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Vol 23, No. 11, November 2019   |   Issue PDF view/purchase
Spend less to combat cancer better?
Insights and critique on the deployment of genomic profiling technology in cancer management.

Cancer is the biggest healthcare burden with 9.6 million deaths in 2018,1 and the year-by-year comparisons demonstrate it continues to grow.2 This signifies the urgency to rethink current methods to combat cancer more effectively. With technological transformation in the oncology space, the trend of value-based healthcare delivery has begun to emerge.

Commonly termed precision oncology, the focus in cancer management has changed from a one-size-fits-all to a more personalized, targeted approach (Figure 1). Pharmaceutical companies are shifting their focus to biomarker-guided therapeutics and immuno-oncology, and regulatory agencies advancing fast-track and accelerated approvals of these targeted drugs.3

Admittedly, precision oncology would not be possible without introducing molecular diagnostics, especially next-generation sequencing (NGS) based tumour genomic profiling (TGP). Yet, one may wonder if such technologies will inflate the total treatment cost, or, on the contrary, make cancer care more cost-effective? Does TGP have the potential to reduce, if not eliminate, both treatment toxicity and financial toxicity? In this article, we review the current body of health economics literature and critique the value of TGP in precision oncology.

Molecular diagnostics and precision oncology

Diagnostics is the forefront of clinical decision-making, molecular diagnostics in particular has propelled the advancement of precision oncology.

Today, molecular diagnostics has become an inseparable part of the standard of cancer care as more drugs are being approved alongside a companion or complementary diagnostics test. The most recent example is Novartis’ alpelisib (Piqray®) for HR+/HER2- advanced breast cancer patients with a PIK3CA mutation, approved by FDA concurrently with the therascreen® PIK3CA companion diagnostic test from QIAGEN.4

In practice, molecular testing can be done either on single gene basis (individually or sequentially) or by a multiplex method that uses targeted NGS platform to profile multiple genes at one go (Figure 2). Tumour tissue is commonly the preferred choice of bio-sample for genomic profiling over other types such as liquid biopsy to obtain genomic insights for cancer management.5 Hence, for the purposes of this article, we will solely focus on tumour sequencing.

TGP allows testing of a large number of genes in a single test and is increasingly applied to the frontline diagnostics for cancer types driven by druggable genomic changes in the tumour cells, for example, melanoma, lung, and colorectal cancer.

Precision oncology aims to reduce inappropriate prescribing and decrease therapeutic side effects due to more accurate targeting of tumour cells. From a diagnostic perspective, the question remains how to make the testing most cost-effective so as to provide the maximum benefit for the majority of oncology patients.

Cost-effectiveness analysis (CEA) in healthcare

According to the Association for Molecular Pathology, cost-effectiveness in the context of healthcare is defined as the impact of a medical test on the cost of care and/or on patient welfare.6 However, it is not straightforward to conduct a robust economic appraisal on TGP in the real-world setting due to the following two reasons.

First, cost-effectiveness is measured in quality-adjusted life years (QALY) and incremental cost-effectiveness ratio (ICER). ICER is a summary measure representing the economic value of an intervention, compared with an alternative (comparator) and is usually the main output or result of an economic evaluation. Arguably, the thresholds of QALY and ICER vary among studies, especially when it comes to determining the value of ICER.7

Second, the CEA results of using multiplex NGS panels also differ substantially, subject to varying methodologies or the cancer type analysed.

Hence, for specificity in this article, our critique will focus on two types of CEA (Table 1):

  1. examination of TGP versus single gene tests (either one-off or sequential), and
  2. studies of TGP-guided targeted therapy.

We will now illustrate, and contrast, the methodology of CEA in the following examples of major cancer types. Please note: all CEA studies were performed from a healthcare payer’s perspective and the currency conversions were done according to the prevailing rates at the time of this write-up.

Examples of diagnostics-focused CEA: colorectal, skin and lung cancer

For example, in 2017 a Japanese research group utilised TGP to comprehensively sequence more than 400 genes in colorectal cancer samples. The group concluded that compared to RAS hotspot testing alone, upfront profiling of multiple genes known to confer resistance to anti-EGFR therapy was more cost-effective for patient’s treatment course. In detail, TGP-based diagnostics added 0.063 QALYs (0.075 life years gained) with an ICER 4,260,187 JPY/QALY, equivalent to 39,819.97 USD/QALY.9

In short, TGP-based cancer treatment does demonstrate promising results in colorectal and skin cancer. However, in advanced lung cancer, evidence shows a wide range of results depending on the diagnostic methodology (e.g. TGP versus sequential) and the number of genes in the analysis.

When more than three lung cancer tumourigenesis genes are sequenced, the CEA results become more striking. Pennell et al. analysed a nine-gene TGP versus nine single gene tests (sequential), and a four-gene panel followed by five single gene tests (panel). The research group affirmed that conducting TGP upfront is more cost-effective for first line treatment selection; moreover, it boasts the shortest turnaround time. More stunning results were revealed by simulation modelling for a hypothetical one million-member health plans from healthcare payer perspectives. Comparing TGP to sequential and panel testing respectively, upfront TGP was able to reduce the cost up to 1,530,869 and 2,140,795 USD (for public payers), and 127,402 and 250,842 USD (for commercial payers).12

When prescribing targeted therapeutics for lung cancer based on TGP, the CEA results have not been so encouraging. For example, in metastatic lung cancer, a precision medicine approach (10-gene TGP with matched targeted therapy) for the selection of fourth line treatment was determined as not cost-effective compared to the use of either cytotoxic treatment or best supportive care at ICER 330,109.62 USD/QALY.13

Nevertheless, two other studies established that upfront TGP is cost-effective compared to single gene EGFR and/or ALK testing to guide the first line treatment selection. A panel of seven genes increased the use of targeted therapies and the ICER for TGP was 148,478 USD/life years gained.14 In the second study, use of an 11-gene TGP decreased the use of non-targeted therapies from 83 percent to 20 percent and reduced the total treatment cost by 2.7 million USD (from 10.2 to 7.5 million).15

Scenarios where TGP provides the best value for money

Having learned the controversial findings across different cancer types and studies, one may be more puzzled about the surrounding circumstances where TGP provides the best value for money in precision oncology. To sum up the major findings from the CEA studies discussed in current health economics literature, we have listed a number of scenarios where TGP holds great potential to make cancer treatment more cost-effective.

  1. TGP becomes cost-effective when the panel size is large enough to identify multiple potential treatment options.
  2. TGP is cost-effective when it is applied upfront at initial diagnosis but will provide less value at a later setting.
  3. The utility of TGP is more remarkable for late or advanced stage patients. Hence, the benefits for earlier stage patients remain to be seen.

Challenges and the way forward

In the era of precision oncology, cancer management is at the cusp of a new revolution. Traditional treatment experience continues to be challenged by the introduction of NGS-based genomic profiling.16

TGP comes to the forefront as a cost-effective alternative, especially for treatment selection, both from a diagnostics and treatment cost perspective. It is evident multiplexed NGS-based TGP is cost-effective in melanoma, colorectal and lung cancer at initial diagnosis. More significantly, TGP can also decrease the number of adverse events, increase patient enrolment into clinical trials and prolong progression-free survival.15 However, this paradigm shift of adopting TGP as a standard of care poses challenges to clinicians and patients.

First, to make genomic profiling a reality in the current landscape of cancer treatment, clinicians need to appreciate the clinical value of genomic testing, the quality control of the specimens, as well as the interpretation of results and curation of the database used.

Second, it is extremely difficult to estimate the total costs associated with processes beyond the actual sequencing runs as they require multiple different professionals from molecular and computational biologists to genetic counsellors, pathologists and clinicians.

To make genomic diagnostics tests more accessible and affordable in Asia, we have witnessed both government17 and private insurers18 starting to reimburse or partially subsidise diagnostic expenses through either social health insurance or public-private partnerships to better protect patients from the costs associated with cancer diagnostics. In doing so, patient outcomes may be improved, and costs reduced when cancer is diagnosed early and treated appropriately.


  1. World Health Organization. Cancer: Key facts (2018 Sep). Retrieved from: https://www.who.int/news-room/fact-sheets/detail/cancer
  2. Latest world cancer statistics – GLOBOCAN 2012: Estimated cancer incidence, mortality and prevalence worldwide in 2012 (2013 Dec). Retrieved from: https://www.iarc.fr/news-events/latest-world-cancer-statistics-globocan-2012-estimated-cancer-incidence-mortality-and-prevalence-worldwide-in-2012/
  3. 6 critical factors for achieving success on the accelerated approval pathway for oncology drugs (2017 Mar). Retrieved from: https://www.precisionmedicinegrp.com/pfm/wp-content/uploads/sites/3/2017/03/Oncology-White-Paper-6-Critical-Factors.pdf
  4. FDA approves Novartis Piqray – the first and only treatment specifically for patients with a PIK3CA mutation in HR+/HER2- advanced breast cancer (2019 May). Retrieved from: https://www.novartis.com/news/media-releases/fda-approves-novartis-piqray-first-and-only-treatment-specifically-patients-pik3ca-mutation-hrher2-advanced-breast-cancer
  5. Nairismagi ML & Lai A. Liquid biopsies and its implications on Asia. Asia-Pacific Biotech News. 2019 Apr; 23(4):12-16
  6. Joseph L, Cankovic M, Caughron S, Chandra P, Emmadi R, Hagenkord J, Hallam S, Jewell KE, Klein RD, Pratt VM, Rothberg PG, Temple-Smolkin RL, Lyon E. The spectrum of clinical utilities in molecular pathology testing procedures for inherited conditions and cancer: A report of the Association for Molecular Pathology. J Mol Diagn. 2016 Sep; 18(5):605-619
  7. York Health Economics Consortium. Incremental Cost-Effectiveness Ratio (ICER) (2016). Retrieved from: https://www.yhec.co.uk/glossary/incremental-cost-effectiveness-ratio-icer/
  8. Zhao B, Wang L, Qiu H, Zhang M, Sun L, Peng P, Yu Q, Yuan X. Mechanisms of resistance to anti-EGFR therapy in colorectal cancer. Oncotarget. 2017 Jan; 8(3):3980-4000
  9. Saito S, Kameyama H, Muneoka Y, Okuda S, Wakai T, Akazawa K. Cost-effectiveness analysis of the use of comprehensive molecular profiling before initiating monoclonal antibody therapy against metastatic colorectal cancer in Japan. J Cancer Policy. 2017 Jun; 12:61-66
  10. Li Y, Bare LA, Bender RA, Sninsky JJ, Wilson LS, Devlin JJ, Waldman FM. Cost effectiveness of sequencing 34 cancer-associated genes as an aid for treatment selection in patients with metastatic melanoma. Mol Diagn Ther. 2015 Jun; 19(3):169-77
  11. Schluckebier L, Caetano R, Aran V, Ferreira CGM. Cost-effectiveness analysis comparing companion diagnostic tests for EGFR, ALK and ROS-1 versus next-generation sequence (NGS) in advanced adenocarcinoma lung cancer patients. J Clin Oncol. 2017 May; 35(15_suppl):9068-9068
  12. Pennell NA, Mutebi A, Zhou ZY, Ricculli ML, Tang W, Wang H, Guerin A, Arnhart T, Dalal A, Sasane M, Wu KY, Culver KW, Otterson GA. Economic impact of next-generation sequencing versus single-gene testing to detect genomic alterations in metastatic non-small-cell lung cancer using a decision analytic model. JCO Precis Oncol. 2019 May; 3:1-9
  13. Doble B, John T, Thomas D, Fellowes A, Fox S, Lorgelly P. Cost-effectiveness of precision medicine in the fourth-line treatment of metastatic lung adenocarcinoma: An early decision analytic model of multiplex targeted sequencing. Lung Cancer. 2017 May; 107:22-35
  14. Steuten L, Goulart B, Meropol NJ, Pritchard D, Ramsey SD. Cost effectiveness of multigene panel sequencing for patients with advanced non-small-cell lung cancer. JCO Clin Cancer Inform 2019 Jun; 3:1-10
  15. Sabatini LM, Mathews C, Ptak D, Doshi S, Tynan K, Hegde MR, Burke TL, Bossler AD. Genomic sequencing procedure microcosting analysis and health economic cost-impact analysis: A report of the Association for Molecular Pathology. J Mol Diagn. 2016 May; 18(3):319-328
  16. Lai A & Nairismagi ML. Clinical utility of and access to cancer molecular diagnostics in Asia. Asia-Pacific Biotech News. 2018 Jun; 22(6):32-36
  17. Genetic tests for identifying cancer treatments to be covered by Japan's public health insurance (2019 May). Retrieved from: https://www.japantimes.co.jp/news/2019/05/29/national/science-health/genetic-tests-identifying-cancer-treatments-covered-japans-public-health-insurance/#.XbK4HOgzaUl
  18. AIA Hong Kong to offer customers cancer genomic testing services at privileged rates (2019 Jul). Retrieved from: https://www.aia.com.hk/en/about-aia/media-centre/press-releases/2019/aia-press-release-20190729.html

Dr Maarja-Liisa Nairismagi is the regional medical manager at ACT Genomics Singapore.

Ms Ashley Yau is the marketing and visual specialist at ACT Genomics Singapore.

Dr Allen Lai is the managing director at ACT Genomics Singapore and an advisory board member of the International Society for Pharmacoeconomics and Outcomes Research, Asia consortium.

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