inj

8 (44.4)

9 (50.0)

3 (75.0)

0 (0.0)

43 (97.7)

11 (25.0)

54 (82.0)

20 (30.3)

7

Cyclophosphamide 500 mg inj

15 (83.3)

3 (16.7)

4 (100)

0 (0.0)

41 (93.2)

9 (20.5)

60 (91.0)

12 (18.2)

8

Cyproterone Acetate 50 mg tab

7 (38.9)

NA

4 (100)

NA

39 (88.6)

NA

50 (76.0)

NA

9

Cytarabine 100 mg inj

3 (16.7)

0 (0.0)

3 (75.0)

1 (25.0)

34 (77.3)

7 (15.9)

40 (61.0)

8 (12.1)

10

Dacarbazine 200 mg inj

4 (22.2)

1 (5.6)

2 (50.0)

1 (25.0)

27 (61.4)

13 (29.5)

33 (50.0)

15 (22.7)

11

Dactinomycin 0.5 mg inj

8 (44.4)

2 (11.1)

3 (75.0)

1 (25.0)

42(95.5)

31 (70.5)

53 (80.3)

34 (51.5)

12

Daunomycin 20 mg inj

2 (11.1)

0 (0.0)

1 (25.0)

1 (25.0)

16(36.4)

11 (25.0)

19 (29.0)

12 (18.2)

13

Docetaxil 80 mg inj

7 (38.9)

0 (0.0)

3 (75.0)

0 (0.0)

33(75.0)

7 (15.9)

43 (65.1)

7 (10.6)

14

Doxorubicin 50 mg inj

14 (77.8)

4 (22.2)

4 (100)

2 (50.0)

44(100)

31(70.5)

62 (94.0)

37 (56.1)

15

Epirubicin 50 mg inj

2 (11.1)

3 (16.7)

4 (100)

1 (25.0)

14(31.8)

9 (20.5)

20 (30.3)

13 (19.7)

16

Etoposide 100 mg inj

15 (83.3)

0 (0.0)

4 (100)

0 (0.0)

44(100)

13 (29.5)

63 (95.4)

13 (19.7)

17

Fludarabine phosphate 50 mg inj

0 (0.0)

0 (0.0)

4 (100)

1 (25.0)

11(25.0)

4 (9.9)

15 (23.0)

5 (7.6)

18

Flourouracil 500 mg inj

16 (88.9)

0 (0.0)

4 (100)

2 (50.0)

44(100)

19 (43.2)

64 (97.0)

21 (31.8)

19

Gemicitabine 1 g inj

5 (27.8)

11 (61.1)

4 (100)

2 (50.0)

31(70.5)

41 (93.2)

40 (61.0)

54 (81.8)

20

Hydroxyurea 500 mg cap

7 (38.9)

0 (0.0)

3 (75.0)

0 (0.0)

23(52.3)

11 (25.0)

33 (50.0)

11 (16.7)

21

Ifosfamide I gminj

5 (27.8)

2 (11.1)

2 (50.0)

0 (0.0)

19(42.3)

21 (47.7)

26 (39.4)

21 (31.8)

22

Imatinibmesylate 400 mg tab

0 (0.0)

NA

3 (75.0)

NA

15(34.1)

NA

18 (27.3)

NA

23

Irinotecan 100 mg inj

0 (0.0)

0 (0.0)

2 (50.0)

0 (0.0)

11(25.0)

10 (22.7)

13 (20.0)

10 (15.2)

24

Lapatinib 250 mg tab

0 (0.0)

NA

2 (50.0)

NA

13(29.6)

NA

15 (23.0)

NA

25

Letrozole 2.5 mg tab

0 (0.0)

0 (0.0)

2 (50.0)

0 (0.0)

16(36.4)

8 (18.2)

18 (27.2)

8 (12.1)

26

Mercaptopurine 50 mg tab

13 (72.2)

3 (16.7)

4 (100)

0 (0.0)

41(93.2)

11 (25.0)

58 (88.0)

14 (21.2)

27

Methotrexate 10 mg tab

15 (83.3)

1 (5.6)

4 (100)

1 (25.0)

44(100)

19 (43.2)

63 (95.4)

21 (31.8)

28

Mitomycin 10 mg inj

2 (11.1)

0 (0.0)

2 (50.0)

1 (25.0)

31(70.5)

12 (27.3)

35 (53.0)

13 (19.7)

29

Mitoxantrone 20 mg inj

0 (0.0)

NA

3 (75.0)

NA

18 (40.9)

NA

21 (32.0)

NA

30

Nilotinib 200 mg cap

0 (0.0)

NA

3 (75.0)

NA

19 (43.2)

NA

22 (33.3)

NA

31

Oxaliplatin 100 mg inf

1 (5.6)

0 (0.0)

2 (50.0)

2 (50.0)

21 (47.7)

11 (25.0)

24 (36.4)

13 (19.7)

32

Paclitaxel 260 mg inf

11 (61.1)

4 (22.2)

3 (75.0)

1 (25.0)

44 (100)

23 (52.3)

58 (88.0)

28 (42.4)

33

Pazopanib 400 mg tab

0 (0.0)

NA

1 (25.0)

NA

4 (9.1)

NA

5 (7.6)

NA

34

Sorfenib 200 mg tab

0 (0.0)

NA

1 (25.0)

NA

5(11.4)

NA

6 (9.1)

NA

35

Sunitinib 50 mg cap

0 (0.0)

NA

0 (0.0)

NA

3 (6.8)

NA

3 (4.5)

NA

36

Tamoxifen 20 mg tab

15 (83.3)

2 (11.1)

4 (100)

2 (50.0)

44(100)

16 (36.4)

63 (95.4)

20 (30.3)

37

Thalidomide 100 mg cap

4 (22.2)

NA

4 (100)

NA

25 (56.8)

NA

33 (50.0)

NA

38

Vinblastine 10 mg inj

9 (50.0)

3 (16.7)

4 (100)

0 (0.0)

31(70.5)

19 (43.2)

44 (67.0)

34 (51.5)

39

Vincristine 2 mg inj

11 (61.1)

2 (11.1)

3 (75.0)

0 (0.0)

33 (75.0)

23 (52.3)

47 (71.2)

25 (37.9)

40

Vinorelbine 50 mg inj

0 (0.0)

0 (0.0)

2 (50.0)

2 (50.0)

21 (47.7)

11 (25.0)

23 (35.0)

13 (19.7)

Total

31.4%

11.7%

71.9%

20.0%

59.4%

34.9%

52.5%

28.1%

OB = Originator brand; LPG = Lowest price generic; NA = Not available

Affordability at different income levels

The affordability of anticancer medicines (OBs and LPGs) by high, middle, and low-income class patients is listed in Table 5. Patients with high income level could afford the expenditures on anticancer medicines; reverse was true for low income level patients. The most affordable LPGs (afforded by 100% patients) for low income class patients include Cytarabine, Flourouracil, Mercaptopurine, Methotrexate, Mitomycin and Tamoxifen, respectively.
Table 5

Affordability of anticancer medicines by high, middle and low-income class patients in Punjab, Pakistan

Sr. No.

Medicine and Dose

OB

Overall OB

LPG

Overall LPG

Overall both (OB + LPG)

High

Middle

Low

High

Middle

Low

1

Anastrozole 1 mg tab

100

50.1

18.3

71.5

100

68.3

20.6

63.2

68.2

2

Bicalutamide 50 mg tab

100

28.2

12.4

48.9

100

100

73.8

93.3

66.4

3

Bleomycin 15 mg inj

68.3

18.1

6.5

27.8

78.8

46.6

15.4

46.9

36.0

4

Capecitabine 500 mg tab

61.9

25.0

8.1

35.5

NA

NA

NA

NA

35.5

5

Carboplatin 150 mg inj

100

93.1

32.7

79.3

100

100

77.1

93.6

85.0

6

Cisplatin 50 mg inj

100

100

60

91.6

100

100

97.5

99.3

94.4

7

Cyclophosphamide 500 mg inj

100

65.5

28.0

70.5

100

95.9

57

86.6

77.0

8

Cyproterone Acetate 50 mg tab

100

99.5

43.8

84.5

NA

NA

NA

NA

84.5

9

Cytarabine 100 mg inj

100

100

69.9

92.5

100

100

100

100

94.7

10

Dacarbazine 200 mg inj

100

77.8

53.6

78.3

100

100

67.9

90

83.4

11

Dactinomycin 0.5 mg inj

100

42.6

14.7

66.1

100

51.8

17.8

56.4

62.3

12

Daunomycin 20 mg inj

100

50.3

15.7

58.1

100

100

43.3

85.6

69.0

13

Docetaxil 80 mg inj

31.8

5.5

3.2

15.1

NP

NP

NP

NP

15.1

14

Doxorubicin 50 mg inj

100

62.5

27.8

68.7

100

93.5

39.5

80.3

73.0

15

Epirubicin 50 mg inj

75.3

28.6

9.0

44.2

96.4

38.1

19.1

55.3

48.6

16

Etoposide 100 mg inj

100

77.4

31.0

74.6

100

92.4

43.9

82.1

77.6

17

Fludarabine phosphate 50 mg inj

30.1

8.2

2.8

15.9

40.3

11.1

5.1

2.7

17.8

18

Flourouracil 500 mg inj

100

100

60.9

90.6

100

100

100

100

94.4

19

Gemicitabine 1 g inj

21.3

9.7

3.5

13.2

32.4

13.5

5.2

18.1

15.1

20

Hydroxyurea 500 mg cap

100

100

100

100

NP

NP

NP

NP

100

21

Ifosfamide I gminj

62.9

29.5

9.1

42.3

62.9

29.2

8.8

33.5

38.8

22

Imatinibmesylate 400 mg tab

7.2

2.4

0.8

3.6

NA

NA

NA

NA

3.6

23

Irinotecan 100 mg inj

6.7

2.2

1.0

3.8

11.6

4.4

2.1

6.5

4.9

24

Lapatinib 250 mg tab

8.0

3.0

1.0

5.1

NA

NA

NA

NA

5.1

25

Letrozole 2.5 mg tab

86.5

40.7

12.6

58.3

100

68.7

20.7

63.3

60.3

26

Mercaptopurine 50 mg tab

100

100

100

100

100

100

100

100

100

27

Methotrexate 10 mg tab

100

100

100

100

100

100

100

100

100

28

Mitomycin 10 mg inj

100

100

48.5

89.2

100

100

100

100

93.5

29

Mitoxantrone 20 mg inj

100

100

52.5

90.1

NA

NA

NA

NA

90.1

30

Nilotinib 200 mg cap

2.2

0.9

0.3

1.4

NA

NA

NA

NA

1.4

31

Oxalplatin 100 mg inf

14.5

5.8

2.0

8.2

18.0

6.6

3.5

10.3

9.1

32

Paclitaxel 260 mg inf

23.9

8.5

4.6

15.6

23.9

14.6

5.0

14.5

15.1

33

Pazopanib 400 mg tab

14.8

3.5

1.4

6.8

NA

NA

NA

NA

6.8

34

Sorafenib 200 mg tab

6.3

3.2

1.1

4.3

NA

NA

NA

NA

4.3

35

Sunitinib 50 mg cap

6.7

1.6

0.6

3.1

NA

NA

NA

NA

3.1

36

Tamoxifen 20 mg tab

100

100

100

100

100

100

100

100

100

37

Thalidomide 100 mg cap

100

67.7

24.3

75.1

NA

NA

NA

NA

75.1

38

Vinblastine 10 mg inj

100

43.2

15.6

50.5

100

100

43.9

81.3

63.7

39

Vincristine 2 mg inj

100

100

85.2

96.3

100

100

99.4

99.8

97.6

40

Vinorelbine 50 mg inj

100

8.7

4.8

54.6

100

15.1

5.1

39.2

48.5

Total

70.7

49.1

29.2

53.4

84.4

69.6

49.0

67.9

55.5

OB = Originator brand; LPG = Lowest price generic; NA = Not available; NP: Not prescribed

Discussion

The initial step for cancer control and prevention is to develop the proper understanding of relationship between disease and demographics [25]. This study reported 73.2% of the cases from urban areas and 26.8% from rural areas. Many cancer cases remained undiagnosed in Pakistan due to financial obstacles and poor availability of health care facilities (e.g. inadequate system of population based registers, and deprived diagnosis as well as treatment facilities in rural areas as compared to urban areas) [26, 27]. Therefore, exact number of cancer cases might be far greater in number than that of reported.

Breast cancer (19.2%) was the most commonly diagnosed cancer among females while NHL (14.9%) was commonly found in males. Such a high prevalence of breast cancer is not only found in Pakistan, it can be seen throughout the world. It is estimated that nearly half of all the reported cases of breast cancer and 38% of all the deaths due to this fatal illness have been reported from developed countries. The various subtypes of NHL are thought to alter immune system and show different pattern of incidence.

Availability of anticancer medicines (originator brands and lowest price generics)

The availability of anti-cancerous medicines is mandatory for saving lives of cancer patients. In many low and middle income countries (LMICs) the availability of LPGs is often less [28] e.g., a cross-sectional study conducted in Dar es Salaam (Tanzania) revealed that the availability of anticancer drugs in healthcare settings was 50% of the total surveyed medicines while only 30% of the patients could get the anticancer drugs from the healthcare settings [29]. Similarly, the current findings showed that in both sectors the overall availability of OBs (52.5%) can be considered as fairly high in comparison with the LPGs (28.1%). Most of the OBs are the products of the multinational pharmaceutical companies (MPCs). These MPCs adopt various strategies (e.g., promotional techniques and the patent rights) in order to compete with the local pharmaceutical companies (LPCs). Due to the limitation of resources, LPCs cannot manage budget for promotional strategies. The promotional efforts of MPCs make product well-familiar to the prescribers. Therefore, prescribers are compelled to prescribe these medicines. According to the Trade-Related Aspects of Intellectual Property Rights (TRIPS) agreement, Pakistan has a right to include in its patent legislation a provision to manufacture LPGs without the requisition of any consent from the patent holder since Pakistan is a member of World Trade Organization (WTO). But, it was also found that 10 medicines LPGs were not available in the market.

In LMICs, the availability of medicines in the healthcare settings is considerably influenced by the cost [30]. This study revealed that the availability of these anticancer medicines was high in the private sector (71.9% for OBs and 20.0% for LPGs) as compared to the government healthcare settings (31.4% for OBs and 11.7% LPGs). Due to financial constraints, the government of Pakistan is unable to maintain good infrastructure of the public healthcare settings [31]. Thus government hospitals often face the issue of unavailability or shortage of medicines as compared to private sectors.

Unlike the conventional medicines new anticancer medicines were less readily available in both sectors. In LMICs like Pakistan, the retail prices are the major deterrent to access when compared with the cost at the supplier level [32]. In Pakistan, the high taxation associated with these lifesaving medicines is a cruel joke with the cancer sufferers. All the national and international organizations i.e., the WHO, HAI, The United States Agency for International Development (USAID), United Nations Organization (UNO) and DRAP must provide adequate funding so that tax free anticancer medicines can be made available to the local masses.

Affordability of anticancer medicines at different income levels

In Pakistan, the affordability of medicines, especially anticancer medicines, is widely affected by the proliferation of OBs [12]. Our findings showed that the LPGs (67.9%) are more affordable than the OBs (53.4%). Because of price constraints medicines are not 100% affordable for general public, so OBs were found to be more affordable (70.7%) for high income patients, less affordable (49.1%) for middle income patients, and least affordable (29.2%) for low income patients. This may cause a great risk of disease progression, higher rate of mortalities and morbidities. In this study, the overall affordability for both OBs and LPGs was found to be 55.5% which makes cancer a catastrophic disease for local masses [33]. Another dilemma of LMICs is that the local masses are unaware of the importance of health insurance [34]. But sometimes these insurance policies fail to provide benefits or demand substantial co-payment [35]. Private health insurance schemes cover medicines cost. But high inflation, low per capta income and increasing cost of living are among the several hurdles that hinder the individuals for buying private health insurance and pay monthly premium. The government hospitals of Pakistan do not require any copayment for consultation and medicines. But in private hospitals all the expenses have to be paid by the patient [36]. Therefore, in 2014 Pakistani government took initiative in the form of Prime Minister National Health Insurance Program. This program aimed to cover a large number of cancer sufferers in both government and private sector. But without the cooperation of international organizations, this program cannot cover all the financially constrained civilians of Pakistan.

Strength and limitations

There is no previously published study that evaluates the anticancer medicines with respect to availability in public and private sectors, and affordability with respect to income class especially in LMICs like Pakistan. Our study will provide a door to the researchers of other LMICs to evaluate availability and affordability related barriers towards optimal cancer treatment in their respective settings so that cancer medicines can be made affordable all over the entire globe.

There are some limitations in this study. First, the availability was measured at ‘one time’ on the day of data collection from any health facility. Therefore some facilities might usually have a product is available, but the drug may be out of stock on the day of data collection. Second, although this paper contains data on availability of anticancer drugs in Pakistan but it does not give insight in to what extent current guidelines of drug treatment of cancer are compromised by limited access to anticancer drugs. So, we cannot conclude what the effect of this is to outcome of anticancer treatment in Pakistan patients. Third, the authors measured households’ capacity to pay by collecting household income information, though it is often recommended that household ordinary expenditure excluding durable goods consumption will better reflect household’s capacity to pay.

Conclusion

Cancers like non-hodgkin lymphomas and breast cancer are prevalent in Pakistan. The study revealed a fairly high availability for OBs and generally low availability for LPGs. The availability of these agents is greater in private sector as compared to public sector. The overall affordability of LPGs is more as compared to OBs irrespective of the income class; however, both of them are more affordable by high income class patients. Government and regulatory authorities must take adequate steps and formulate such policies to ensure the equitable availability and affordability of cancer medicines to fight against this deadly disease.

Abbreviations

HAI: 

Health Action International

LPCs: 

Local Pharmaceutical Companies

LPGs: 

Lowest Price Generics

MPCs: 

Multinational Pharmaceutical Companies

OBs: 

Originator Brands

SPSS: 

Statistical Packages for Social Sciences

WHO: 

World Health Organization

Declarations

Acknowledgements

We would like to express wholehearted thankfulness to participants of the study. We wish to express gratitude to Dr. Muhammad Atif (Assistant Professor, Islamia University of Bahawalpur, Pakistan), Dr. Zaheer-Ud-Din Babar (Professor, University of Huddersfield, United Kingdom), Dr. Shane Scahill (Senior Lecturer, Massey University, New Zealand) and Dr. Tayyaba Sadiq (Lecturer, Akhtar Saeed College of Pharmaceutical Sciences, Pakistan) for reviewing and editing the paper and for valuable comments. Also, a note of thanks to all pharmacy students who acted as data collectors.

Funding

None

Availability of data and materials

The raw data on which conclusions of this manuscript rely is available upon request. Please contact Muhammad Rehan Sarwar at rehansarwaralvi@gmail.com.

Authors’ contributions

MRS conceptualized and designed the study. AS and SI analyzed and interpreted the data. MRS and AS drafted the manuscript. SI and MRS critically revised the manuscript. All authors read and approved final version of the manuscript.

Ethics approval and consent to participate

The ethical approval was obtained from the Pharmacy Research Ethics Committee (PREC) at Akhtar Saeed College of Pharmaceutical Sciences (Reference: 14–2016/PREC, December 25, 2016). Before conducting the study, permission was granted from the hospital and pharmacy administrators. The purpose and protocols of this study were thoroughly explained to every participant and their verbal consents were obtained. Written consent was not possible for most of the respondents either because they were illiterate or they had problems in reading and/or signing the consent document. The PREC committee approved this consent procedure.

Consent for publication

Not applicable

Competing interests

The authors declare that they have no competing interests.

Publisher’s Note

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Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors’ Affiliations

(1)
Department of Pharmacy, The Islamia University of Bahawalpur, Bahawalpur, Pakistan
(2)
Akhtar Saeed College of Pharmaceutical Sciences, Lahore, Pakistan

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