Skip to main content
NCBI home page
Journal of Cancer Research and Clinical Oncology logoLink to Journal of Cancer Research and Clinical Oncology
. 2021 Apr 22;147(12):3693–3698. doi: 10.1007/s00432-021-03607-5

Economics influences therapy decisions in chronic myeloid leukaemia: should it?

Qian Jiang 1, Richard A Larson 2, Robert Peter Gale 3,✉
PMCID: PMC11802147  PMID: 33885952

Abstract

The question whether economic considerations should influence therapy decisions in persons with chronic myeloid leukaemia (CML) is complex touching on many metrics other than medicine including the perceptions, attitudes, and motivations of physicians, patients, their families, and payors’, allocation of health care resources, and others. We discuss metrics whereby physicians, patients, and payors make CML therapy choices in settings where cost and availability are or are not considerations. We conclude that economic considerations strongly influence therapy decisions in CML. Whether this should be so and what impact it has on outcomes is also considered. Absent definitive data proving which therapy strategy is best allowing economic considerations to operate may not be as unreasonable or unethical as it appears. In some settings, it may be the best approach. However, because TKIs markedly prolong survival and may even cure some persons with CML, TKI therapy should be available to everyone with CML.

Keywords: Therapy decisions in CML, Chronic myelogenous leukemia, Economic influences on theraphy

Introduction

The question whether economic considerations should influence therapy decisions in persons with chronic myeloid leukaemia (CML) is complex, touching on many areas other than medicine and economics, including the perceptions, attitudes, and motivations of physicians, patients, their families payors, allocation of health care resources, and others. Five tyrosine kinase inhibitors (TKIs) are approved by the US Food and Drug Administration (FDA), the European Medicines Agency (EMA), and other Health Authorities to treat CML. Not all are available worldwide, and not all, when available, are approved for the same indication(s). For example, some drugs are approved for initial therapy of chronic-phase CML, others for more advanced phases, and others for persons with specific BCRABL1 mutations. Our discussion focuses on the choice of a TKI for initial therapy of chronic-phase CML. We critique what role economic considerations, if any, should play in the decision which TKI to use. Specifically, we do not analyze the cost implications, for example, of the introduction of generic versions of TKIs such as imatinib. (Conti et al. 2015; Padula et al. 2016). Nor do we address the best therapy strategy or therapy goal in CML. Detailed reviews of costs of CML therapy and impact of generic versions of CML drugs are available elsewhere (Conti et al. 2015; Padula et al. 2016). Discussions of the cost of developing new drugs, drug pricing including affordability of drugs, whether drug companies are earning too much, and related issues are also available (Wouters et al. 2020; Ledley et al. 2020; Hernandez et al. 2020).

Decision points

Several decision metrics affecting whether economic considerations should influence therapy decisions in CML include: (1) physician metric, (2) patient metric, and (3) payor metric. We discuss these below in two settings (1) a hypothetical when drug cost and availability are not a consideration; and (2) in the real world where both are considerations.

Scenarios where cost and availability are not considerations

Scenarios where cost and availability are not issues are conceptually interesting but non-existent. However, visualizing such a situation allows us to discuss several important factors which we return to in the real-world setting.

Physician metric

Typically, physicians decide which TKI to recommend and prescribe. What are their considerations and drivers? When cost and availability are not considerations, physicians choose the TKI which they prefer. However, physicians have different metrics for choosing one or other TKI. For example, mutations in BCRABL1 might influence this decision including mutations in other myeloid-related genes associated with different prognoses. Save at some academic medical centers, analyses of mutations in BCRABL1 or other genes by Sanger or by next-generation sequencing (NGS) are not done at diagnosis. Moreover, it is rare to detect a mutation in the ABL1 kinase domain that might interfere with TKI binding in persons with newly diagnosed chronic-phase CML. More often, choice of an initial TKI is based on risk stratification measured by the Sokal score or the ELTS (EUTOS Long-Term Survival) score. Persons with low-risk scores typically receive imatinib, whereas those with high-risk scores typically receive dasatinib, nilotinib, or bosutinib. There is often indecision regarding the preferred TKI for persons with intermediate-risk scores.

Some physicians will choose imatinib as initial therapy because of the favorable safety profile based on more than 20 years of data. However, other physicians think that rapidity of response is important and choose dasatinib, nilotinib, or bosutinib. Other strategies include starting with imatinib and switching to dasatinib or nilotinib if the rate and/or depth of response was insufficient, or the contrary, starting with dasatinib or nilotinib or even bosutinib and then switching to imatinib because of adverse events or after the targeted response depth is reached. There are no convincing data to support the latter approach, but this need not impact physician preferences when unconstrained. Other strategies involve increasing imatinib dose depending on response rate or depth or decreasing imatinib, dasatinib, or nilotinib dose after achieving a targeted response depth or because of adverse events.

An important consideration for some physicians is potential adverse events. For example, physicians may prescribe a TKI based on someone’s age, co-morbidities, or risk to develop lung, heart, or other vascular adverse events. In general, older people and those with co-morbidities are less likely to tolerate the second-generation TKIs. A person with lung disease may be less likely to receive dasatinib and a person with arterio-sclerotic peripheral vascular disease, nilotinib. Sometimes because of similar response rates and fewer adverse events, physicians may reduce doses of drugs such as imatinib or dasatinib. (Naqvi et al. 2020; Hochhaus et al. 2020).

As highlighted in the current management recommendations from the European LeukemiaNet (ELN) Working Group, experts differ in treatment goals for persons with newly diagnosed chronic-phase CML. (Hochhaus et al. 2020). Survival is generally accepted as the most important therapy endpoint, but this is complex, because most persons with CML now die from unrelated events such as heart disease and diabetes, not CML (Saussele et al. 2015). None of the current TKIs produce convincingly better survival. Consequently, some physicians aim for a rapid and deep molecular response (DMR) defined as a BCR/ABL1 transcript level < 0.01 percent on the International Scale, the trigger for considering therapy discontinuation. Thus, strategy(ies) used to rapidly achieve therapy-free remission (TFR) rather than those used to rapidly achieve a major molecular response (MMR) defined as BCR/ABL1 transcript levels < 0.1% (IS) also affect TKI choice. Because more potent TKIs achieve these endpoints more rapidly than imatinib, some physicians prefer starting with these drugs. If one assumes a DMR > 2 or 3 years is needed before stopping TKI therapy, this strategy shortens the interval to the start point but not by much in most people. However, no clinical or laboratory co-variates accurately predict which persons succeed in achieving TFR after > 2–3 years of DMR. There are no convincing data which everyone needs the same duration of DMR to successfully stop TKI therapy (Gale and Saglio 2021). Nor are there data, when adjusting for other co-variates, successful TFR correlates with the TKI used to achieve and maintain a DMR. Given these uncertainties, physicians recommend a TKI more based on their beliefs and biases than scientific evidence. In other areas of oncology, physicians’ risk tolerance quantified by assessing their stock investment portfolio and physician and patient race and sex are significantly correlated with therapy choices (Luo et al. 2015; Arrieta et al. 2017; Ferguson et al. 2017). Although this is unstudied in the context of TKI therapy of CML, these co-variates are likely to operate.

A diversity of strategies by experts for using TKIs usually indicates there are no convincing data any strategy is better. Consequently, in this hypothetical scenario of unconstrained cost and availability of TKIs, there is no reason why pharmaco-economic considerations should affect TKI choice for chronic-phase CML.

Another reality is that physicians may participate in clinical trials of a TKI. Although their major motivation may be to answer a scientific question, there may also be rewards, direct and indirect, for prescribing one or another TKI, such as publication authorship, participation in a drug company speakers bureau, travel, etc. Some of these activities may be compensated. Monies received by US academic physicians (termed key opinion leaders or KOLs) from drug companies are reviewed elsewhere (Gill et al. 2020). Sometimes, these sums are considerable.

Despite these complex considerations, and as in many other medical settings, when physicians are unconstrained by cost and availability, they often choose a drug with which they have the most experience and are most comfortable with. This reality will play out differently in different venues. For example, in the US, most persons with CML are treated by oncologists in private practice, whereas in countries with a national health care system like the UK, there are likely to be more constraints. Better organized health care systems tend to direct people with CML to the so-called centers of excellence and experience where they are managed by expert hematologists. However, there are convincing data CML management by expert haematologists results in better outcomes than management by non-experts. Of course, every physician considers themselves an expert, making it difficult or impossible to identify the non-experts.

Patient metric

Again, in a hypothetical setting where cost and availability are not considerations, patients are not neutral to the TKI they prefer receiving. In a study in China, we found a preference for branded TKI over generics (Jiang et al. 2017a, b; Jiang and Gale 2016; Jiang et al. 2017b; Jiang et al. 2016). Typically, patients prefer TKIs from well-known international drug companies to local and imported generics. These preferences are independent of safety or efficacy and reflect typical consumer attitudes when cost is ignored such as preferring a Mercedes over a Fiat. Other considerations such as dosing frequency need to take a drug with meals, and perceived quality-of-life on therapy impact a patient's adherence and TKI preference. In some countries, people are influenced by drug company-sponsored advertising campaigns via a direct marketing campaign such as on television or the Internet or by supporting patient advocacy and support organizations. Patient preferences are also influenced by Internet-based patient groups some of which are bona fide, others not.

Payor metric

Payors are never neutral to cost and availability. We discuss these issues below.

Scenarios where cost and availability are issues

Market prices of TKIs in the US for CML are high (Tefferi et al. 2015). The average wholesale price of generic imatinib in the US is $10,000 USD per month versus $12,000 USD per month for branded imatinib. Thus, the generic price of imatinib in the US is not substantially less than the branded drug price. These data contrast with Canada where generic imatinib is $733 per month USD (> tenfold less) versus $3200 per month USD (about threefold less) for branded imatinib. The price of generic imatinib in India, China, and other developing countries is very much less. Although a detailed discussion of TKI pricing is beyond the scope of our typescript, data on imatinib price in seven countries are displayed in the Fig. 1. Price per month of imatinib in USD is $146 to $11,336 with a median of $2,372 USD. There remains a huge range even when adjusted for purchasing power parity, $649 to $11,336 with a median of $2360 USD.

Fig. 1.

Fig. 1

Open in a new tab

Cost of branded imatinib in seven countries. XR, price in USD in local currency using foreign exchange rates; PPP, price in USD when converted from local currency using purchasing power parity (Goldstein et al. 2017)

Physician metric

The metric here is considerably more complex than when cost and availability are not considerations. Even when physicians are fiscally independent from payors, they may be constrained as to which TKI which they can prescribe. In some settings, physicians participate in a medical practice group and/or managed care organization which monitors costs of drugs they prescribe. Using a lower cost TKI such as a generic or a preferred drug from an approved formulary may be incentivized by giving physicians monies not spent by the group or organization. Also, in some settings, physicians may be punished by their hospital for prescribing expensive TKIs when cheaper versions are available. Sometimes, hospitals restrict which TKI a physician can prescribe by limiting choices to those in a hospital formulary. Above, we discuss direct and indirect remuneration to physicians from drug companies. In some countries, typically with a government payor, a national health agency may monitor physician prescription practices and intervene to change prescription practices. The same practices apply to large third-party insurers in some countries.

Availability is, of course, an issue. Physicians can only prescribe TKIs available where they practice. However, this does not preclude patients from importing branded and generic foreign-made TKIs, a practice common in many developing countries. In some, like India, the government may order drug companies to produce a generic version of one or more TKIs.

Patient metric

The input of patients is important in settings where cost and availability are considerations. This is especially so when the patient is the only or a major payor (see below). We studied this issue in China where provincial health insurance for TKIs varies considerably. In a survey of patients’ and hematologists’ concerns regarding TKI therapy, patients were more concerned with TKI reimbursement policies and price reduction of TKIs compared with hematologists. (Jiang et al. 2018) We also found people living in rural areas, those with a less education, and those divorced or widowed preferred generic to branded imatinib or to a second-generation TKI for the initial therapy. This preference was independent of sex, age, and prognosis. (Dou et al. 2020). The motivation appears to be cost savings, either self- or family-imposed. These data indicate socio-economic co-variates influence people’s preference for TKIs. Availability of free or markedly reduced cost drugs in drug company-sponsored patient assistance programmes (PAPs) or clinical trials may have a large impact on patients’ TKI preference.

Payor metric

The impact of payor preferences depends strongly on the health care system structure and reimbursement scheme. We review several below.

Single-payor systems

Fundamental to answering whether economic considerations should influence CML therapy decisions is determining who pays. Sometimes, the answer is simple such as when there is a single-payor national health care system. Here, the government decides which TKIs are available and at what price and reimbursement ratio. Pricing is typically negotiated with or dictated to the drug company. The price of the TKI may depend on whether the drug company provides a rebate to the government if the therapy is unsuccessful. When offered, two competing drugs of equivalent safety and efficacy national health agencies tend to choose the lower bidder. The negotiated price varies according to diverse factors including a country’s wealth, the fraction of the gross domestic product (GDP) committed to health care, and per capita health care expenditure. The range is huge. For example, median annual per capita health care spending in India is $209 USD compared with $399 for China. This means the per capita health care spending for about 40% of the world population is about $300 USD. US per capita health care expenditure is $8948, a 30-fold greater expenditure than in India and China. In the single-payor setting, neither the physician nor person with CML decides on which TKI to prescribe or receive based on pharmaco-economics unless a person imports drug at their own expense. Sometimes, this is legal but not in all countries. In other countries, typically developing countries, there is no alternative. In this instance and in many developing countries, the patient is the payor. His/her choice of TKI will be influenced by their physician’s recommendation, drug availability, price, therapy goal, co-morbidities, convenience of dosing, and the socio-economic co-variates which we discussed above.

Mixed systems

More often health care expenses are a combination of government, commercial insurer, employer, and patient contributions. Insurers can be governmental or commercial, for-profit, or not-for-profit. Sometimes, the employer is self-insured. Most employer-sponsored plans in the US make use of a pharmacy benefit manager (PBM) to process prescriptions and control costs. Sometimes patients must fail the least expensive drug, usually generic imatinib, before they can access more expensive TKIs through their prescription plan. However, physicians can manipulate this system by, for example, deciding a minor adverse event is a failure. Sometimes, this strategy is self-motivated. Other times, it is used under pressure from a patient who may want a more expensive branded TKI. Drug companies may offer substantial rebates, but these typically go to the PBM rather than the consumer. (Rubin et al. 2020). Sometimes, there is an intermediary not- or for-profit insurer. Often, there is a co-pay or deductible for drugs regardless of the type of insurer. In this setting, the choice of TKIs may be limited by contractual agreements, but this is not always so. Employers and insurers may have different reimbursement schemes for different drugs (known as tiers) depending on price and whether the TKI is prescribed on- or off-label. Drug companies may help patients who have limited monies via a PAP (discussed above). In the US where many people are under-insured for expensive anti-cancer therapies, PAPs have helped diffuse some criticism of the high list price of many life-prolonging drugs such as TKIs in CML. Sometimes, these programmes reflect a market price closer to the cost of goods. However, in many if not most instances, the (tax deductible) loss of profits in one country is recovered by high prices in other countries, especially the US. For example, the monthly cost of branded imatinib in a patient assistance programme in China is about $670 USD versus a commercial price of about $9000 USD in the US. There is huge variability in the price of branded imatinib over time and country. For example, when imatinib was first introduced in 2001, the annual cost in the US was $26,000 USD. By the time of its patent expiration, the annual cost increased to $120,000/year. Interestingly, when the patent expired in 2017, a month supply of branded imatinib costs about $9000 USD, like the cost of the first generic imatinib to enter the US market, about $8000 USD. The price has declined slowly despite additional generic products entering the US market.

No payor system

This is the same as a sole payor system where there is no external fiscal support and the patient pays. As remote as this sounds to many readers, this situation applies to most people with CML living in under-developed or developing countries, more than one-half of everyone with CML globally. Here, the patient is unlikely to understand differences in safety or efficacy of TKIs and will garner information from their physician, relatives, the Internet (typically unavailable), or a combination. They are also unlikely to understand different therapy goals such as achieving TFR. Consequently, cost and availability are the key determinants in this setting.

Conclusion

We began with the question: Should economic considerations influence therapy decisions in CML? Above we discuss metrics whereby physicians, patients, and payors make CML therapy choices in settings where cost and availability are or are not considerations. We conclude economic considerations strongly influence therapy decisions in CML. The question whether this should be so is different from the question whether they do. One element of the answer relates to ethics. People imagine that, in a perfect setting, economic considerations would have no influence on someone’s medical care namely, everyone should get the best therapy regardless of drug cost or availability. However, certain unavoidable realities confound this ideal. Perhaps, the most important is that the best therapy of CML is unknown and may be unknowable (Larson et al. 2015; Hantel et al. 2018). Add to this the substantial likelihood, there is no one best therapy for everyone. Further clouding the issue are several real-world considerations. Not every person or nation has the same fiscal resources, opinion how to appropriate resources nor even the same notion of the value of a human life. Under these circumstances, the impact of economic considerations on choices of TKI therapy is unavoidable. Allowing economic considerations to operate may not be as unreasonable or unethical as it appears. In some settings, it may be the best approach. However, because TKIs markedly prolong survival and may even cure some persons with CML TKI therapy should be available to everyone with CML.

Acknowledgements

RPG acknowledges support from the National Institute of Health Research (NIHR) Biomedical Research Centre funding scheme.

Compliance with ethical standards

Conflict of interest

RAL has acted as a consultant or advisor to Novartis, Amgen, Ariad/Takeda, Astellas, Celgene/BMS, CVS/Caremark, Epizyme, and MorphoSys, and has received clinical research support from Novartis, Astellas, Celgene, Cellectis, Daiichi Sankyo, Forty Seven, Rafael Pharmaceuticals, and royalties from UpToDate. RPG is a consultant to: BeiGene Ltd., Fusion Pharma LLC, LaJolla NanoMedical Inc., Mingsight Parmaceuticals Inc., and CStone Pharmaceuticals. Medical Director of FFF Enterprises Inc, on the Board of Directors: RakFond Foundation for Cancer Research Support. Scientific Advisory Board: Antegene Biotech LLC, StemRad Ltd.

Footnotes

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

References

  1. Arrieta A, Garcia-Prado A, Gonzalez P, Pinto-Prades JL (2017) Risk attitudes in medical decisions for others: An experimental approach. Health Econ 26(s3):97–113 [DOI] [PubMed] [Google Scholar]
  2. Conti RM, Padula WV, Larson RA (2015) Changing the cost of care for chronic myeloid leukemia: the availability of generic imatinib in the USA and the EU. Ann Hematol 94(Suppl 2):S249–S257 [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Dou X, Qin Y, Lai Y, Shi X, Jiang Q (2020) Comparable Efficacy and Safety of Generic Imatinib and Branded Imatinib in patients with newly diagnosed chronic myeloid leukemia with a consideration of socioeconomic characteristics: A retrospective study from a single center. Clin Lymphoma Myeloma Leuk 20(6):e304–e315 [DOI] [PubMed] [Google Scholar]
  4. Ferguson MK, Huisingh-Scheetz M, Thompson K, Wroblewski K, Farnam J, Acevedo J (2017) The influence of physician and patient gender in risk assessment for lung cancer resection. Ann Thorac Surg 104:284–289 [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Gale RP, Saglio G (2021) Point: is there a best duration of deep molecular response to achieve therapy-free remission in chronic myeloid leukaemia? Br J Hematol 192(1):22–23. 10.1111/bjh.17112 [DOI] [PubMed]
  6. Gill J, Haslam A, Crain MS, Herrara-Perez D, Prasad V (2020) Comparison of industry payments in 2017 with annual salary in a cohort of academic oncologists. JAMA Intern Med. 10.1001/jamainternmed.2020.0090 [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Goldstein DA, Clark J, Tu Y, Zhang F, Goldstein R, Stemmer SM et al (2017) A global comparison of the cost of patented cancer drugs in relation to global differences in wealth. Oncotarget 8:71548–71555 [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Hantel A, Larson RA (2018) Imatinib is still recommended for frontline therapy for CML. Blood Adv 2:3648–3652 [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Hernandez I, Rodriguez AS, Good C (2020) Changes in list prices, net prices and discounts for branded drugs in the US, 2007–2018. JAMA 323:854–862 [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Hochhaus A, Baccarani M, Silver RT (2020) European LeukemiaNet 2020 recommendations for treating chronic myeloid leukemia. Leukemia. 34:966–84 [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Jiang Q, Gale RP (2016) Molecular monitoring of tyrosine kinase inhibitor therapy of chronic myeloid leukemia in China. J Cancer Res Clin Oncol 142:1549–1555 [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Jiang Q, Liu ZC, Zhang SX, Gale RP (2016) Young age and high cost are associated with future preference for stopping tyrosine kinase inhibitor therapy in Chinese with chronic myeloid leukemia. J Cancer Res Clin Oncol 142:1539–1547 [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Jiang Q, Wang H, Yu L, Gale RP (2017a) Higher out-of-pocket expenses for tyrosine kinase-inhibitor therapy is associated with worse health-related quality-of-life in persons with chronic myeloid leukemia. J Cancer Res Clin Oncol 143:2619–2630 [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Jiang Q, Wang HB, Yu L, Gale RP (2017b) Variables associated with patient-reported outcomes in persons with chronic myeloid leukemia receiving tyrosine kinase-inhibitor therapy. J Cancer Res Clin Oncol 143:1013–1022 [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Jiang Q, Yu L, Gale RP (2018) Patients’ and hematologists’ concerns regarding tyrosine kinase-inhibitor therapy in chronic myeloid leukemia. J Cancer Res Clin Oncol 144:735–741 [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Larson RA (2015) Is there a best TKI for chronic phase chronic myeloid leukemia? Blood 126:2370–2375 [DOI] [PubMed] [Google Scholar]
  17. Ledley FD, McCoy SS, Vaughn G, Galkina E (2020) Profitability of large pharmaceutical companies compared with other large public companies. JAMA. 323:834–843 [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Luo T, Spolverato G, Johnston F, Haider AH, Pawlick TM (2015) Factors that determine cancer treatment choice among minority groups. J Oncol Pract. 10.1200/JOP.2015.003640 [DOI] [PubMed] [Google Scholar]
  19. Naqvi K, Jabbour E, Skinner J, Anderson K, Dellasala S, Yimanez M et al (2020) Long-term follow-up of lower dose dasatinib (50 mg daily) as frontline therapy in newly diagnosed chronic-phase chronic myeloid leukemia. Cancer 126:67–75 [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Padula WV, Larson RA, Dusetzina SB, Apperley JF, Hehlman R, Baccarani M et al (2016) Cost-effectiveness of tyrosine kinase inhibitor treatment strategies for chronic myeloid leukemia in chronic phase after generic entry of imatinib in the United States. JNCI 108:3 [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Rubin R (2020) Rebates-The little-known factor behind increasing drug list prices. JAMA. 323:812–813 [DOI] [PubMed] [Google Scholar]
  22. Saussele S, Kraus MP, Hehlman R, Lauseker M, Proetel M, Kalmanti L et al (2015) Impact of co-morbidities on overall survival in patients with chronic myeloid leukemia: results of the randomized CML study IV. Blood 126:42–49 [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Tefferi A, Kantarjian H, Rajkumar SV, Younes A, Zelenetz AD, LeMaistre CA (2015) In support of a patient-driven initiative and petition to lower the high price of cancer drugs. Mayo Clin Proc 90:996–1000 [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Wouters OJ, McKee M, Luyten J (2020) Estimated research and development investment needed to bring a new medicine to the market, 2009–2018. JAMA 323:844–853 [DOI] [PMC free article] [PubMed] [Google Scholar]

Articles from Journal of Cancer Research and Clinical Oncology are provided here courtesy of Springer

RESOURCES