Αρχειοθήκη ιστολογίου

Αλέξανδρος Γ. Σφακιανάκης
ΩτοΡινοΛαρυγγολόγος
Αναπαύσεως 5
Άγιος Νικόλαος Κρήτη 72100
2841026182
6032607174

Τρίτη 19 Ιανουαρίου 2021

Biomarker testing and mutation prevalence in metastatic colorectal cancer patients in five European countries using a large oncology database

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Background: The literature on biomarker testing for metastatic colorectal cancer (mCRC) in Europe is scarce. This study aimed to estimate the percentage of mCRC patients from five European countries tested for biomarkers over time. Materials & methods: An oncology database was retrospectively analyzed; evaluated biomarkers were RAS, BRAF and microsatellite instability (MSI). The patients were drug treated during 2018 and tested for relevant biomarkers in 2013–2018. Results:RAS testing was conducted in >90% of mCRC patients from 2014 onwards. BRAF testing increased from 31% of mCRC patients in 2013 to 67% in 2018. MSI testing increased from 10 to 41%. There was no notable trend over time for RAS and BRAF mutation or MSI-high prevalence. Conclusion: Biomarker testing among patients diagnosed with mCRC was increased over time. This study demonstrates the quick uptake of biomarker testing in clinical pra ctice. These findings are significant as biomarker-based drugs are becoming more common.

Lay abstract
Each patient's cancer is unique. To find the best medicine for each patient, doctors perform tests to look at the cancer's genes. It is unknown how often and how well these tests are done. We tried to find this out for patients with cancer of the bowel or rectum that has spread to other organs. We found that an important genetic test called RAS is done in most patients. Other tests, called BRAF and microsatellite instability, are also conducted increasingly frequently. This is important because the results of such tests allow doctors to decide which drug(s) should be the most effective depending on the patient's cancer genes.

Keywords:
biomarkerBRAFEGFRmCRCMSIprevalenceRAS
Globally, colorectal cancer (CRC) is the third most frequently diagnosed malignancy in men and the second in women, with an incidence of 1.8 million and almost 861,000 deaths in 2018 alone according to the WHO's GLOBOCAN database [1]. Of those, 20–25% already have metastatic CRC (mCRC) at initial diagnosis [2,3], which dramatically reduces survival. The 5-year survival rate is 90% for localized CRC versus 71% for CRC with regional spread and 14% for patients with distant metastases [4].

Clinical trials and observational studies of anti-EGFR monoclonal antibodies (mAbs) in mCRC indicated differences in response between patients with or without mutations in the RAS family of genes compared with the overall study population [5–18]. For RAS wild-type patients, a recent Cochrane systematic review quantified anti-EGFR mAb-induced risk reduction compared with standard treatments to be 40% for disease progression, 23% for mortality and the rate of early tumor shrinkage to have increased from 21 to 48% [19].

Therefore, RAS mutation status was established as an important marker for patient selection for anti-EGFR mAb-containing therapy by leading guideline bodies, such as the European Society of Medical Oncology (ESMO) [20]. The EMA restricted the indication for both, panitumumab and subsequently cetuximab, to RAS wild-type tumors in 2013 [21,22].

The validity of BRAF testing was established from the 2014 ESMO guidelines onwards [20,23,24]; however, it is not a prerequisite of anti-EGFR mAb use according to the respective EMA labels. Inclusion of BRAF testing was originally done for prognostic reasons [25,26].

Since the introduction of RAS testing in Europe, several observational studies were conducted to estimate the prevalence of RAS mutation in mCRC patients in the real-world setting. These studies showed RAS mutation prevalence estimates in the real world (44–46%) compared with the estimates from randomized controlled trials (RCTs) (43–56%) [27–30].

BRAF mutations are less common, affecting only 8–12% of mCRC patients [26,31–34]. BRAF mutations appear to be predominantly found in patients with right-sided primary tumors (68%, vs 35% in left-sided [34]), and are almost never found in combination with RAS mutations. BRAF-mutant status overlaps with the presence of microsatellite instability (MSI) in about a third of tumors [34].

Although several studies have been carried out to estimate biomarker prevalence, there has been limited published work on the percentage of diagnostic testing among mCRC patients in Europe [35].

The current study is based on an oncology database that includes patients from ten countries and over 35 cancer indications. It is designed as repeated quarterly cross-sectional cohorts capturing patient information through electronic case report forms (eCRFs). The study aim was to estimate the percentage of mCRC patients tested for biomarkers in Europe, and the mutation prevalence over time.

Materials & methods
Database
The oncology database used for the present research (Oncology Dynamics™, IQVIA Ltd, London, UK) is a secondary database utilizing primary data collected in patient files. It includes data from ten countries (France, Germany, Italy, Spain, the UK, China, Japan, South Korea, Saudi Arabia and Mexico). It is designed as repeated quarterly cross-sectional cohorts and contains more than 167,000 cancer cases per year and over 35 cancer indications. This design ensures there is a large sample size even for rarer cancers such as acute lymphoblastic leukemia or glioblastoma. The patient numbers per cancer indication and country as collected in the year 2018 are given in Supplementary Table 1.

The database captures patient information via a standardized eCRF entered by the treating physician from patients' health records. It is limited to patients treated with a cancer drug at the time of data collection, and excludes patients solely treated with radiotherapy, surgery, supportive care or on active surveillance.

Stratified random sampling is used to select physicians to represent the distribution of specialties for each cancer indication and country. In most countries included in the database, cancer care is administered in hospitals; the only exception is Germany where both hospitals and office-based physicians administer anticancer therapy. The sample design aims to target no more than three physicians from the same hospital (and only one per ward) to avoid a cluster effect or duplication of patients and ensure a large number and variety of sites. At the patient level, a systematic sampling approach is used. Indeed, at each quarterly data collection point, participating physicians at each center are instructed to select systematically for inclusion the most recent patients (i.e., office encounters during the last 7–14 days) up to a predefined quota.

Key data attributes include patient demographic and clinical characteristics at time of diagnosis, as well as treatment information at 'current' (at the time of data extraction) and 'previous' line of therapy (as defined by the treating physician). The most recent diagnostic test information is reported if carried out at any time since diagnosis. Detailed variables are shown in Supplementary Table 2. The online supplemental material provides further methodological details of the database.

Quality control takes place at various stages, during data collection, coding, processing and creation of the final dataset for each quarterly data generation cycle. During data entry, the validation check system includes rules to avoid reporting of incorrect values (i.e., negative values between date of diagnosis and start of the current treatment) or are validated against previous answers to detect inadmissible responses (e.g., absence of metastatic sites in patients with stage IV cancer). Dosage of each drug reported by the physician is checked against a drug dose reference file and the reporting physician is prompted if out of range to ensure that it conforms to acceptable dose levels. Data coding uses standardized procedures to prevent errors in coding of free-text entries. Implausible data entries are checked directly with the participating physicians.

Objectives
The primary objectives of the study were to estimate the percentage of mCRC patients tested for RAS and BRAF (all types) mutations over time and to estimate the percentage of RAS and BRAF-mutant tests for mCRC patients over time. The secondary objectives included MSI testing and RAS, and BRAF testing specifically in mCRC patients receiving anti-EGFR mAbs.

Eligibility criteria
This study included mCRC patients from France, Germany, Italy, Spain and the UK, diagnosed with CRC, who received active anticancer treatment in the advanced/metastatic setting in 2018 and had a diagnosis date between July 2013 and December 2018. The International Classification of Diseases – Tenth Revision codes were used to identify the CRC population in combination with the staging information, which was used to define the metastatic status. Clinical trial participants and patients not on active anticancer therapy are not captured within the database as interest is on patients treated under routine clinical practice excluding experimental treatments.

Primary tumor location was assigned by the treating physician. When recorded as unknown by the physician, the International Classification of Diseases – Tenth Revision code, from which anatomy of tumor location could be determined, was used where available. The definition of primary tumor location was in line with previous analyses [36], where left-sided tumors were defined as those originating in the splenic flexure, descending colon, sigmoid colon or rectum. Right-sided tumors were defined as those originating in the appendix, cecum, ascending colon or hepatic flexure as well as the transversum – between the hepatic and splenic flexure.

Statistical considerations
The analysis was descriptive providing frequencies and percentages with their corresponding 95% CI. SAS© Software was used (Enterprise Guide Version [7.1] on Linux [LIN X64], SAS Institute, Inc., NC, USA).

Results
Overall, 4455 mCRC patients were included in the study, 982 of whom received anti-EGFR mAb therapy. The patients captured were mostly treated in public facilities (n = 3310; 74.3%), mainly in France, Italy, Spain and the UK. In Italy (n = 1012; 76.3%) and France (n = 481; 63.3%) the majority of patients were reported as from nonuniversity hospitals, while in Spain (n = 427; 64.2%) and the UK (n = 536; 66.3%) the majority was from university hospitals; in Germany most patients were from office-based practitioners (n = 574; 64.1%). The current line of mCRC therapy was mainly prescribed by oncologists (n = 3121; 70.1%) or onco-hematologists (n = 837; 18.8%). Characteristics by site and participating physicians are shown in Table 1A.

Table 1. Demographic and clinical characteristics of metastatic colorectal cancer patients by country.
(A) Description of patients' cases by site and participating physicians
France Germany Italy Spain United Kingdom Total
All mCRC patients 760 895 1326 665 809 4455
Type of treating hospital
– Office-based practitioner – 574 (64.1) – – – 574 (12.9)
– Private 29 (3.8) 51 (5.7) 49 (3.7) 161 (24.2) 13 (1.6) 303 (6.8)
– Private – not for profit 179 (23.6) 52 (5.8) 27 (2.0) 10 (1.5) – 268 (6.0)
– Public 552 (72.6) 218 (24.4) 1250 (94.3) 494 (74.3) 796 (98.4) 3310 (74.3)
Treating hospital status
– Nonuniversity 481 (63.3) 216 (24.1) 1012 (76.3) 238 (35.8) 273 (33.7) 2220 (49.8)
– University 279 (36.7) 105 (11.7) 314 (23.7) 427 (64.2) 536 (66.3) 1661 (37.3)
– Office-based practitioner – 574 (64.1) – 574 (37.3)
Physician specialty
– Gastroenterologist 238 (31.3) 51 (5.7) 289 (6.5)
– Hepatologist – – 4 (0.3) 4 (0.1)
– Onco-hematologist – 837 (93.5) 837 (18.8)
– Oncologist 505 (66.4) – 1302 (98.2) 665 (100) 649 (80.2) 3121 (70.1)
– Radiotherapist 12 (1.6) 6 (0.7) 160 (19.8) (178 (4.0)
– Others 5 (0.7) 1 (0.1) 20 (1.5) 26 (0.6)
(B) Patient demographics
France Germany Italy Spain United Kingdom Total
All mCRC patients 760 895 1326 665 809 4455
Gender, n (%)
– Females 299 (39.3) 337 (37.7) 544 (41.0) 251 (37.7) 317 (39.2) 1748 (39.2)
– Males 461 (60.7) 558 (62.3) 782 (59.0) 414 (62.3) 492 (60.8) 2707 (60.8)
Age group at current therapy, n (%)
– <30 2 (0.3) 2 (0.2) 2 (0.2) 1 (0.2) 3 (0.4) 10 (0.2)
– 31–40 12 (1.6) 3 (0.3) 19 (1.4) 4 (0.6) 34 (4.2) 72 (1.6)
– 41–50 37 (4.9) 60 (6.7) 97 (7.3) 26 (3.9) 74 (9.1) 294 (6.6)
– 51–60 120 (15.8) 154 (17.2) 257 (19.4) 144 (21.7) 192 (23.7) 867 (19.5)
– 61–70 320 (42.1) 362 (40.4) 442 (33.3) 228 (34.3) 269 (33.3) 1621 (36.4)
– 71–80 217 (28.6) 236 (26.4) 372 (28.1) 187 (28.1) 195 (24.1) 1207 (27.1)
– >80 52 (6.8) 78 (8.7) 137 (10.3) 75 (11.3) 42 (5.2) 384 (8.6)
Age at current therapy†, years
– Mean (SD) 66.7 (10.0) 66.5 (10.1) 66.5 (11.1) 67.2 (10.3) 63.3 (11.7) 66.0 (10.8)
– Median (IQR) 68 (63, 73) 68 (63, 73) 68 (58, 73) 68 (58, 73) 63 (53, 73) 68 (58, 73)
(C) Clinical characteristics
France Germany Italy Spain United Kingdom Total
All mCRC patients 760 895 1326 665 809 4455
Stage at diagnosis‡, n (%)
– Stage I 4 (0.5) 18 (2.0) 5 (0.4) 5 (0.8) 6 (0.7) 38 (0.9)
– Stage II 26 (3.4) 36 (4.0) 65 (4.9) 25 (3.8) 38 (4.7) 190 (4.3)
– Stage III 103 (13.6) 121 (13.5) 244 (18.4) 57 (8.6) 107 (13.2) 632 (14.2)
– Stage IV 627 (82.5) 720 (80.4) 889 (67.0) 578 (86.9) 658 (81.3) 3472 (77.9)
– Unknown – – 123 (9.3) – – 123 (2.8)
Tumor location, n (%)
– Right side§ 266 (35.0) 280 (31.3) 521 (39.3) 250 (37.6) 282 (34.9) 1599 (35.9)
– Left side¶ 476 (62.6) 603 (67.4) 797 (60.1) 412 (62.0) 500 (61.8) 2788 (62.6)
– Unknown 18 (2.4) 12 (1.3) 8 (0.6) 3 (0.5) 27 (3.3) 68 (1.5)
Current metastatic sites, n (%)
– 1 site 310 (40.8) 332 (37.1) 676 (51.0) 265 (39.8) 291 (36.0) 1874 (42.1)
– 2 sites 274 (36.1) 271 (30.3) 448 (33.8) 258 (38.8) 336 (41.5) 1587 (35.6)
– 3 sites 130 (17.1) 227 (25.4) 148 (11.2) 112 (16.8) 156 (19.3) 773 (17.4)
– 4 sites 41 (5.4) 52 (5.8) 39 (2.9) 24 (3.6) 22 (2.7) 178 (4.0)
– 5+ sites 5 (0.7) 13 (1.5) 15 (1.1) 6 (0.9) 4 (0.5) 43 (1.0)
Site of metastases, n (%)
– Liver and lung combination 179 (23.6) 244 (27.3) 292 (22.0) 179 (26.9) 232 (28.7) 1126 (25.3)
– Liver only 240 (31.6) 218 (24.4) 447 (33.7) 185 (27.8) 192 (23.7) 1282 (28.8)
– Liver with other combination 222 (29.2) 266 (29.7) 292 (22.0) 144 (21.7) 182 (22.5) 1106 (24.8)
– Lung only 25 (3.3) 23 (2.6) 60 (4.5) 46 (6.9) 47 (5.8) 201 (4.5)
– Lung with other combination 17 (2.2) 25 (2.8) 39 (2.9) 45 (6.8) 48 (5.9) 174 (3.9)
– Other (no liver or lung) 77 (10.1) 119 (13.3) 196 (14.8) 66 (9.9) 108 (13.3) 566 (12.7)
Current line of anticancer therapy in advanced/metastatic stage, n (%)
– Neoadjuvant 23 (3.0) 14 (1.6) 25 (1.9) 11 (1.7) 27 (3.3) 100 (2.2)
–Adjuvant 29 (3.8) 13 (1.5) 21 (1.6) 6 (0.9) 17 (2.1) 86 (1.9)
– 1st line 488 (64.2) 650 (72.6) 1026 (77.4) 460 (69.2) 563 (69.6) 3187 (71.5)
– 2nd line 138 (18.2) 139 (15.5) 167 (12.6) 132 (19.8) 152 (18.8) 728 (16.3)
– 3rd line 58 (7.6) 44 (4.9) 69 (5.2) 44 (6.6) 41 (5.1) 256 (5.7)
– 4th or subsequent line 24 (3.2) 35 (3.9) 18 (1.4) 12 (1.8) 9 (1.1) 98 (2.2)
BMI at current therapy
– Mean (SD) 24.1 (3.4) 25.1 (3.9) 24.7 (3.6) 24.6 (3.1) 25.8 (4.5) 24.9 (3.8)
– Median (IQR) 23.8 (22, 26.2) 24.6 (22.5, 27.4) 24.5 (22.3, 26.9) 24.3 (22.7, 26.3) 25.1 (22.7, 28) 24.5 (22.4, 26.9)
– Min, max 13.7, 40.8 15.6, 45.4 13.3, 42.7 15.8, 39.1 15.6, 50 13.3, 50
ECOG status at current therapy, n (%)
– 0 129 (17.0) 151 (16.9) 531 (40.0) 166 (25.0) 187 (23.1) 1164 (26.1)
– 1 442 (58.2) 553 (61.8) 646 (48.7) 416 (62.6) 542 (67.0) 2599 (58.3)
– 2 169 (22.2) 185 (20.7) 113 (8.5) 76 (11.4) 77 (9.5) 620 (13.9)
– 3 19 (2.5) 4 (0.4) 10 (0.8) 5 (0.8) 2 (0.2) 40 (0.9)
– 4 1 (0.1) 2 (0.2) 1 (0.1) 2 (0.3) 1 (0.1) 7 (0.2)
– Unknown – – 25 (1.9) – – 25 (0.6)
Percentages are based on the number of participating patients overall and by country.

†Exact age is not recorded within the database due to data governance rule relating to anonymization. Instead the following groups are provided: <16, 16–20, 21–25, 26–30, 31–35, 36–40, 41–45, 46–50, 51–55, 56–60, 61–65, 66–70, 71–75, 76–80 and >80 years old. To provide estimates of the mean and median of 'age', the age groups were substituted by the mid-range value, e.g., '<16' is substituted by '8', '16–20' by '18', etc.

‡Using TNM staging.

§Primary tumors originating in the appendix, cecum, ascending colon, hepatic flexure or transversum (between hepatic and splenic flexure).

¶Primary tumors originating in the splenic flexure, descending colon, sigmoid colon or rectum.

0: Asymptomatic; 1: Symptomatic and fully ambulatory; 2: Symptomatic and in bed <50% of the day; 3: Symptomatic and in bed >50% of the day; 4: Bedridden; ECOG: Eastern Cooperative Oncology Group; IQR: Interquartile range; mCRC: Metastatic colorectal cancer; SD: Standard deviation.

Most patients were male (n = 2707; 60.8%) and of advanced age, with 36.4% being 61–70 years (n = 1621) and 27.1% being 71–80 years old (n = 1207); median age was 68 years (Q1: 58 and Q3: 73; Table 1B). Gender and age distribution were consistent across countries. The vast majority of this cohort of mCRC patients were diagnosed with stage IV cancer (n = 3472; 77.9%) and were in their first line of treatment of advanced/metastatic stage cancer (n = 3187; 71.5%), with 16.3% being in second-line treatment (n = 728). The primary tumor was located on the left side in 62.6% of patients (n = 2788), on the right side in 35.9% (n = 1599) and location was unknown in 1.5% (n = 68). The site of metastasis was liver only in 28.8% of patients (n = 1282), a combination of either liver and lung in 25.3% (n = 1126) or liver and another site in 24.8% (n = 1106); 57.9% of patients (n = 2581) had two or more sites of metastasis. ECOG status was 0 or 1 in 84.5% (n = 3763) and ≥2 in 15.0% (n = 667; T able 1C).

Biomarker & MSI testing
As the eligibility criteria included patients on active anticancer drug treatment during 2018, the number of mCRC patients for whom testing percentage was calculated decreased going back in time (e.g., 2181 patients were tested for RAS in 2018 and only 34 in 2013, Figure 1).


Figure 1. Percentage of metastatic colorectal cancer patients tested for RAS & BRAF mutations over time.
(A) mCRC patients tested for RAS mutations, overall and in those receiving anti-EGFR mAb treatment. (B) mCRC patients tested for BRAF mutations, overall and in those receiving anti-EGFR mAb treatment.

mAb: Monoclonal antibody; mCRC: Metastatic colorectal cancer.

RAS testing was conducted in over 90% of mCRC patients from 2014 onwards (Figure 1A). BRAF testing rate increased from 31.0% in 2013 to approximately 50% between 2014 and 2016 and above 60% in 2017 and 2018 (Figure 1B). The percentage of mCRC patients tested for MSI increased over time from 10.0% in 2013 to 41.4% in 2018. The MSI assessment was performed more frequently for patients <50 years of age (56.5%; 95% CI: 48.5–64.3 in 2018) compared with those ≥50 years (40.0%; 95% CI: 7.7–42.3 in 2018; Table 2).

Table 2. Percentage of patients tested for microsatellite instability and confirmed microsatellite instability-high status over time, n/N (%) (95% CI).
2013 2014 2015 2016 2017 2018
mCRC patients tested for MSI 5/50 (10.0)
(3.3, 21.8) 40/173 (23.1)
(17.1, 30.1) 73/318 (23.0)
(18.4, 28.0) 159/551 (28.9)
(25.1, 32.8) 502/1430 (35.1)
(32.6, 37.6) 800/1933 (41.4)
(39.2, 43.6)
<50 years of age† 0/1 (0.0)
(0.0, 97.5) 1/6 (16.7)
(0.4, 64.1) 7/20 (35.0)
(15.4, 59.2) 15/46 (32.6)
(19.5, 48.0) 57/142 (40.1)
(32.0, 48.7) 91/161 (56.5)
(48.5, 64.3)
≥50 years of age† 5/49 (10.2)
(3.4, 22.2) 39/167 (23.4)
(17.2, 30.5) 66/298 (22.1)
(17.6, 27.3) 144/505 (28.5)
(24.6, 32.7) 445/1288 (34.5)
(32.0, 37.2) 709/1772 (40.0)
(37.7, 42.3)
mCRC patients with confirmed MSI-H status 1/5 (20.0)
(0.5, 71.6) 4/40 (10.0)
(2.8, 23.7) 12/73 (16.4)
(8.8, 27.0) 20/157 (12.7)
(8.0, 19.0) 73/472 (15.5)
(12.3, 19.0) 87/721 (12.1)
(9.8, 14.7)
†Age at current therapy.

mCRC: Metastatic colorectal cancer; MSI: Microsatellite instability; MSI-H: MSI-high.

The frequency of RAS testing was consistently high in all five countries. For BRAF, France had the highest testing rate (73.6%, 95% CI: 70.3–76.7) followed by Italy (65.9%, 95% CI: 63.3–68.5). MSI testing rates were generally lower, but again most frequently carried out in France (51.8%, 95% CI: 48.2–55.4) and Spain (49.3%, 95% CI: 45.5–53.2). The online supplement shows the testing frequencies for RAS, BRAF and MSI by country (Supplementary Table 5).

Mutation & MSI-high prevalence
In 2018, the percentage of mCRC patients with confirmed RAS mutant tumors was 53.6% (95% CI: 51.3–55.8) with no notable trend over time (Table 3). Prevalence of confirmed BRAF mutation status was 7.0% (95% CI: 5.6–8.5; Table 3).

Table 3. Percentage of metastatic colorectal cancer patients with mutant biomarker status over time, n/N (%) (95% CI).
2013 2014 2015 2016 2017 2018
RAS biomarker
overall 10/28 (35.7)
(18.6, 55.9) 49/102 (48.0)
(38.0, 58.2) 93/204 (45.6)
(38.6, 52.7) 229/414 (55.3)
(50.4, 60.2) 716/1351 (53.0)
(50.3, 55.7) 1,007/1880 (53.6)
(51.3, 55.8)
BRAF biomarker
overall 0/13 (0.0)
(0.0, 24.7) 0/68 (0.0)
(0.0, 5.3) 4/131 (3.1)
(0.8, 7.6) 21/275 (7.6)
(4.8, 11.4) 67/928 (7.2)
(5.6, 9.1) 90/1294 (7.0)
(5.6, 8.5)
RAS biomarker
anti-EGFR mAb patients 0/5 (0.0)
(0.0, 52.2) 1/23 (4.3)
(0.1, 21.9) 1/43 (2.3)
(0.1, 12.3) 3/77 (3.9)
(0.8, 11.0) 7/317 (2.2)
(0.9, 4.5) 18/512 (3.5)
(2.1, 5.5)
BRAF biomarker
anti-EGFR mAb patients 0/3 (0.0)
(0.0, 70.8) 0/17 (0.0)
(0.0, 19.5) 1/34 (2.9)
(0.1, 15.3) 4/59 (6.8)
(1.9, 16.5) 9/247 (3.6)
(1.7, 6.8) 23/425 (5.4)
(3.5, 8.0)
mAb: Monoclonal antibody.

Of mCRC patients in general the rate of MSI-high (MSI-H) tumors ranged between 10 and 16% over time (Table 3). There was no notable difference in the rate of MSI-H tumors by stage at time of diagnosis (Supplementary Table 6).

Testing & prevalence in patients receiving anti-EGFR mAbs
Of patients receiving anti-EGFR mAbs in 2018, almost all (99.8%; 95% CI: 98.9–100.0) were tested for RAS (Figure 1A). Of those, 3.5% (95% CI: 2.1–5.5) had confirmed RAS-mutant tumor status (Table 4). The percentage of patients receiving anti-EGFR mAbs that were tested for BRAF increased from below 60% in 2014 to 87% in 2018 (Figure 1B). The BRAF mutation prevalence in these patients was 5.4% in 2018 (95% CI: 3.5–8.0; Table 4).

Discussion
This study aimed to describe a population of patients actively treated for mCRC in 2018 and to estimate the percentage of these patients tested for biomarkers and the mutation prevalence over time (between 2013 and 2018). It was found that over 90% of mCRC patients receiving anticancer treatment had been tested for RAS, with consistent RAS testing rates over time. Testing for BRAF was less prevalent but increasing to approximately two-thirds of patients over time. The prevalence of RAS and BRAF mutations, respectively, were stable over time. Almost all patients receiving anti-EGFR mAb therapy were tested for RAS. In 2018, BRAF was tested in approximately 90% of patients receiving anti-EGFR mAbs, suggesting that BRAF testing is an easy add-on test when RAS testing is conducted as a default for anti-EGFR mAbs and/or that treating physicians believe in the value of BRAF in the anti-EGFR mAb treatment decision. MSI testing was done in more than half of patients <50 years of age and appro ximately 40% in the older age group in 2018. MSI-H status was confirmed in 12.1% overall.

There is very limited information from observational studies describing characteristics of mCRC patients as the present study with several treatment lines and active treatments covered. However, the patient and disease characteristics found in the current study appear to be consistent with the literature. Of the total mCRC patients, 60.8% were male and the median age was 68 years. The stages at diagnosis were 0.9% stage I, 4.3% stage II, 14.2% stage III and 77.9% stage IV; 2.8% stage unknown. A study investigating the characteristics of mCRC patients participating in clinical trials found a median age of 62 years with 60% male patients. The clinical characteristics of these patients would not be expected to be representative of real-world clinical practice [37]. A Canadian chart review study following retrospectively mCRC patients from their first line of therapy in the metastatic setting onwards, found a median age at initiation of first-line therapy of 61.5 years with a distributio n of stages at diagnosis of 2% stage I, 9% stage II, 13% stage III and 78% stage IV [38].

Using the Oncology Analyzer™ database (predecessor of the Oncology Dynamics™ database prior to 2017), Bruce et al. [39] documented a shift in RAS testing patterns from KRAS only to full RAS testing after the respective anti-EGFR mAb label changes in late 2013 (14% full RAS testing prior to label change, 44% in Q3/2014, ~1 year after the label change). Similarly, Trojan et al. [40] demonstrated a very quick uptake of full RAS testing after the anti-EGFR mAb label change in a medical record review during two subsequent observation periods in 2012/2013 (97.7% of patients, KRAS only; prior label change) and 2014/2015 (83.2% of patients, full RAS; 16.8%, KRAS only; after label change). The present study included patients who received anti-EGFR mAb treatment in 2018 and reached back at their testing history for up to 5 years to see if they were tested for these important biomarkers at all and when. As recommended by the ESMO guidelines [20], our findings suggest that clinicians request expanded RAS analysis for almost all patients already at diagnosis with increasing numbers of patients additionally tested for BRAF mutations. BRAF testing was recommended by the ESMO as of the 2016 guidelines, which may have influenced the testing patterns. For BRAF, France had the highest testing rate, which may be due to the availability of a completely free nation-wide molecular testing platform in oncology in the French healthcare system since 2006 (https://www.e-cancer.fr). Finally, we noted a small decrease in RAS testing in 2017 and 2018. An explanation could be that primary tumor location started to be taken into account in some centers by excluding patients with right-sided primary tumors from anti-EGFR treatments [41].

Among patients receiving anti-EGFR mAb therapies, almost all were tested for RAS even in 2013 when the label changed to include RAS testing prior to treatment initiation. The quick uptake of biomarker testing in clinical practice is important as more drugs based on biomarkers are now being approved. Of those tested for RAS 3.5% (95% CI: 2.1–5.5) were confirmed with RAS-mutant status. This finding is consistent with past studies by van Krieken et al. [28] and Trojan et al. [40] which found that 2.3 and 5.0% of patients, respectively, had received panitumumab without having a confirmed wild-type KRAS status. BRAF mutation prevalence was 5.4% in 2018 (95% CI: 3.5–8.0). As this is not much lower than the 7.0% (95% CI: 5.6–8.5) mutation prevalence estimated among all mCRC patients, it can be interpreted that BRAF may not be a major factor in the treatment decision making.

A number of observational studies have been carried out providing RAS/BRAF mutation prevalence estimates in the real world. In a survey among European pathology laboratories, Boleij et al. [29] found an overall crude RAS mutation prevalence of 46.0% (95% CI: 44.3–47.7) and 48.5% (95% CI: 46.4–50.6) for laboratories testing for all RAS hotspot codons. A meta-analysis of real-world data conducted by Kafatos et al. [27] found a pooled RAS mutation prevalence of 43.6% (95% CI: 38.8–48.5). For RCTs a pooled RAS mutation prevalence of 55.9% (95% CI: 53.9–57.9) was observed [30] although one study found 43% [28,42]. In the present study the RAS mutation prevalence was estimated as 53.6% (95% CI: 51.3–55.8) in 2018. The biomarker information was captured separately for KRAS and NRAS and assumptions were made for combining this information into RAS. If this had an effect on the RAS mutation prevalence estimates, this would apply throughout and therefore, not affecting any trends ove r time. Kafatos et al. [27] estimated BRAF mutation prevalence across different data sources. The overall pooled BRAF mutation prevalence was estimated as 5.8%, ranging between sources from 2.7 to 14.3%. In the GENIE cancer genomics database a confirmed BRAF mutation prevalence of 8.4% was documented [43]. In the present study, a BRAF mutation prevalence of 7% (95% CI: 5.6–8.5) was found. The performance of laboratory testing and the sensitivity of available biomarker test kits have improved over time, raising questions on whether this has affected the RAS/BRAF mutation prevalence estimates [44]. However, we found no notable trends over time.

Patients with MSI-H CRC generally have a better prognosis than patients with microsatellite stable CRC [45]. MSI testing uptake, however, was slower but reached above 35% in 2017 and >40% in 2018. In these patients, the prevalence of confirmed MSI-H status decreased from 20 to 12.1% over time. It is possible that prior to 2016 more reflex testing was done and only if there was already a suspicion of MSI-H profile. In a systematic review, MSI-H prevalence was estimated at 17% with a wide range of 3–47% [46]. This is in accordance with the present study, where the prevalence of MSI-H was estimated between approximately 10 and 16% overall and may in part have been conducted to test selected patients with a family history of CRC for hereditary CRC, for example, Lynch syndrome.

In order to interpret the study results and their significance for clinical practice, the following considerations need to be taken: the database used for the present study includes information from multiple countries, cancer indications, demographic and clinical characteristics, treatments (type and dosing) and biomarkers. In terms of outcomes, the eCRF captures duration of therapy, time-to-next-treatment, side effects (based on a fixed multiple-choice list) and tumor response. Hospitalizations and deaths/survival are not included. The information is collected quarterly with very small time lag following the end of each quarter (∼6 weeks). The database captures information at different time points of the patient history and specifically at diagnosis, previous and current line of therapy. Hence, it does not cover the full patient treatment history since cancer diagnosis. The advantage with using an eCRF completed by physicians is that variables such as line of therapy or precise su bclassifications of cancer types, for example, small cell versus non-small-cell lung cancer are often complex to define from claims or electronic health record data sources. Due to the design of the present database, such variables are provided by the participating physicians. The disadvantage is that there may be inconsistencies in the way patient information is being reported between physicians.

The selection of the physician panel within the database is crucial as it is assumed that their drug-treated patients will, in turn, reflect the real-world cancer-treated population. Participation in quarterly data collection is limited to settings where physicians are able or willing to answer web questionnaires. Reasons for nonresponse may be work burden, with limited ability to participate in multiple, concurrent studies [47]. This especially applies to countries where physicians are required to seek approval form the hospital management prior to participation, for instance in Germany. Studies, however, show that physicians are interested in endorsing quality improvement and to contribute to clinical knowledge in areas of personal interest to them [48]. Moreover, there is a potential preference to sample physicians from larger sites as participation was restricted to physicians with a target number of treating patients.

In terms of the patient sample, only drug-treated patients are captured within the database. This means that the data cannot be directly used to estimate prevalence and incidence (unless external information is used to extrapolate to population level). It is also important to consider that patients visiting the oncologists more frequently may be overrepresented in the database, but the possibility to report the same patient across multiple quarters is minimized by the definition of a patient cap and by limiting the data collection to a 14-days period in the quarter. The systematic sampling approach (physicians selecting the most recent treated patients) is chosen to minimize the potential for physicians to self-select patient cases.

Conclusion
Biomarker mutation prevalence was stable over time despite documented changes in laboratory practices. During the study period, an increase in biomarker testing rates was observed among patients diagnosed with mCRC. Clinicians appeared to be requesting expanded RAS tests for almost all mCRC patients with increasing numbers of patients additionally tested for BRAF mutations. All anti-EGFR patients had been tested for RAS even in 2013 when the anti-EGFR mAb labels were changed to include RAS testing prior to treatment initiation. This study demonstrates the quick uptake of biomarker testing in clinical practice. These findings are significant as biomarker-based drugs are becoming more common.

Future perspective
In the era of precision medicine, there are many biomarker-driven drugs that are under development, especially within the oncology therapeutic area. As these drugs will be gradually getting introduced, it is important to know that new biomarker testing practices can be quickly adopted by the pathology centers.

Summary points
There is little published work on the testing landscape of biomarkers for metastatic colorectal cancer (mCRC) patients in Europe. This study therefore aimed to estimate the percentage of mCRC patients tested for biomarkers and the mutation prevalence over time.

This was a retrospective analysis using a large oncology database that includes data from ten countries and over 23 cancer indications. The database captures patient information via a standardized electronic case report form entered by the treating physician from patients' health records.

This study included mCRC patients from five European countries, receiving an active anticancer therapy during 2018 and diagnosed at any time between July 2013 and December 2018.

The mCRC population (n = 4455) had the following characteristics: 60.8% of patients were male, median age was 68 years. The stages at diagnosis were mostly stage III (14.2%), and stage IV (77.9%).

RAS testing was conducted in over 90% of mCRC patients from 2014 onwards. BRAF testing increased from 31% of mCRC patients in 2013 to 67% in 2018. Microsatellite instability testing for mCRC patients increased over time from 10% in 2013 to 41% in 2018.

The prevalence of RAS and BRAF mutations in 2018 were 53.6% (95% CI: 51.3–55.8) and 7.0% (95% CI: 5.6–8.5), respectively, with no notable trend over time. Of mCRC patients in general, the rate of microsatellite instability-high tumors ranged between 10 and 16% over time.

Biomarker mutation prevalence was stable over time despite documented changes in laboratory practices.

During the study period, an increase in biomarker testing rates was observed among patients diagnosed with mCRC. Clinicians appeared to be requesting expanded RAS tests for almost all mCRC patients with increasing numbers of patients additionally tested for BRAF mutations.

All anti-EGFR patients had been tested for RAS even in 2013 when the anti-EGFR mAb labels were changed to include RAS testing prior to treatment initiation.

This study demonstrates the quick uptake of biomarker testing in clinical practice. These findings are significant as biomarker-based drugs are becoming more common.

Supplementary data
To view the supplementary data that accompany this paper please visit the journal website at: www.futuremedicine.com/doi/suppl/10.2217/fon-2020-0975

Author contributions
All authors were involved in, and contributed to, the drafting and critical review of this manuscript.

Financial & competing interests disclosure
This research project was funded by Amgen Ltd. G Kafatos, KA Lowe and D Neasham are compensated employees of Amgen, Inc., and stockholders of Amgen, Inc. P Burdon was an employee of Amgen (Europe) GmbH at the time the research was conducted and owns shares in Amgen, Inc.; he is currently an employee of MSD International GmbH. V Banks was a compensated contract worker for Amgen, Inc., during the time of this research. C Anger and F Manuguid are employees of IQVIA Ltd. P Cheung is an independent contractor providing programming services to Amgen Ltd. J Taieb received honoraria for advisory or speaker roles for Amgen, Astra Zeneca, Celgene, HallioDx, Lily, Merck, MSD, Pierre Fabre, Roche, Sanofi, Servier and Sirtex. JH van Krieken declares no conflicts of interest.The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.

M Hemetsberger of hemetsberger medical services, Vienna, Austria, provided medical writing support, funded by Amgen Ltd.

Ethical conduct of research
The Oncology Dynamics™ database (IQVIA Ltd) used in this study is fully anonymized and complies with relevant regulations for protecting patient privacy.

Data sharing statement
The data that support the findings of this study are available from IQVIA but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. Data are however available from the authors upon reasonable request and with permission of IQVIA.

Open access
This work is licensed under the Attribution-NonCommercial-NoDerivatives 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-nd/4.0/

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