Supervised by: Merissa Hickman BSc (Hons). Merissa studied Biomedical Science at the University of Hull. She is a current postgraduate student at the University of Cambridge studying Genomic Medicine. She was awarded a Cambridge Trust Scholarship to complete her MPhil.

Abstract 

Pharmacogenomics is continuing to evolve and become a very prominent field in modern healthcare. DPD testing is an example of the important role of pharmacogenomics. Though DPD testing has proven to be effective in preventing adverse reactions and improving patient experience, questions arise regarding its suitability for different patient groups as well as  how it might affect the efficacy of treatments. Through a study of evidence, limitations, and the consideration of ethical aspects, this critical analysis discusses the comprehension of how DPD testing could potentially guide treatment choices, and highlights the  possibilities and obstacles that DPD testing presents as it continues to shape the future of medicine. However, concerns have been raised about DPD testing’s suitability for non-Caucasian groups due to DPYD variant differences and the cost of testing. Both phenotyping and genotyping risk false outcomes, affecting chemotherapy dosing. Inaccurate DPYD*2A, *13, and p.D949VT variant tests, paired with uracilemia changes in renal impairment, emphasize the urgency of improving accuracy and inclusivity in DPD testing.

1. Introduction

1.1 Pharmacogenomics

Pharmacogenomics is the field of studying how genetic factors contribute to the effect of drugs. The goal of pharmacogenomics is to enhance drug efficacy and reduce drug adverse reactions. Pharmacogenomics contributes to the field of personalized medicine by helping doctors determine drug selection and the correct dosages to provide to patients and treatment plans (Cecchin & Stocco, 2020). The DPYD gene encodes proteins that make the enzyme dihydropyrimidine dehydrogenase. Dihydropyrimidine dehydrogenase (DPD) helps our body process fluoropyrimidines which are one category of chemotherapy drugs used during treatment (Dean & Kane, 2016). An example of fluoropyrimidines is 5- Fluorouracil (5-FU). (DPD) helps break down pyrimidine-based compounds, such as the body’s natural uracil, thymine, and cytosine, so that the body can process these compounds easier (Dean & Kane, 2016). The role of DPYD in the catabolism of these compounds conclusively influences 5-FU’s efficacy and potential side effects. DPD specifically helps the body in the initial steps of the catabolic breakdown of pyrimidines, which aids metabolism of 5-FU. Specifically, DPD works by converting over 85% of clinically administered 5-FU to 5-FUH2, an inactive metabolite (Diaso, 1998). However if the DPYD gene is mutated, enzyme activity within the body is altered. This is dangerous to a person’s health because fluoropyrimidines will accumulate in people with DPD deficiency and lead to toxicity. Variation in the DPYD gene results in an individualized response to fluoropyrimidines due to the altered rate of enzyme activity. This results in a spectrum of clinical outcomes in regards to efficacy and toxicity response (White et al., 2021). The spectrum of gene variations that allows for different production levels of the DPD enzyme may result in an accumulation of fluoropyrimidines, leading to adverse toxicity reactions that can be fatal. Overall, variations in the DPYD gene can affect how an individual responds to fluoropyrimidines. DPD testing is a way to determine how your body will react to the fluoropyrimidines.Utilizing DNA sequencing analysis and various other technologies, the test checks DPYD for any mutations that may affect the body’s ability to metabolize fluoropyrimidines. DPD testing can be completed via a blood test, whereby the blood sample taken during the test is sent to a genetic laboratory to examine the DPYD gene (Callister, 2021).

1.3 Methods for DPD Testing 

Recent research has identified multiple methods for conducting DPD tests. One test is targeted genotyping for specific DPYD variants (Diasio & Offer, 2022). Genotyping is the procedure of determining a person’s genetic makeup by examining specific parts of their DNA. A test that involves genotyping for specific DPYD variants would examine the DNA of an individual in order to identify specific genetic changes associated with altered DPD function. An additional test option available is sequence-based testing for DPD deficiency and interpretation of novel alleles (Diasio & Offer, 2022). This test examines the genetic sequence of the DPYD gene in order to determine if there are any deficiencies in the DPD enzyme. This method of testing involves analyzing a person’s DNA sequence in order to detect any mutations or variations affecting DPD enzyme activity. Another option for testing are phenotypic methods to identify DPD deficiency. Phenotypic methods have the ability to help identify people with DPD deficiency due to factors outside of known causal alleles detected by genetic tests. An example of a phenotypic method of testing is a uracil breath test. In this test, the patient ingests a small amount of labeled uracil and their breath is analyzed for labeled carbon dioxide. The amount of labeled carbon dioxide exhaled helps determine the metabolism of uracil by the DPD enzyme. If the DPD enzyme is not functioning properly, there will be a reduced amount of exhaled labeled carbon dioxide (Diasio & Offer, 2022). Like any medical test, each of these tests come with their own drawbacks. Factors such as costs, ethnic differences, and lack of accuracy almost all must be considered before testing. In this article these components of DPD testing will be analyzed and discussed in order to provide a critical analysis of DPD testing.

2. Costs

2.1 Cost of DPD Testing

DPD testing costs can range up to approximately £354 per test , limiting the accessibility of this test (Vogel et al., 2020). A cost-effectiveness analysis of DPD testing, executed by scientists for PubMed, found that implementing DPD screening added a £61 cost per patient (Brooks et al, 2022). The paper also found that when the costs of DPD testing exceeded £225.21, the incremental cost-effectiveness ratio (ICER) was beyond £39,373 per quality adjusted life year (QALY)( Brooks et al, 2022). Looking at how the costs of testing range past this point, the ICER per QALY exceeds this amount. The National Institute for Health and Care Excellence claims that the cost per QALY threshold is between £20,000 and £30,000 in the UK, meaning the cost per QALY of DPD testing is around £10,000 over the expectation (Claxton et al., 2015). 

Between 2022-2023, the UK National Health Service (NHS) received an allotted budget of £153 billion (NHS, 2022). The NHS states that they plan to fund DPD testing through their regional teams, which feed off the money received in the budget (NHS, 2022). The NHS commissions several services, which all, in themselves, also have varieties of different branches (NHS, 2022). The business plan of the NHS states that for 2022/2023, after the costs of other aspects in their business plan, the NHS only have £2.4 million to directly invest with for commitments they talk about (NHS, 2022). These findings suggest  that the NHS is struggling to keep up with both corporate and societal commitments. This raises valid concerns whether the NHS can fund the high costs of DPD testing. Around 375,000 patients cope with cancer in the UK alone each year (Cancer Research UK, 2016). Increasing the uptake of DPD testing in cancer treatment would be a costly burden for the NHS. These costs may draw away from other critical issues in healthcare, including proper infrastructure, alternative cancer treatments, research, and more. Unlike these objectives, the usefulness of DPD testing across a nation has not been evaluated. From the perspective of a national healthcare system, the high costs of DPD testing makes implementation infeasible. In the event that a national healthcare organization is unable to fund DPD testing, the test could be at risk of becoming privatized. This means that DPD testing will only be available to patients who are able to afford it. 

Currently, the NIH openly acknowledges the fact that DPD testing is not able to perform 100% accurately (NIH, 2022). If medical professionals work to increase the accuracy of the testing, then national healthcare organizations will be more inclined to increase funding towards the objective. These funds could be raised through advocacy of the need for DPD testing and changes in current budgets. Increased funding of DPD testing will be vital in the future to sustain further implementation whilst avoiding privatization. The New York State Department of Health found that targeting the screening towards specific populations, which are at higher risk of having the deficiency, can help increase the accuracy until scientists are able to mechanically and scientifically create more accurate results overall (NY State Gov Department of Health, 1999). Additionally, experts in the NIH found that the cost of a DPD test is less than the cost of prolonged hospitalization (NIH, 2022). On average, a person has around a 2-8% chance of having a partial DPD deficiency (Cancer Research UK, 2023). However, since the tests are not 100% accurate, they therefore do not even meet the 2-8% chances of preventing someone from prolonged hospitalization (NIH, 2022). Hence, if the accuracy of DPD testing is scientifically increased while health organizations like the NHS work to simultaneously focus the screening on a target group , the test itself can become more efficient to receive funding. The NHS can also work to save more on these prolonged hospitalization costs, ultimately making DPD testing a cost-effective choice. 

3. Ethnic Differences on DPD Testings

3.1 Introduction

Currently, the practice of initially testing the dihydropyrimidine dehydrogenase (DPYD) gene has been introduced throughout parts of Europe and the United Kingdom (de With et al., 2023; PharmGKB, n.d.; Yoshino et al., 2021). The screening procedure examines DPYD gene variants well-documented in specifically caucasian patient groups. Consequently, the dosage adjustment recommendations, based on genotyping, are personalized based on these specific variants. This approach causes concerns regarding differences between DPYD gene variants among non-Caucasian population. It is not fully established how the genotype differences in diverse populations indicate complications within clinical tolerance of fluoropyrimidine-based chemotherapy and genotype-guided dose adjustment guidelines (White et al., 2021; Yoshino et al., 2021). Since ethnicity plays a pivotal role in shaping genetic variations that influence drug metabolism and response, variants associated with DPYD genes can impact the enzymatic activity of DPD. This in turn affects the metabolism of fluoropyrimidine-based chemotherapies. Hence, the prevailing focus on Caucasian populations in DPD tests may neglect the diverse genetic landscape found in non-Caucasian groups. By addressing the disparities and the inclusivity of DPD testing, further steps can be taken in ensuring equitable and effective personalized treatment strategies whilst encompassing a more diverse population.

3.2 DPYD Population Studies 

There have been limited studies conducted based on the diversity of DPYD genotype variants on non-Caucasian populations. Yet, a few studies have been completed to assess DPD activity in non-Caucasian populations (White et al., 2021; Lu et al., 1993; Sohn et al., 1999; Mattison et al., 2006).

Numerous studies spanning several decades have explored DPD activity as an indicator of 5-FU toxicity. The preferred method in measuring phenotypic activities across the studies are through the high performance liquid chromatography (HPLC) utilized to assess DPD activity within the cytosol of peripheral blood mononuclear cells (PBMC) cytosol in vitro. An alternative approach includes accessing the natural substrate uracil ratio to dihydrouracil (a product of enzyme activity in the plasma).

A study completed by Lu et al. (1993) evaluated patients who had undergone moderate-to-severe toxicity after FP treatments (62% Caucasian and 38% non-Caucasian). The study evaluated DPD activity through HPLC on PBMCs, with 124 volunteers and 25 selected cancer patients. The mean DPD activity was 0.425 ± 0.124 (SD) nmol/min/mg across all patients. Six out of the 25 cancer patients developed grade 2-3 toxicity with among the group of cancer patients, six out of twenty-five individuals experiencing grade 2–3 toxicity exhibited partial DPD deficiency, with their DPD activity being at or below 30% of that observed in healthy controls. Furthermore, three patients, who succumbed to toxicity associated with FP treatment, displayed profound deficiency, with their DPD activity falling below 10% of the normal level. Notably, there was no significant disparity in mean DPD activity between participants of Caucasian and non-Caucasian backgrounds (Lu et al., 1993). So the ranges of DPD testing accuracy in predicting toxicity itself can be a question; variation in DPD activity variation can be different among different ethnic groups, but it can also be different within the ethnic groups. 

Yet, a larger study of comparing DPD activities between non-Caucasian and Caucasian by Morsman et al. (2000), did find ethnic variation. In exploring in vitro DPD activity of 296 volunteers from different ethnic ancestries (South-West Asian, Kenyan, Ghanaian, and British-Caucasian), PBMC samples were analyzed where a significant lower mean activity (0.119 nmol/min/mg), is seen among the Ghanaian participants compared to the South-West Asian, Kenyan and British Caucasian populations (0.192, 0.194 and 0.215 nmol/min/mg). When compared to another reference group, the French-Caucasian population shows a mean of 0.22 nmol/min/mg, while an even higher mean was found within the Korean population. Investigated by Sohn et al. (1999), their study from 114 participants revealed a mean DPD activity of 0.280 nmol/min/mg. However, because Sohn’s studied participants were based on healthy volunteers, DPD activity on individual’s experience of severe FP toxicity could not be accurately established (Sohn et al., 1999; Gmeiner, 2021).

Mattison et al. (2006) conducted a study investigating DPD activity variations in individuals of African-American heritage. They examined PBMC samples from 258 healthy participants, including 149 African-Americans and 109 Caucasians. The research revealed a DPD deficiency in 5.8% of the overall group, with 8% of African-Americans and 2.8% of Caucasians exhibiting deficiency (Mattison et al., 2006). Notably, all individuals with profound deficiency were of African-American descent. The median DPD activity level was lower in African-Americans (0.26 ± 0.006 nmol/min/mg) compared to Caucasians (0.29 ± 0.007 nmol/min/mg), showing a statistically significant difference (P=0.002). However, the clinical impact of a 0.03 mmol/min/mg difference in median activity remains uncertain. Intriguingly, these median levels were higher than those reported by Morsman et al. (2000) for both Caucasian and African ancestry groups, suggesting potential measurement variability among centers or within similar ethnic subgroups. The genetic diversity and measurement variability indicates enzymatic activity inconsistencies. Small differences in DPD activity measurements implicate differences in treatment response considerations and emphasizes the multifaceted nature of DPD activity assessment. Patients, following the differences in ethnic background, might experience differences in severity of FP toxicity and with the variation of enzymatic activities, further standardized methodologies and research is needed upon DPD testing. 

c.1905+1G>A, c.2846A>T, c.1679T>G, and C.1236G>A are the more common DPYD variants, with the ability to predict the likelihood of experiencing toxicity from FP chemotherapy in individuals who carry either one or two copies of the variants, especially within the Caucasian population. However, the effects of these variants in individuals from non-Caucasian backgrounds exhibit notable variability. Research involving patients from diverse regions such as East Africa, China, and Japan has consistently demonstrated the absence of specific DPYD genetic variants, such as c.1905+1G>A, c.1679T>G, and c1601G>A. Similarly, the c.1236G>A variant was not found in a study of East African individuals, comprising mainly Somali and Kenyan subjects. The rarity of these variants even within Caucasian populations could be attributed to their low occurrence rates coupled with limited sample sizes. Hishinuma and colleagues extended this understanding by examining DPYD gene variations among a group of 1070 healthy Japanese individuals, previously subjected to whole-genome sequencing. This study unveiled 21 novel variants, of which 12 displayed decreased DPD enzymatic activity compared to standard controls when tested in vitro. The absence of the four common Caucasian DPYD variants was also validated, which means DPD testing can possibly fail to interpret the likelihood of FP toxicity. While this investigation showcased a distinctive collection of DPYD variants within the Japanese population that led to reduced DPD expression in vitro, establishing a clinical correlation among Japanese patients undergoing FP-based chemotherapy is essential to affirm the clinical relevance of these findings (White et al., 2021).

3.3 Impact of DPYD Variant Differences Across Diverse Ethnic Backgrounds

The diversity of DPYD variants across different ethnic populations adds intricacies to the current approach of DPYD genotyping for identifying individuals prone to heightened toxicity. As DPD testing mainly incorporates a targeted selection of variants, there may be potential gaps where patients of non-Caucasian backgrounds are not able to receive thorough or fitting genotyping variants specific to their genetic heritage (White et al., 2021). The implications of these variants extend to the variability in individuals’ responses to chemotherapy treatments due to DPD deficiencies. Yet, the existing shortage of extensive studies, and limited implementation of DPD testing worldwide, contribute to the scarcity of available data and consequently hinder the robustness of DPD testing outcomes. Hence, the current state of DPD testing captures the complexities arising from diverse ethnic backgrounds. This suggests the disadvantages of patients from non-Caucasian populations from lack of comprehensive genotyping and cause potential suboptimal treatment decisions and compromised therapeutic outcomes.

3.4 Potential Solutions 

Expanding genetic variant databases can be a solution in addressing the disparity of DPYD testing. The databases of DPD testing currently include more common DPYD gene variants that indicate FP toxicity in caucasians groups such as c.1905+1G>A, c.2846A>T, c.1679T>G, and C.1236G>A. Hence, by incorporating genetic data to include a more diverse population group, more accurate genotyping and dosage adjustment of FP based chemotherapy can be achieved. This can also possibly be achieved with further improvements of sequencing technologies in the medical field. 

An alternative of FP based chemotherapy treatment is the S-1 treatment. S-1 is an oral anticancer drug with components of tegafur, gimeracil, and oteracil potassium. Studies suggest that S-1 can be a safe alternative for fluoropyrimidines, as the DPD is already inactivated by gimeracil (CDHP) within the S-1 components. In addition, the drug has demonstrated a significant improvement of overall survival rate when used in chemotherapy. So instead of relying on DPD testing and FP-based chemotherapy, alternatives can also be considered regarding the diverse range of genetic variants that currently poses a problem (Leung, 2017; Cao et al., 2014).

Further development of comprehensive guidelines can also benefit the accuracy and inclusivity of DPYD testing. Guidelines can be negotiated between regulatory bodies and medical associations in defining and identifying wider ranges of DPYD variants. This can ensure that individuals from non-Caucasian backgrounds receive more accurate genotyping results and better personalized treatment recommendations. For example, in 2020, the European Society for Medical Oncology (ESMO) and Japanese Society for Medical Oncology (JSMO) conducted a meeting in negotiating clinical practice guidelines for the diagnosis, treatment, and follow-up of localized colon cancer. They accounted for the ethnic differences of Asians populations and, through consensus reached by China (CSCO), India (ISMPO), Korea (KSMO), Malaysia (MOS), Singapore (SSO), and Taiwan(TOS), developed a set of guidelines in treatment practices. With more of these guidelines developed in treatment taking account of different ethnic backgrounds and through discussions among different culture groups, the future of DPYD testing will be enhanced and gain wider usages among different populations (Yoshino et al., 2021).

4. Test Inaccuracies and False test results

4.1 Introduction

The presence of false negatives and false-positives within both DPYD genotyping and phenotyping can be crucial. It can determine the efficiency of fluoropyrimidine drugs such as capecitabine and fluorouracil (5-FU). Analytical validity refers to whether or not the patient has DPD deficiency, while clinical validity will make toxicity predictions that will determine the Fluoropyrimidine (FP) dosing received by the patient. Analytical validity can completely determine whether or not a patient receives the drugs, clinical validity can determine the starting doses of a drug. When the DPYD test shows the presence of the DPYD gene and hence DPD deficiency, oncologists and physicians will reduce the starting dose to eliminate the chances of fatality or toxicity. In this situation, the effectiveness of the fluoropyrimidine drugs will be questioned, and the patient’s cancer will only worsen. 

4.2 False-negatives and false-positives within DPYD genotyping

Throughout Europe, notably in France, the most common DPYD phenotyping method is through measuring uracil concentration within the plasma (uracilemia). This is done through blood sampling. A uracil concentration level of over 150 nanograms (ng)/mL suggests complete DPD deficiency, hence an alternative to FP treatments. While a uracilemia measurement between 16ng/mL and 150ng/mL suggests partial DPD deficiency (Laures et al., 2022). In this case, a reduction in FP doses would be necessary. 

One study, carried out by Royer et al. (2023), looked at the impact of renal impairment in DPYD testing. This is done through a measure of the expected glomerular filtration rate (eGFR), or the amount of blood that passes through the filtration gate of the kidney each minute. The researchers took patients from three major French medical centers, and drew their blood consistently for DPD phenotyping. DPYD phenotyping based on uracil concentration can also be influenced and altered by a number of biological factors: renal impairment, renal function, hepatic function, or even food intake. Renal impairment, however, has the largest proven effect on false-results within DPD testing.

Together with uracilemia levels, every patient’s eGFR measures were documented and recorded. The same patients’ uracilemia and eGFR measures were again documented after dialysis, serving as the control group. With 3039 participants, the study found a significant relationship between renal impairment and DPD deficiency (Royer et al, 2023). Oftentimes, patients with renal impairment experience low eGFR levels. Likewise, the study found an inverse relationship between eGFR levels and the likelihood of DPD deficiency. The study separated the participants into A, dialysis patients, B, participants with renal impairment, and C, patients with normal renal function (stable eGFR levels). Each group was measured before and after dialysis. For group B, their results were shocking. The DPD deficiency frequency dropped from 83.3% to 16.6% after dialysis. On the contrary, group A showed a less significant result, as uracilemia levels did not change at all. This could be explained by the patients’ normal uracilemia levels due to routine dialysis. Group C, similarly, saw a small decrease in uracilemia levels after dialysis. Group C participants also experienced much lower uracilemia levels, which is expected due to the absence of renal impairment. Yet, the drop from 83.3% to 16.6% for group B participants is still indicative of the strong correlation between uracilemia levels and renal impairment; hence the likelihood of false DPYD phenotyping results within patients with renal impairment (Boyer et al, 2023). 

Despite the findings, it is impossible to rule out the possibility that uracilemia levels of a patient would decrease below 16 nanograms/mL after dialysis in a patient with both kidney impairment and DPD deficiency. In other words, a false negative is very possible. Yet, analyzing results after dialysis is still the best method due to three main reasons: not all patients’ uracil concentration levels drop below the DPD deficiency threshold; there is a r = 0.80 correlation between uracilemia level before and after dialysis, suggesting that it is very possible for uracil concentration to remain high even after dialysis. Furthermore, the frequency of DPD deficient patients after dialysis in group B and C were really similar, suggesting a fair result.

Hence, DPD genotyping through measuring uracil concentration levels can be altered by renal impairment, since the study shows renal impairment can massively change the way eGFR and uracilemia levels show up on blood tests. After dialysis, results can also vary. In rare occasions, DPD phenotyping results will show the absence of the DPYD gene in a DPD deficient patient due to previous renal impairment, leading physicians to administer a high starting dose without full knowledge of the patient’s condition. On other occasions, renal impairment will lead to high uracilemia levels on blood tests, even without the DPYD gene. This false-positive result could result in a lower FP dose for the patient, reducing the efficiency of the drug. All in all, the use of uracil concentration levels in DPYD phenotyping can mask the true test results, mainly due to renal impairment. 

4.3 False-negative and false-positives within DPYD phenotyping

The DPYD*2A gene, the most common mutation associated with DPD deficiency, changes guanine to adenine. In turn, exon 14, an essential part of the gene when producing mRNA, is skipped. Hence, a piece of the mRNA will not be produced. In other words, a homozygous DPYD*2A would mean complete DPD deficiency, while a heterozygous would mean partial DPD deficiency (Saif et al, 2006). Albeit less common, the DPYD*13 gene is at risk of causing clinical false negatives within DPYD testing. The genetic mutation would cause guanine to represent an original thymine in the 1679th nucleotide of a DNA. The p.D949VT is also associated with DPD deficiency, in which the protein sequence suffers a mutation. The amino acid at the 949th position of the protein sequence, which is supposed to be an aspartic acid, has turned into valine (Lee et al., 2014). 

A pharmacogenetic study in Europe investigated 1545 patients over four years through a phase-3 clinical trial, which showed further evidence of the aforementioned variants contributing to false test results (Boige et al., 2016). They discovered that testing for the p.D949VT gene saw a specificity of 100% and sensitivity of 2% (Innocenti et al, 2020). This means that everyone who had the genetic variant tested positive. However, the 2% sensitivity is a shocking number. Of everyone who was negative, only 2% tested true negative. In other words, it is very likely that everyone will test positive, leading to a significantly high percentage of people testing positive despite not having the genetic variant, creating an analytic false-positive scenario. The two genetic variants, DPYD*2A and DPYD*13, also saw similar numbers, meaning that many people were receiving reduced or no fluoropyrimidine dose at all, hindering their chemotherapy cancer treatment. This highlights the fact that the DPYD*2A genetic variant is the most common mutation associated with DPYD testing and only increases the chances of an analytical false-positive test. 

Another study focused on clinical false-positive tests (Hertz et al, 2023). Rather than determining whether or not patients had the genetic variation, this study focused on the reduced or increased FP dosing based on clinical test results. In the United States, the FDA rejected mandatory DPYD testing in patients considering fluoropyrimidine chemotherapy treatment. Genetic tests conducted and approved by the FDA attempted to predict clinical false results. They predicted that the chances of clinical false positives were around 20% . This means that around 20% of patients would receive an unnecessary reduction in their starting dose due to the test inaccurately predicting their recommended starting dose, based on the level of DPD deficiency. On the other hand, the study predicted around 30% of the patients experienced toxicity from their suggested starting dose based on their level of deficiency (Hertz et al, 2023). In these false-negative scenarios, patients would suffer from unexpected levels of toxicity due to receiving starting doses that the body could not tolerate.

As these studies are mere predictions based on patient histories, there could be differences in the numbers and statistics. Yet, one thing is for sure: the lack of accuracy of DPYD tests, whether it is clinical or analytical, has to be questioned. Their influence on patients receiving FP doses is too significant to be ignored. 

4.4 Potential solutions

As studies have shown that renal impairment can mask DPYD phenotyping results, this patient group would need to refer to DPYD genotyping to ensure accurate tests. In fact, this is also the solution to false-positives and negatives within DPYD testing. Patient groups have to be identified in order to select the right tests for them. Patients with renal or hepatic impairments should refer to DPYD phenotyping. Furthermore, further research has to be done in order to identify patient groups at risk of receiving false phenotyping results. Patients also have to be informed of the risks that come with these tests. Research also has to be done to minimize the risk of both analytical and clinical false test results within DPYD genotyping. 

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