Clinical Significance of Change in Body Weight During Treatment of Advanced Colorectal Cancer Patients - A Pilot Study
Conditions: Cancer, Colorectal, Chemotherapy Effect, Weight Loss, Prognosis
Sponsor: Tuen Mun Hospital

Section 13: Proposed Research Project 
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Study Protocol 
 
 
 
 
 
Change in Body Weight During Treatment of Advanced 
Colorectal Cancer 
 
 
PROTOCOL DATE:  
January 1, 2019

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PROPOSED RESEARCH PROJECT 
a) 
Title:   
 
Change in Body Weight During Treatment of Advanced Colorectal Cancer 
 
Abstract 
Objectives: To evaluate whether change in body weight in advanced colorectal cancer patients 
occurring during systemic anti-cancer treatment influences treatment outcomes  
Hypothesis to be tested: Weight loss during treatment is associated with adverse treatment 
outcomes in patients with advanced colorectal cancer, compared to patients without weight loss or 
with weight gain. 
Design: A pilot, prospective, single-centered observational study of patients with advanced 
colorectal cancer having first line systemic anti-cancer treatment. 
Setting: Outpatient Clinical Oncology clinic in Tuen Mun Hospital 
Participants: Patients having histologically proven stage IV colorectal adenocarcinoma, requiring 
systemic anti-cancer treatment, which entail chemotherapy (5-fluouracil, capecitabine, oxaliplatin 
and irinotecan) with or without targeted therapy (cetuximab or bevacizumab) as first line treatment. 
Main outcome measures: Primary outcomes: disease control rate, progression free survival. 
Secondary outcomes: Dose reduction of systemic chemotherapy. 
 
 
b) 
Introduction:  
 
Colorectal cancer (CRC) is a significant and growing health burden in Hong Kong. According to 
data from Hong Kong Cancer Registry, CRC ranked the first in incidence and the second in 
mortality, with around 5,000 new cases diagnosed and more than 2,000 cancer-related mortality in 
2014.1 Around one-fourth of CRC present as metastatic disease; it is also estimated that 50-60% of 
patients diagnosed with CRC eventually develop metastasis during their course of disease.2 Among 
metastatic CRC (mCRC) patients, only few with limited metastases are potential long-term 
survivors after receiving locoregional treatment,3 while the majority of them are incurable and the 
standard treatment is systemic therapy.  
 
Over the past 15 years, the introduction of molecular targeted therapy into mCRC treatment 
armamentarium has dramatically improved the prognosis, with the median overall survival (OS) 
14-16 months in the pre-targeted therapy era compared with around 30 months nowadays.4 
Systemic therapy with combination chemotherapy, Oxaliplatin-based or Irinotecan-based, plus 
targeted therapy, either anti-epidermal growth factor receptor (anti-EGFR) monoclonal antibody 
(mAb) or anti-vascular endothelial growth factor (anti-VEGF) mAb becomes the current standard 
first-line treatment.   
 
Studies have suggested that exposure to a greater number of chemotherapeutic agents is 
associated with better survival.5 Therefore, the current principle of management of mCRC 
emphasizes on maximizing the exposure of various chemotherapeutic and molecular targeted 
agents in a stepwise manner.6, 7 

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However, these treatments have their peculiar side effects. Many chemotherapy treatments are 
dosed based on body weight or body surface area (BSA), with recommended milligrams (mg) per 
BSA (m2) derived from studies testing for dose-limiting toxicities. Nevertheless, many patients still 
experience severe toxicity and subsequently experience reductions in dose or dose delays or 
discontinue treatment prematurely.8, 9 Discontinuation, reductions, and delays in chemotherapy 
might adversely affect prognosis by reducing the exposure to therapeutic agents.8, 10, 11 Great 
variability exists in patients’ tolerance for cancer treatment that is not explained by age and 
comorbidities.12, 13 Body composition, the amount and distribution of fat and lean soft tissue (the 
main compartment of which is skeletal muscle mass), is one factor influencing the 
pharmacokinetics and pharmacodynamics of many chemotherapeutic agents.14 
 
Studies were conducted to evaluate the role of muscle mass and treatment tolerance and outcome 
in CRC patients.8, 11 Computed tomography (CT) based cross-sectional measurement of muscle 
mass was shown to be highly correlated with total body muscle mass.15 Based on this information, 
in a recent study by Feliciano et al.,8 muscle mass was quantified using CT and was used to 
evaluate if body composition at diagnosis was associated with chemotherapy tolerance and overall 
survival in the adjuvant setting. The authors concluded that low muscle mass was associated with 
greater treatment toxicity and poorer chemotherapy adherence.8 The evidence so far suggested 
muscle mass has prognostic value. However, the measurement required specialized software and 
staff training, making this resource draining and time-consuming. This produces practical difficulty 
especially for community oncology centers where budget and manpower is tight. It is likely that the 
measurement will be used mainly as research tool unless computer automation is available widely. 
Furthermore, other observational studies of muscle mass and treatment outcomes have been 
limited by modest sample size, and inadequate adjustment for confounding factors such as age, 
disease stage, race or comorbidities.16, 17 
 
An alternative is to measure the weight change or body mass index (BMI). In patients with CRC 
weight loss is common at disease presentation.9, 10 Weight loss is one of the diagnostic criteria for 
cancer cachexia, and is closely related to poor prognosis in cancer.18 Weight loss is not only a 
problem at diagnosis, but is also encountered during treatment which might impair patients’ 
tolerance to treatment, and treatment outcomes. In one retrospective study, 35% patients with 
mCRC already had weight loss on presentation, and it was shown that these patients received less 
systemic treatment on average, had significantly reduced tumor response, failure free survival, and 
OS.10 In contrast, weight stabilization or reversal of weight loss during treatment was associated 
with longer failure free and OS in that study.10 Similar relationship between serial body weight and 
outcome has been detected in advanced non-small cell lung cancer patients. Patel et al. reported 
weight gain of at least 5% was associated with higher response rate (odds ratio 2.55) and overall 
survival (OS) (HR 0.54), and progression-free survival (PFS) (HR 0.59).19 Hypotheses include 
better nutritional status can improve the host’s immunity and anti-cancer effects, and tumour control 
might inhibit or reverse the processes that promote cachexia and allow weight gain.19, 20  

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Multiple factors might affect body weight during treatment. Cancer-related symptoms can impair 
quality of life and appetite. Cachexia syndrome affects around 50% of colon cancer patients and is 
characterized by cancer-induced catabolism with involuntary weight loss (fat and muscle), patients 
have increased lipolysis and change in skeletal muscle metabolism, including increased energy 
expenditure at rest and protein degradation, and decreased protein synthesis.21 Besides these 
disease factors, treatment related side effects are common causes of weight loss, such as inability 
to ingest or digest food effectively due to nausea, vomiting, and malaise. Based on these factors 
and the hypotheses between tumour control and weight gain, monitoring the serial weight change 
can have practical value. Body weight can be monitored readily in each clinical follow-up session. 
Increasing or maintained weight might indicate that the cancer is not worsening and the patient 
tolerates treatment well. In contrast, weight loss during treatment might alert clinicians to review for 
disease progression and patient’s tolerance to treatment, with corresponding change in strategies 
initiated (including proactive symptom control, early stopping of ineffective treatment, change in 
treatment regimen, or earlier palliative care). Cost in healthcare may be saved by more efficient use 
of resource.22  
 
As for dose reduction, toxicity, especially hematological, is the most common reason. In patients 
with metastatic disease, chemotherapy dose intensity is consistently associated with increased 
rates of complete and partial response, as well as PFS.23  
 
Measurement of weight has the advantages of being cheaper, and easier, and the equipment is 
widely available in the clinic, whereas measurement of muscle mass needs CT or advanced 
techniques such as bio-impedance analysis. To the best of our knowledge, no prospective study 
has reported the impact of serial weight change during treatment for mCRC in terms of treatment 
tolerance and treatment outcomes. Studies have attempted to evaluate the value of measuring 
pre-treatment muscle mass or BMI in predicting patients’ tolerance to systemic anti-cancer 
treatment, but most of them were for adjuvant setting and no serial measurement was made during 
the course of chemotherapy.8, 11 These studies were not specifically conducted for mCRC patients 
undergoing first line palliative systemic treatment. We believe that body weight is strong clinical 
indicator of benefits related to tolerability and tumor response, in addition to tests such as liver and 
renal function tests or serum tumor markers during treatment. Besides, by establishing and 
quantifying the relationship between weight and patient outcomes, the potential value of nutritional 
interventions and what constitutes the cost-effective method to monitor patients during treatment 
can be evaluated in the future. Thus, for the potential benefits to both local and global healthcare 
system, we undertake this pilot study to assess the relationship between serial weight change and 
treatment tolerance (as reflected by dose reduction), tumor response (by disease control rate 
[DCR]) and survival outcomes (by PFS).  
 
Work done by us 
Our team has previously carried out different kinds of oncology research, including in the field of 

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CRC. Tuen Mun Hospital is a tertiary referral oncology center with high clinical volume. Our team 
has extensive clinical experience on CRC and managed more than 1000 new cases of colorectal 
cancer per year; around 60% of them had metastatic disease either at the time of presentation or 
recurrence. More than 150 new patients start first line systemic treatment for mCRC each year.  
 
 
 
c) 
Aims and Hypotheses to be Tested: 
 
Aim:  
To evaluate the association between serial weight change during first line treatment and outcomes 
in patients with mCRC. 
 
Hypothesis to be tested: Weight loss during treatment is not associated with adverse treatment 
outcomes in patients with advanced colorectal cancer, compared to patients without weight loss or 
with weight gain during treatment. 
 
Main outcome measures:  
(1) Primary endpoint: DCR which includes stable disease, partial response and complete response 
as defined in RECIST 1.1; and PFS defined as the time from randomization until first evidence of 
objective tumour progression (as defined in RECIST 1.1) or death from any cause, with censoring 
of patients who are lost to follow-up.  
 
(2) Secondary endpoints: Dose reduction is defined as <70% of relative dose intensity, which 
represents the ratio of dose intensity (dose given per unit body surface area per unit time i.e. 
mg/m2/week) actually administered, to standard dose intensity.8 
 
 
 
d) 
Plan of Investigation: 
 
(i)  Subjects    
Sample size calculation: 
We used power analysis program G*Power to calculate sample size.24 Estimated proportion of 
subjects having significant weight loss is approximately 15%. Risk ratio of dose reduction was 
about 3.0 for patients with significant weight loss, according to a study in adjuvant setting. 
Prior study indicated that the failure rate among controls is 0.2. We will need to recruit 240 
patients to be able to reject the null hypothesis that the primary endpoints (incidence of dose 
reduction) for patient with and without significant weight loss are equal with probability (power) 
0.8. Assuming 10% loss to follow-up, total number of patients to require is 264. The Type I 
error probability associated with this test of this null hypothesis is 0.05. We will use logistic 
regression to evaluate this null hypothesis. 
 
Inclusion criteria for studies 
We recruit male and female patients aged 18 years or older with stage IV, histologically 

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confirmed colorectal adenocarcinoma who will receive systemic treatment, an Eastern 
Cooperative Oncology Group (ECOG) performance status of 0–2, an estimated life 
expectancy of greater than 3 months, and adequate organ function. We exclude patients who 
are pregnant, have human immunodeficiency virus infection and acquired immune deficiency 
syndrome (HIV/AIDS), and past medical history of another cancer. 
 
 
 
 
(ii)  Methods   
This study is prospective observational cohort study, recruitment period is 24 months. We start 
to collect data once patient is recruited and individual data can be available before end of 
recruitment period. Baseline weight (in kilogram), height (in centimeter), and BMI (in kilogram 
per height in meters squared) are measured by medical assistants closest to the start of 
treatment as baseline, and at onset of every treatment cycle. Patients are weighed without 
shoes, in light clothes or hospital gowns, using a Seca digital scale with graduation 0.01 kg. 
Body height is measured to the nearest 0.1 cm with the same digital scale with graduation 0.1 
cm.  
 
Patients’ demographics (age, sex, and ethnicity), and disease characteristics (left versus right 
colon cancer, RAS status) are collected. Other clinical variables considered to be important 
prognostic factors are collected and included in the analysis: TNM cancer stage, histological 
grade, peripheral blood neutrophil-lymphocyte ratio, serum carcinoembryonic antigen (CEA) 
level, ECOG performance status, Charlson comorbidity index.25 
 
 
 
 
 
 
(iii) Study design  
Disease is staged by CT from thorax to pelvis or positron emission tomography-computed 
tomography (PET-CT). Clinical assessment (history taking and physical examination) and 
routine laboratory tests (complete blood counts, liver and renal function tests) are performed 
at baseline and before every treatment cycle according to daily practice. Adverse events are 
assessed using clinical and laboratory data, and graded by using Common Terminology 
Criteria for Adverse Effects, version 4.02. 
 
The treatment doses and administration dates are recorded at chemotherapy infusion tables. 
Any treatment delay and dose reduction is recorded.  
 
Patient is followed up at each treatment cycle. Some patients opt for treatment interruption 
after four to six months of treatment to avoid cumulative toxicity and preserve a good quality of 
life, and are put on close monitoring, treatment can be reinitiated when progression is 
detected. Interval assessments of disease response are made with physical examination 
(every clinic visit), serum CEA level, and three to six monthly CT, PET-CT or X-ray. 
 

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Ethical consideration: Our study adds no additional procedure or risk to the daily management 
of patients. Only medical personnel involving in care and the study can access the data, and 
sufficient protection of patient privacy is ensured. Data are entered and stored in the 
department computer for research purpose only. Data are protected by password. No 
personal identifier will be included in the data processing.  All data will be destroyed 3 years 
after completion of study.  The Clinical and Research Ethics Committee of New Territories 
West Cluster is reviewing the ethical aspects including the waiving of written informed 
consent. 
 
Choices of systemic treatment regimens are available in appendix 1. Dose modifications 
details of the regimens are available in appendix 2.  
 
 
 
 
(iv) Data processing and analysis  
We present descriptive statistics (mean +/- standard deviation, median [range] and 
percentages) of weight change. Weight change is defined as maximum weight change during 
treatment. Besides being a continuous variable, the data on weight are divided into three 
groups: weight gain is >5% body weight increase, weight loss is >5% weight loss, the rest is 
stable weight. 5% is used as a cut-off to account for daily fluctuation in weight and standard 
error in measurement. 
 
Unadjusted logistic regression is used to explore the association between baseline covariates 
and weight change during treatment. 
 
For primary outcomes: 
Time to death (PFS) as a function of weight change is evaluated by Kaplan Meier estimates, 
log-rank tests. Joint modelling approach that can model longitudinal and time-to-event data 
components jointly is used to assess the association between weight change and PFS. 
Fisher’s exact test is used to compare the DCR between weight change groups as univariate 
analysis. Then adjusted logistic regression is used to assess the association between weight 
change and DCR. The models will be adjusted for age, sex, targeted therapies. Other 
variables, such as Charlson’s comorbidity index, and BMI may be selected as covariables. 
Likelihood ratio test will be used to compare models for selecting the final model. 
 
For secondary outcomes: 
We use Chi squared test to explore the association between weight change and dichotomous 
outcomes (dose reduction in treatment). Then separate regression models are used to further 
estimate the association as multivariate analyses. Weight change will be analysed as 
continuous variable, and ordinal variable (coding continuously 0, 1 and 2 for weight loss, 
stable weight and weight gain respectively). Dose reduction is analysed as dichotomous 
variable. The models will be adjusted for age, sex, targeted therapies. Other variables, such 
as Charlson’s comorbidity index, and BMI can be included as covariables. Likelihood ratio test 

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will be used to compare models for selecting the final model. BMI has been found to be 
correlated positively with muscle mass, and is associated with treatment outcomes and side 
effects in different cancers. 
 
Stata is used for all analyses. All significance tests are two-sided. 
 
 
 
 
 
 
 
e) 
Existing Facilities:   
 
The Department of Clinical Oncology at Tuen Mun Hospital will be the primary center for the 
conduct and analytic work in this study. We have an experienced team of researchers of performing 
cancer research. 
 
 
f) 
Justification of Requirements: 
 
 
Travel costs: We have included in our budget travelling costs for one trip to attend international 
conferences ($10,000) in year 3. This is to reflect the need to present results at leading international 
conferences. This travel is mainly intended for international conference attendance. 
 
Publication costs: These will cover the fee to publish the results in high-profile impact Open Access 
journals estimated at $20,000 each. We will promote Open Access publications, according to the 
2003 Berlin Declaration, as an additional mean to disseminate research effectively to large 
audiences. Publications will be uploaded to the open access repository “Dryad” and official site of 
Tuen Mun Hospital. 
 
Other goods: scientific software: i) Stata-SE 15 one-core statistical software license for 1 computer 
(USD$1,695 ~ HKD$13,302). English editing services for research articles estimated at $5,000 
each. We further prepare $3,000 for reference materials. We budget $1,000 each year for 
stationeries and other expenses (e.g. printing and postage) because we expect printing and 
photocopying of a large amount of literature as well as miscellaneous office expenses relate mostly 
to the data collection, analysis, reporting and writing phase of the study. 
 
 
g) 
Purpose and Potential: 
CRC ranks the first in cancer incidence and second in cancer-related mortality in Hong Kong; and 
around 60% of CRC patients develop metastasis during their course of illness. This study will 
quantify the impact of weight change on the tolerability of treatment, as reflected by the need of 
dose reduction, and prognosis. Weight is easy and cheap to measure, which is suitable for 
resource-tight healthcare system such as that in Hong Kong. These are clinically important 
end-points which potentially impact the treatment strategies of stage IV colorectal cancer, including 
the nutritional intervention, and early stop or reducing dose of chemotherapy in case of weight loss. 

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Based on this study, further research can be conducted to evaluate the health economics on 
different treatment strategies which may affect the funding decision of health care payer and the 
future health care policy. 
 
The results of this study will be submitted to international, peer-reviewed journals, and be presented 
in academic conferences. 
 
 
h) 
Key References:   
 
1. 
Hong Kong Cancer Registry. Hong Kong Special Administration Region. 2017 [Available from: 
http://www3.ha.org.hk/cancereg/. 
2. 
Van Cutsem E, Nordlinger B, Adam R, et al. Towards a pan-European consensus on the 
treatment of patients with colorectal liver metastases. Eur J Cancer. 2006;42(14):2212-21. 
3. 
Kanas GP, Taylor A, Primrose JN, et al. Survival after liver resection in metastatic colorectal 
cancer: review and meta-analysis of prognostic factors. Clin Epidemiol. 2012;4:283-301. 
4. 
Venook AP, Niedzwiecki D, Lenz H-J, et al. CALGB/SWOG 80405: Phase III trial of 
irinotecan/5-FU/leucovorin 
(FOLFIRI) 
or 
oxaliplatin/5-FU/leucovorin 
(mFOLFOX6) 
with 
bevacizumab (BV) or cetuximab (CET) for patients (pts) with KRAS wild-type (wt) untreated 
metastatic adenocarcinoma of the colon or rectum (MCRC). Journal of Clinical Oncology. 
2014;32(15_suppl):LBA3-LBA. 
5. 
Grothey A, Sargent D, Goldberg RM, Schmoll HJ. Survival of patients with advanced 
colorectal cancer improves with the availability of fluorouracil-leucovorin, irinotecan, and oxaliplatin 
in the course of treatment. J Clin Oncol. 2004;22(7):1209-14. 
6. 
Network NCC. NCCN Clinical Practice Guidelines in Oncology. Colon cancer. version 1. 2018 
ed. 
7. 
Van Cutsem E, Cervantes A, Nordlinger B, Arnold D. Metastatic colorectal cancer: ESMO 
Clinical Practice Guidelines for diagnosis, treatment and follow-up†. Annals of Oncology. 
2014;25(suppl_3):iii1-iii9. 
8. 
Cespedes Feliciano EM, Lee VS, Prado CM, et al. Muscle mass at the time of diagnosis of 
nonmetastatic colon cancer and early discontinuation of chemotherapy, delays, and dose 
reductions on adjuvant FOLFOX: The C-SCANS study. Cancer. 2017;123(24):4868-77. 
9. 
Dewys WD, Begg C, Lavin PT, et al. Prognostic effect of weight loss prior to chemotherapy in 
cancer patients. Eastern Cooperative Oncology Group. Am J Med. 1980;69(4):491-7. 
10. Andreyev HJ, Norman AR, Oates J, Cunningham D. Why do patients with weight loss have a 
worse outcome when undergoing chemotherapy for gastrointestinal malignancies? Eur J Cancer. 
1998;34(4):503-9. 
11. 
Jung HW, Kim JW, Kim JY, et al. Effect of muscle mass on toxicity and survival in patients with 
colon cancer undergoing adjuvant chemotherapy. Support Care Cancer. 2015;23(3):687-94. 
12. Sargent DJ, Goldberg RM, Jacobson SD, et al. A pooled analysis of adjuvant chemotherapy 
for resected colon cancer in elderly patients. N Engl J Med. 2001;345(15):1091-7. 
13. Gross CP, McAvay GJ, Guo Z, Tinetti ME. The impact of chronic illnesses on the use and 
effectiveness of adjuvant chemotherapy for colon cancer. Cancer. 2007;109(12):2410-9. 

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14. Hopkins JJ, Sawyer MB. A review of body composition and pharmacokinetics in oncology. 
Expert review of clinical pharmacology. 2017;10(9):947-56. 
15. Prado CM, Birdsell LA, Baracos VE. The emerging role of computerized tomography in 
assessing cancer cachexia. Curr Opin Support Palliat Care. 2009;3(4):269-75. 
16. Prado CM. Body composition in chemotherapy: the promising role of CT scans. Curr Opin Clin 
Nutr Metab Care. 2013;16(5):525-33. 
17. Prado CM, Maia YL, Ormsbee M, et al. Assessment of nutritional status in cancer--the 
relationship between body composition and pharmacokinetics. Anticancer Agents Med Chem. 
2013;13(8):1197-203. 
18. Thoresen L, Frykholm G, Lydersen S, et al. Nutritional status, cachexia and survival in 
patients with advanced colorectal carcinoma. Different assessment criteria for nutritional status 
provide unequal results. Clin Nutr. 2013;32(1):65-72. 
19. Patel JD, Pereira JR, Chen J, et al. Relationship between efficacy outcomes and weight gain 
during treatment of advanced, non-squamous, non-small-cell lung cancer patients. Ann Oncol. 
2016;27(8):1612-9. 
20. Topkan E. Weight gain as a surrogate marker of longer survival in advanced non-small cell 
lung cancer patients. Annals of translational medicine. 2016;4(19):381. 
21. Argiles JM, Busquets S, Stemmler B, Lopez-Soriano FJ. Cancer cachexia: understanding the 
molecular basis. Nature reviews Cancer. 2014;14(11):754-62. 
22. Cheung MC, Earle CC, Rangrej J, et al. Impact of aggressive management and palliative care 
on cancer costs in the final month of life. Cancer. 2015;121(18):3307-15. 
23. Lyman GH. Impact of chemotherapy dose intensity on cancer patient outcomes. J Natl Compr 
Canc Netw. 2009;7(1):99-108. 
24. Faul F, Erdfelder E, Buchner A, Lang AG. Statistical power analyses using G*Power 3.1: tests 
for correlation and regression analyses. Behavior research methods. 2009;41(4):1149-60. 
25. Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic 
comorbidity in longitudinal studies: development and validation. J Chronic Dis. 1987;40(5):373-83. 
 
 
 
 
 

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Figure 1. Grouping of mCRC tumors by KRAS exon 2 mutations and extended RAS mutations 
 
Ref. 6, 7 
mCRC 
All-RAS wild type 
 
(40-45%) 
K-RAS exon 2 mutation 
 
(40%) 
K-RAS exon 3,4 mutations / 
N-RAS exon 2,3,4 
mutations (15-20%) 
RAS mutated  
(55-60%) 

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Figure 2. Simplified management algorithm in mCRC. 
 
Abbreviations / remarks: BSC: best supportive care. *Panitumumab is not commonly used in our center, therefore it is not included in the study. 
Notes: [a] In patients who cannot afford targeted therapy, only chemotherapy (cytotoxic doublet) will be available as the first- and second-line treatment and best supportive 
care (BSC) as the third-line treatment. 
[b] In patients who can afford targeted therapy. Either anti-EGFR or anti-VGFR monoclonal antibodies (mAb) are indicated for all-RAS wild type; whereas only anti-VGFR 
mAb is applicable for RAS mutated patients. 
[c] Using either (1) Oxaliplatin based cytotoxic doublets as the first-line and Irinotecan based cytotoxic doublets as the second-line, or (2) vice versa, as cytotoxic doublet 
chemotherapy regimens (i.e., the same paths as in [a] chemotherapy only). 
Ref. 6, 7 
Oxaliplatin based 
cytotoxic doublets 
Irinotecan based cytotoxic 
doublets 
Best supportive care (BSC) 
Irinotecan based cytotoxic 
doublets 
Oxaliplatin based cytotoxic 
doublets 
BSC 
Cetuximab / *Panitumumab 
+ Cytotoxic doublet 
Bevacizumab 
+ Cytotoxic doublet 
(i) BSC; or 
(ii) Regorafenib 
Cetuximab / *Panitumumab 
+ Cytotoxic doublet 
(i) BSC; or 
(ii) Regorafenib 
Bevacizumab 
+ Cytotoxic doublet 
Bevacizumab 
+ Cytotoxic doublet 
Bevacizumab 
+ Cytotoxic doublet 
(i) BSC; or 
(ii) Regorafenib 
[a] Chemotherapy only 
(Cytotoxic doublet) 
[b,c] Targeted 
therapy 
All-RAS wild type 
Any RAS mutation 
mCRC 
1st line 
2nd line 
3rd line 

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