Issa J. Dahabreh, MD; Teruhiko Terasawa, MD, PhD; Peter J. Castaldi, MD, MS; Thomas A. Trikalinos, MD
Grant Support: By the Agency for Healthcare Research and Quality (contract HHSA-290-2007-100551).
Potential Conflicts of Interest: Drs. Dahabreh, Castaldi, and Trikalinos: Grants received (money to institution): Agency for Healthcare Research and Quality. Disclosures can also be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M10-1700.
Requests for Single Reprints: Thomas A. Trikalinos, MD, Center for Clinical Evidence Synthesis, Institute for Clinical Research and Health Policy Studies, Tufts Medical Center, 800 Washington Street (Box 63), Boston, MA, 02111; e-mail, TTrikalinos@tuftsmedicalcenter.org.
Current Author Addresses: Drs. Dahabreh, Castaldi, and Trikalinos: Center for Clinical Evidence Synthesis, Institute for Clinical Research and Health Policy Studies, Tufts Medical Center, 800 Washington Street (Box 63), Boston, MA, 02111
Dr. Terasawa: Fujita Health University Nanakuri Sanatorium, 424-1 Odoricho, Tsu, Mie, 514-1295, Japan.
Author Contributions: Conception and design: I.J. Dahabreh, T. Terasawa, T.A. Trikalinos.
Analysis and interpretation of the data: I.J. Dahabreh, T. Terasawa, T.A. Trikalinos.
Drafting of the article: I.J. Dahabreh, T.A. Trikalinos.
Critical revision of the article for important intellectual content: T. Terasawa, P.J. Castaldi, T.A. Trikalinos.
Final approval of the article: I.J. Dahabreh, T. Terasawa, P.J. Castaldi, T.A. Trikalinos.
Statistical expertise: I.J. Dahabreh, T.A. Trikalinos.
Administrative, technical, or logistic support: T.A. Trikalinos.
Collection and assembly of data: I.J. Dahabreh, T. Terasawa, P.J. Castaldi, T.A. Trikalinos.
Dahabreh I., Terasawa T., Castaldi P., Trikalinos T.; Systematic Review: Anti–Epidermal Growth Factor Receptor Treatment Effect Modification by KRAS Mutations in Advanced Colorectal Cancer. Ann Intern Med. 2011;154:37-49. doi: 10.7326/0003-4819-154-1-201101040-00006
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Published: Ann Intern Med. 2011;154(1):37-49.
KRAS mutations have been extensively investigated as predictive biomarkers for treatment of advanced colorectal cancer with the anti–epidermal growth factor receptor (EGFR) antibodies cetuximab and panitumumab.
To summarize whether KRAS mutation status modifies effects of anti-EGFR–based treatments for patients with advanced colorectal cancer and whether KRAS status predicts clinical outcomes among such patients.
MEDLINE and 2 curated genetics databases (through 24 March 2010) were searched for observational studies. MEDLINE, the Cochrane Central Register of Controlled Trials, the Cochrane Database of Systematic Reviews, and the Database of Abstracts of Reviews of Effects (through 1 September 2010) were searched for randomized, controlled trials. No search was restricted by language.
Three reviewers screened titles and abstracts to identify published studies assessing KRAS mutations as predictors of overall and progression-free survival or treatment failure for patients who received anti-EGFR–based therapy for metastatic colorectal cancer.
Three investigators extracted data on population and study-design characteristics, including quality items, and on outcomes of interest. Random-effects meta-analyses were done on nonoverlapping studies.
In 4 reanalyses of randomized trials of anti-EGFR–based therapy versus best supportive care or cytotoxic chemotherapy, no significant benefit was found for overall or progression-free survival from anti-EGFR–based treatment among KRAS-positive patients (hazard ratio [HR], 1.0). However, evidence favors anti-EGFR therapy among KRAS wild-type patients; the relative HR across KRAS-positive and wild-type patients was 1.30 (95% CI, 0.95 to 1.78) for overall survival and 2.22 (CI, 1.74 to 2.84) for progression-free survival by random-effects meta-analysis. In 13 cohorts of patients who received anti-EGFR antibodies, the summary HR for overall survival was 1.79 (CI, 1.48 to 2.17), with better survival in wild-type patients. The corresponding HR for progression-free survival was 2.11 (CI, 1.74 to 2.55 [16 cohorts]). In random-effects bivariate meta-analysis of 22 studies, the summary sensitivity of KRAS mutations for predicting lack of response was 0.49 (CI, 0.43 to 0.55), and summary specificity was 0.93 (CI, 0.87 to 0.97).
Limited evidence from randomized studies exists. Patient-level data are needed to assess modifiers of the mutation-by-treatment interaction. Publication bias could be a concern.
KRAS mutations are consistently associated with reduced overall and progression-free survival and increased treatment failure rates among patients with advanced colorectal cancer treated with anti-EGFR antibodies.
Agency for Healthcare Research and Quality.
KRAS mutations may mark resistance to anti–epider-mal growth factor receptor (EGFR) antibody treatments for patients with advanced colorectal cancer.
This systematic review of trials and cohort studies found that KRAS mutations were consistently associated with increased rates of treatment failure and reduced survival in adults with advanced colorectal cancer treated with anti-EGFR antibodies.
Patient-level data about pathologic features of tumors and other potential prognostic factors were not available.
Benefits of anti-EGFR monoclonal antibody treatment of colorectal cancer may be limited to patients without KRAS mutations.
Colorectal cancer has an incidence of approximately 150 000 cases per year in the United States and is the third leading cause of cancer-related death in both men and women (1). Up to 80% of patients are diagnosed with advanced disease (2) and have an adverse prognosis, with an estimated median survival of approximately 2 years despite treatment with combination cytotoxic chemotherapy (3). Recent efforts to improve outcomes have focused on the combination of standard chemotherapy with agents targeting biological pathways central to colorectal cancer pathogenesis (4, 5).
Epidermal growth factor receptor (EGFR) has been considered a good candidate for targeted cancer therapy since its discovery (6, 7). Colorectal cancer is a model disease for EGFR-targeted treatments because the EGFR gene is frequently amplified in colorectal cancer and is overexpressed at the RNA and protein levels in most tumors (8, 9). The development of monoclonal antibodies that target EGFR began in the 1980s and has culminated in the clinical testing and approval of 2 monoclonal antibodies: cetuximab and panitumumab (7). These agents, either alone or in combination with chemotherapy, have been shown to improve overall and progression-free survival and have an adverse effect profile that is distinct from that of conventional cytotoxic agents (10, 11). Because not all patients respond to anti-EGFR monoclonal antibodies, and because of the risk for adverse effects associated with their use and their substantial cost, there is particular interest in identifying predictors of treatment benefit or lack thereof. One hypothesis that has been explored in many studies is that genetic aberrations of the genes encoding downstream effectors of EGFR-mediated signaling could be associated with resistance to anti-EGFR antibody therapy. Among all EGFR effectors, KRAS, a member of the rat sarcoma virus (ras) gene family of oncogenes, is a central signaling node that integrates signaling cascades controlling gene transcription, including many EGFR-mediated pathways. KRAS is frequently mutated in epithelial cancer, including colorectal cancer, resulting in activation of the downstream RAS-RAF-MAPK or PI3K pathways, regardless of whether the EGFR is activated or pharmacologically blocked (constitutive activation) (12).
It has been hypothesized that the presence of KRAS mutations could abrogate the effects of anti-EGFR antibodies and preclude any beneficial effects of antibody therapy. Therefore, KRAS mutations may predict resistance (lack of response) to anti-EGFR antibodies, and testing for KRAS mutations can inform treatment choices. In fact, many retrospective studies have suggested that both cetuximab and panitumumab have limited efficacy in patients with activating KRAS mutations (13). More recently, several analyses of randomized, controlled trials (RCTs) comparing anti-EGFR–based therapy with alternative treatments have assessed the ability of KRAS mutations to predict clinical outcomes (14–17). We report a systematic review of the published evidence on the ability of KRAS testing to predict response to treatment with cetuximab or panitumumab in patients with advanced colorectal cancer.
Our 2 main objectives were to summarize whether KRAS mutation status modifies the comparative effect of anti-EGFR–based therapies versus best supportive care or cytotoxic chemotherapy and to summarize whether KRAS status predicts clinically relevant outcomes among patients treated with anti-EGFR antibodies. To address the first objective, a reasonable alternative to de novo RCTs of molecular testing versus no testing is to use reanalyses of already completed RCTs that provide information on the interaction of KRAS mutation status with anti-EGFR treatment. Such “repurposed” RCTs provide higher-level evidence for biomarker validation compared with the retrospective cohorts that are much more common in the biomarker literature (18). The second objective can be informed by noncomparative cohorts of patients treated with anti-EGFR and stratified by KRAS mutation status (including treatment groups of repurposed RCTs).
This systematic review is based on a technology assessment conducted by the Tufts Evidence-Based Practice Center, using standard systematic review methods and following a prespecified protocol. The technology assessment and its supplements are available at www.effectivehealthcare.ahrq.gov/reports/final.cfm.
We searched PubMed, MEDLINE, and the Human Genome Epidemiology Literature Finder (19) through 24 March 2010 to identify studies reporting on at least 1 of the following outcomes: overall mortality; recurrence, relapse, or disease progression; and treatment failure, and the corresponding time-to-event outcomes (for example, overall or progression-free survival) for patients with colorectal cancer receiving treatment with cetuximab or panitumumab, stratified by KRAS mutation status. We set no geographic or language restrictions. We also searched an online database of predictive studies of colorectal cancer (dbCPCO [www.med.mun.ca/cpco]) (20). Additional targeted searches for RCTs were done. We searched MEDLINE, the Cochrane Central Register of Controlled Trials, the Cochrane Database of Systematic Reviews, and the Database of Abstracts of Reviews of Effects through 1 September 2010. To increase yield, we also searched the references of all retrieved manuscripts and relevant review articles. All of the investigators screened the first 300 citations to ensure that screening criteria were well understood and applied uniformly. Thereafter, 3 authors screened nonoverlapping sets of the remaining citations. Potentially eligible studies were retrieved and reviewed in full text.
Eligible studies were published studies that reported on at least 10 patients who had received a diagnosis of metastatic colorectal cancer and received treatment with anti-EGFR antibodies alone or in combination with cytotoxic chemotherapy, used genotyping methods to identify KRAS mutations, and reported the outcomes of interest stratified by mutational status. Because biomarker studies do not typically define time-to-event outcomes with the exception of overall survival, we accepted the definitions used in the primary studies (21). Treatment failure was defined as lack of response by radiologic criteria, as used in each study. We considered all study designs (prospective and retrospective), treatment settings (first line and second line or higher), and treatment strategies (monotherapy and combination with cytotoxic chemotherapy). During full-text review, we only considered studies published in English. Studies that did not identify any KRAS mutation carriers could not contribute to the analyses and were excluded. We also excluded studies conducted in the adjuvant or neoadjuvant setting. Because evidence suggests that combinations of anti-EGFR antibodies with bevacizumab (an antivascular endothelial growth factor antibody) and chemotherapy may be harmful (22), we considered such studies separately.
We took particular care to identify publications with at least partially overlapping populations by comparing authors, centers, recruitment periods, and patient demographic characteristics. We depicted the overlap by using undirected graphs in which each publication is represented by an ellipse, and ellipses of publications with at least partial overlap are linked. This provides a visual representation of potentially overlapping publications: The larger the number of connected publications, the more extensive the overlap in a topic. All publications were included in descriptive analyses, but only nonoverlapping publications were included in meta-analyses (23). This method avoids overcounting in quantitative analyses but may introduce undercounting and is thus a conservative approach.
Three reviewers independently extracted data. Each study was reviewed by 2 reviewers, and discrepancies were resolved by consensus including a third reviewer. From each eligible study, we extracted bibliographic information and information on study design; inclusion criteria; patient and treatment characteristics; details of genetic testing and specific mutations; definitions of outcomes; quality-related items; and numerical data for the outcomes of interest, namely overall survival, progression-free survival, and treatment failure. If a study did not explicitly report these data, but cited other publications instead, we consulted the cited publications.
For time-to-event outcomes (overall and progression-free survival), we extracted hazard ratios (HRs) comparing patients with KRAS mutations with wild-type patients, as well as the corresponding variance (24). For comparative RCTs of anti-EGFR–based therapy versus alternative treatments, we extracted survival statistics for the treatment effect separately for KRAS-positive and wild-type patients. Survival statistics were extracted by using methods described elsewhere (24–26). We also extracted the total number of wild-type and KRAS-positive patients and the number of patients in each of these groups who had treatment failure.
We abstracted information on aspects of the design and conduct of the individual studies that were deemed important for interpreting their results (27). These items include description of patient sampling, administered treatments, design of the parent study (repurposed RCT or prospective or retrospective cohort), whether tissue samples were available for the substantial majority of study participants, whether clinically representative patients were assessed, assay methodology, definitions of clinical end points and methods of measurement, and analysis methods. These items are largely consistent with the REMARK (REcommendations for tumor MARKer prognostic studies) guidelines (28).
We considered overall survival the primary outcome and progression-free survival and treatment failure secondary outcomes. For our first objective (to summarize the interaction effects of anti-EGFR treatment by KRAS mutation status), we calculated relative HRs for overall and progression-free survival of anti-EGFR treatment in KRAS-positive over wild-type (KRAS-negative) patients as the ratio of the respective HRs. Similarly, we calculated the relative odds ratio (OR) for treatment failure as the ratio of the respective ORs for KRAS-positive over wild-type patients. Variances of the log-transformed relative HRs and relative ORs were calculated by using standard methods (29). A relative HR (or OR) of 1.0 indicates that the HR (or OR) of the anti-EGFR–based treatment is the same in both KRAS-positive and KRAS-negative patients. A value greater than 1.0 means that the anti-EGFR effect is more favorable in wild-type patients than in KRAS-positive patients, whereas a value less than 1.0 means the opposite. These analyses of the interaction between anti-EGFR treatment and KRAS mutation status are possible only in (repurposed) RCTs of anti-EGFR–based treatments with cytotoxic chemotherapy or best supporting care.
We examined whether KRAS predicts clinically relevant outcomes among patients treated with anti-EGFR (our second objective) by calculating HRs for overall and progression-free survival in KRAS-positive over wild-type patients. In addition, we quantified the sensitivity and the specificity of KRAS mutations (index test) to predict treatment failure (reference standard) (30–32). For the second objective, we included the anti-EGFR groups of RCTs as independent cohorts.
To summarize evidence on survival outcomes, we did random-effects meta-analysis of HRs, relative HRs, and ORs by using the DerSimonian–Laird model (33). We tested for between-study heterogeneity with the Q statistic (considered significant at the 0.10 level) and quantified its extent with the I2 statistic (34). Systematic differences in the effect sizes of more and less precise (bigger and smaller) studies were tested with the Egger regression test (35) and only for the primary outcome. This and other similar tests (36) are often misleadingly referred to as publication-bias tests(37, 38).
To assess the accuracy of KRAS mutations for predicting treatment failure, we did a bivariate random-effects meta-analysis of sensitivity and specificity by using the exact binomial likelihood (39, 40). We also calculated summary positive and negative likelihood ratios with their corresponding CIs (41). Likelihood ratios quantify the value of mutations for ruling in (positive likelihood ratio) or ruling out (negative likelihood ratio) lack of response to treatment.
We did subgroup analyses to assess whether specific factors may influence the ability of KRAS mutations to predict response to anti-EGFR antibodies. Subgroups were defined by percentage of patients who had not been exposed to previous chemotherapy, use of the anti-EGFR antibodies in combination with chemotherapy or as monotherapy, and the specific antibody used. The effect of these covariates on the log HR of KRAS mutations for overall and progression-free survival was assessed by using univariate random-effects meta-regressions. The respective analyses for treatment failure used bivariate meta-regressions in which covariates were allowed to have distinct effects on sensitivity and specificity (42–44).
Statistical analyses were conducted with Stata SE, version 11.1 (StataCorp, College Station, Texas), and Meta-Analyst, version 3.0 beta (Tufts Medical Center, Boston, Massachusetts) (45). P values for all comparisons were 2-tailed, and statistical significance was defined as a P value less than 0.05 for all tests except those for heterogeneity.
This project is based on a technology assessment done under contract with the Agency for Healthcare Research and Quality. The funding source had no role in the design, conduct, and analysis of the study or in the decision to submit the manuscript for publication.
Appendix Figure 1 summarizes the literature flow. A total of 45 publications were considered eligible for this systematic review. The log of included and excluded studies is in the appendices of the original technology assessment. Table 1 summarizes the clinical settings and therapeutic regimens investigated. The technology assessment contains details about the designs of these studies, the methods and results of mutational testing, and the outcomes assessed.
RCT = randomized, controlled trial.
Cetuximab and panitumumab have been investigated in several phase 2 and phase 3 clinical trials. Many of the centers participating in these trials have genotyped tissue samples from their patient cohorts for KRAS mutations and presented several post hoc analyses, often including additional patients treated outside the clinical trials. Furthermore, pooled analyses of patients included in previous publications have also been published. Appendix Figure 2 suggests that the 45 publications correspond to 24 nonoverlapping studies because there are 24 unconnected components: that is, single ovals or groups of connected ovals. Only the largest publication from each unconnected component of Appendix Figure 2 was included in quantitative analyses.
Each publication is represented by an ellipse, and ellipses of publications with at least partial overlap are linked. The graph indicates that a substantial amount of overlap is present: Of a total of 45 studies, only 24 reported on independent patient populations.
Most patients had received previous treatment with at least 1 chemotherapy regimen; both the number and types of treatment regimens administered varied across studies. Mean or median participant age was 65 years or older in 6 of 40 studies that reported relevant information, and 60 years or older in 31 of 42 studies that reported relevant information.
Table 1 summarizes clinical settings and treatment strategies. Cetuximab was evaluated both as monotherapy and in combination with cytotoxic chemotherapy; panitumumab was evaluated almost exclusively as monotherapy. Anti-EGFR antibody dosing was commonly not reported, particularly in reports of retrospective studies; many of the patients in the 45 publications were enrolled in larger, multicenter prospective clinical trials that used standard drug doses.
In the 45 publications, 12 to 440 patients were analyzed for KRAS status and treated with anti-EGFR antibodies. Median follow-up duration ranged from 9 to 26 months and was commonly not reported. Only 2 studies explicitly stated that sample collection and subgroup analysis by KRAS testing was a prespecified aim of the study. In the remaining 43 studies, outcome assessment was frequently described as prospective, whereas KRAS testing was done only on available archival samples (14). Most studies (39 studies) assessed the ability of KRAS testing to predict outcomes only in patients who received anti-EGFR antibodies. This design essentially assumes that KRAS testing has no predictive ability for colorectal cancer outcomes in patients who did not receive anti-EGFR antibodies.
Six studies reported biomarker analyses based on RCTs in which the control groups received cytotoxic chemotherapy (16, 17), best supportive care (14, 15), or chemotherapy in combination with bevacizumab (47, 61). In the 6 RCTs, 1479 patients treated with anti-EGFR antibodies and 1476 patients treated in the comparator groups were assessed for KRAS mutations. Addition of bevacizumab to cetuximab plus chemotherapy has been shown to result in reduced survival and increased toxicity; therefore, we considered the 2 RCTs in which bevacizumab was used (47, 61) as a separate subgroup.
The methods and results of KRAS mutation analyses are presented in detail in the technology assessment. Most studies only assessed codons 12 and 13 of the KRAS gene, using direct sequencing or allele-specific methods. The commonly used technologies are commercially available, and their analytic validity is appropriate for clinical use.
We used the results of the 4 comparative RCT–based biomarker analyses in which the control groups received cytotoxic chemotherapy or best supportive care to quantify the treatment-by-biomarker interaction. For overall survival, 3 RCTs provided data (14–16), and 1 indicated a statistically significant benefit for using cetuximab (compared with best supportive care) among KRAS wild-type patients (15). Among KRAS-positive patients, anti-EGFR therapy did not seem to offer clinically significant benefits. As shown in Appendix Figure 3, top, the random-effects summary relative HR comparing the treatment effect on overall survival between KRAS-positive and wild-type patients was 1.30 (95% CI, 0.95 to 1.78; P = 0.103), indicating that benefits from anti-EGFR regimens are probably limited to KRAS wild-type patients.
Forest plots on the left present results for the treatment effect (anti-EGFR antibody group vs. comparator), stratified by KRAS mutation status, for each clinical trial. These estimates are indicative of the treatment effect (anti-EGFR treatment group vs. control) within the subgroups of patients defined by KRAS mutation status. Circles represent the point estimate of the treatment effect among KRAS wild-type patients, and squares represent the point estimate of the treatment effect among KRAS-mutated patients. Forest plots on the right summarize the relative treatment effect within each of the 4 studies (KRAS mutant vs. wild-type). These estimates are comparing the treatment effects (anti-EGFR treatment group vs. control) between the groups defined by KRAS mutation status. For each estimate, horizontal lines indicate the 95% CI. Diamonds indicate the summary relative estimates (hazard ratios or odds ratios, as appropriate) by random-effects calculations; the width of the diamond represents the 95% CI of the summary estimates. EGFR = epidermal growth factor receptor. Top. Results for overall survival. Middle. Results for progression-free survival. Bottom. Results for treatment failure.
Four studies provided data on progression-free survival; all 4 suggested that anti-EGFR antibody treatment is beneficial among KRAS wild-type patients but not among KRAS-positive patients (14–17). One study suggested that treatment with anti-EGFR antibody–based therapy was harmful compared with standard cytotoxic chemotherapy (17). The summary relative HR was 2.22 (CI, 1.74 to 2.84; P < 0.001), indicating that benefit from anti-EGFR antibodies is limited to KRAS wild-type patients (Appendix Figure 3, middle).
Regarding response to treatment, all 4 RCTs demonstrated a statistically significant benefit of anti-EGFR antibody treatment compared with alternative therapies among KRAS wild-type patients but not KRAS-positive patients. There seemed to be no effect among patients with mutated KRAS. The summary relative OR for treatment response was 3.27 (CI, 1.70 to 6.31; P < 0.001), indicating that anti-EGFR antibody treatment benefits on response to treatment are limited to KRAS wild-type patients, although substantial uncertainty was found around the relative OR estimates of the studies conducted in the second-line setting (Appendix Figure 3, bottom) (14, 15).
The results from the comparative RCT–based biomarker analyses, in which the control groups received cytotoxic chemotherapy in combination with bevacizumab, are presented in Appendix Figure 4. In general, the combination of cetuximab, bevacizumab, and chemotherapy resulted in worse outcomes compared with chemotherapy plus bevacizumab alone, regardless of mutational status and without significant treatment-by-biomarker interaction.
Forest plots on the left present results for the treatment effect (anti-EGFR antibody group vs. comparator), stratified by KRAS mutation status, for each clinical trial. Circles represent the point estimate of the treatment effect among KRAS wild-type patients, and squares represent the point estimate of the treatment effect among KRAS-mutated patients. Forest plots on the right summarize the relative treatment effect within each of the 4 studies (KRAS mutant vs. wild-type). Reference 46 is represented by 2 strata because survival information was presented separately on the basis of cytotoxic chemotherapy regimens used. For each estimate, horizontal lines indicate the 95% CI. Diamonds indicate the summary relative estimates (hazard ratios or odds ratios, as appropriate) by random-effects calculations; the width of the diamond represents the 95% CI of the summary estimates. EGFR = epidermal growth factor receptor. Top. Results for overall survival. Middle. Results for progression-free survival. Bottom. Results for treatment failure.
The technology assessment details the findings from the eligible studies with the clinical outcomes of mortality, progression, and response to treatment. For these analyses, we did not consider the anti-EGFR antibody groups of bevacizumab plus chemotherapy trials.
In all 20 publications that reported relevant information, median overall survival in KRAS-positive patients was shorter compared with wild-type patients and ranged from 4.4 to 17.5 months for patients with KRAS mutations and from 6.6 to 24.9 for wild-type patients. Figure 1 shows the meta-analysis of the 13 nonoverlapping studies (651 mutations in 1695 patients) with data on overall survival. The summary HR was 1.79 (CI, 1.48 to 2.17; P < 0.001), indicating that KRAS mutations are associated with shorter survival, and there was evidence of between-study heterogeneity (P = 0.007; I2 = 56%). Some evidence suggested that smaller studies were systematically different from larger studies (P = 0.04).
Each study is shown by the point estimate of the HR (size of square is proportional to the weight of each study) and 95% CI; the summary HR and its 95% CI by random-effects calculations are depicted by the diamond. Values greater than 1 indicate that patients with the KRAS mutation have reduced survival compared with wild-type patients. HR = hazard ratio.
In all 30 of 42 publications that reported disease progression, median progression-free survival or time-to-progression was shorter among patients with KRAS-positive tumors than with wild-type patients. Median progression-free survival and time to progression ranged from 1.3 to 7.6 months for patients with KRAS mutations and from 1.4 to 12.3 months for wild-type patients. In total, 16 studies (741 mutations in 1945 patients) were considered nonoverlapping and provided data for the meta-analysis of progression-free survival. The summary HR was 2.11 (CI, 1.74 to 2.55; P < 0.001), indicating a detrimental effect of KRAS mutations on progression-free survival; there was evidence for substantial between-study heterogeneity (P = 0.003; I2 = 57%).
Overall, treatment failure rates were higher in patients with KRAS mutations than in wild-type patients. Particularly in studies of patients who had received previous chemotherapy, the response rates in the presence of KRAS mutations were typically very low and often 0. Figure 2 shows the summary sensitivity and specificity of KRAS mutations for predicting treatment failure from a bivariate meta-analysis of 22 studies with nonoverlapping populations (841 mutations in 2242 patients). The summary specificity was 0.49 (CI, 0.43 to 0.55), and the summary sensitivity was 0.93 (CI, 0.87 to 0.97), corresponding to a summary positive likelihood ratio of 7.35 (CI, 3.72 to 14.50) and a summary negative likelihood ratio of 0.55 (CI, 0.49 to 0.61) for predicting treatment failure.
Study results are plotted in the receiver-operating characteristic curve space. Each study is represented by a circle, whose size is proportional to the study size. EGFR = epidermal growth factor receptor.
For both overall and progression-free survival, none of the assessed covariates affected the predictive value of KRAS mutations beyond that expected by chance (Table 2). In contrast, for treatment failure, KRAS testing had high summary specificity (0.90) in all study subgroups, except those of studies conducted in the first-line setting. The specificity of KRAS mutations in the first-line setting was statistically significantly different from that in the second-line setting (P < 0.001 for interaction). Sensitivity was low (0.47 to 0.57) in all evaluated subgroups (Table 3).
Our report is an overview of KRAS mutations as a biomarker of resistance to anti-EGFR antibodies for patients with advanced colorectal cancer. We found that KRAS mutations are strong predictors of reduced overall survival and progression-free survival and increased rates of treatment failure. Quantitative evidence that the benefits of anti-EGFR targeted treatment in colorectal cancer are largely limited to patients with no KRAS mutations is provided; this treatment-by-biomarker interaction was particularly evident for the outcomes of progression-free survival and response to treatment, but congruent results were obtained for overall survival. Hence, our results provide support for a recent Provisional Clinical Opinion by the American Society of Clinical Oncology and the labeling changes implemented by the U.S. Food and Drug Administration restricting the use of anti-EGFR monoclonal antibodies to patients with colorectal cancer with tumors that test negative for KRAS mutations (87).
We evaluated activating KRAS mutations for their ability to predict differential response to EGFR-based treatment: that is, as a biomarker that informs a pharmacogenetic interaction. Predictive or pharmacogenetic effects of biomarkers (ability to identify treatment-effect modification) should be distinguished from prognostic effects (ability to predict outcomes regardless of treatment) (88). Ideally, to assess predictive effect of KRAS mutations, patients who did and did not receive EGFR-based therapy need to be tested for treatment-by-KRAS mutation interactions (18), as was done in 6 repurposed RCTs that we identified. Most of the available studies analyzed only patients who received EGFR-based treatments and, by definition, do not provide information on treatment-by-KRAS mutation interactions. We argue that they can still be considered supportive of a predictive (pharmacogenetic) effect of KRAS mutations because mutations seem to have little or no ability to predict outcomes in patients receiving standard chemotherapy (89, 90). Therefore, the relationship of KRAS mutations on clinical outcomes in the noncomparative studies essentially can be viewed as a predictive or pharmacogenetic effect.
Two of 6 repurposed RCTs used a combination of cetuximab, bevacizumab, and chemotherapy in the experimental group, which has been shown to result in reduced efficacy and increased toxicity compared with bevacizumab plus chemotherapy combinations (22). No statistically significant pharmacogenetic (treatment-by-KRAS status) interaction occurred in these 2 trials.
The predictive ability of KRAS mutations seems to be similar in cetuximab and panitumumab therapy, although the bulk of available evidence for this subgroup comparison was related to studies assessing panitumumab as monotherapy and, in all cases, in patients pretreated with cytotoxic chemotherapy. Panitumumab is approved for use as a single agent for patients with disease progression who are receiving or following fluoropyrimidine, oxaliplatin, and irinotecan chemotherapy regimens (91).
The predictive effect of KRAS mutations may be modified by previous exposure to chemotherapeutic agents (92). In our analysis, the ability of KRAS mutations to predict treatment failure seemed to be lower in studies conducted in the first-line setting compared with studies in patients who have received cytotoxic chemotherapy. A plausible explanation is that in the salvage setting, many patients are already resistant to cytotoxic chemotherapy and most of their benefit comes from the anti-EGFR component of the treatment regimens. In patients who have been previously treated (salvage setting), the modifying effect of KRAS mutations on the anti-EGFR therapy is not diluted by the effect of cytotoxic chemotherapy and is more readily observable. These observations need to be viewed with caution, given that they did not seem to apply to survival outcomes and require confirmation by further research focused in the first-line setting. Ideally, this could be studied in future RCTs of anti-EGFR agents by prespecifying analyses by KRAS status. Another option is to repurpose already completed RCTs, in which the drugs of interest are tested against a suitable comparator, by genotyping tissue samples from enrollees (18, 93). In the latter case, genetic analyses in archival tissue from RCT enrollees would be done and associated with the prospectively recorded clinical outcomes (18). Properly stored tissue samples can be genotyped with negligible error long past the collection date. Provided that samples are collected from all RCT participants (even if a proportion is missing completely at random), retrospective associations of somatic mutations with treatment outcomes should be unconfounded. However, statistical corrections for repeated testing would still need to be done to control for spurious findings (type I error) (18).
Several limitations need be considered when interpreting our results. First, our criteria to identify overlapping publications are conservative, in that we may have excluded publications that do not have extensive overlap with the included ones. This approach ensures that overcounting of patients did not occur. Randomized evidence is limited, and few studies seem to have been specifically designed to address the questions that were considered in this review. Furthermore, we had no access to primary data, such as sex, age, or pathologic features of the tumor, that may also have predictive importance and may be modifiers of the observed relationship of KRAS mutations and treatment effect. Finally, we found some evidence that smaller observational studies provided more extreme estimates of the HR for overall survival compared with larger studies. Although it is customary to ascribe this pattern to publication bias, many reasons, including unexplained between-study heterogeneity and chance, can result in similar patterns (37, 38). Nevertheless, as in all systematic reviews based on the published literature, publication bias may exist. However, it is unlikely that the consistent and relatively large pharmacogenetic interaction is a result of publication bias alone.
In conclusion, we provide evidence that KRAS mutations are predictive of survival, disease progression, and treatment failure in patients with advanced colorectal cancer treated with anti-EGFR antibodies. We show that the benefits of anti-EGFR antibody therapy are largely limited to KRAS wild-type patients, particularly regarding progression-free survival and response to treatment. Evidence indicates that the predictive effect is stronger among patients who have received previous cytotoxic chemotherapy, but more evidence is needed to establish this observation. Further research is warranted to identify subgroups of the disease in which the predictive effect may be stronger and to integrate several molecular biomarkers, such as BRAF, PTEN, or PIK3CA aberrations (13), along with KRAS mutations in predictive instruments, to further improve predictive accuracy.
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Ezzeldin M. Ibrahim
International Medical Center
October 24, 2011
Systematic Review: Anti-Epidermal Growth Factor Receptor Treatment Effect Modification by KRAS Mutations in Advanced Colorectal Cancer
We read with interest the systematic review by Dahabreh et al that was recently published in the Annals (1). The authors investigated whether KRAS mutation status modifies effects of anti-EGFR-based treatments for patients with advanced colorectal cancer (CRC) and whether KRAS status predicts clinical outcomes. Unfortunately, the authors did not refer to our meta-analysis - the largest published so far - that addressed similar questions (2). The article was published online on March 2010, perhaps after Dahabreh et al have locked their literature search database. In our meta-analysis there were four randomized studies (RS) that compared cetuximab-based therapy (CBT) versus non-cetuximab control (NCC) in 2,292 patients, and six non-randomized studies (NRS) included patients received cetuximab after failure of prior chemotherapy (411 patients). Patients in RS with wild K-ras tumor gained more benefit from CBT vs. NCC. For objective response rate (ORR), the odds ratio (OR) was 2.10 (p=0.0002), while the hazard ratio (HR) for progression-free survival (PFS) was 0.64 (p=0.04). On the other hand, CBT was associated with an adverse effect on RR and no effect on PFS in mutated K-ras. In all patients who received CBT in RS and NRS, those with wild vs. mutated K-ras demonstrated higher RR (odds ratio 3.72; p<0.0001). Compared with NCC in three RS, CBT showed significant overall survival (OS) advantage in patients with wild K-ras (HR=0.68; p=0.01). Subsequent to that meta-analysis, we performed a more recent meta-analysis intended to examine the clinical outcome of panitumumab for metastatic CRC (3). In the later meta-analysis, we identified four RS that included 1,010 and 1,105 patients who received panitumumab-based therapy (PBT) PBT and the control intervention, respectively. Used in subsequent-line setting and among those with wild k-ras, PBT was associated with 42% improvement in PFS (HR = 0.58; P = 0.02), a non-significant overall survival (OS) benefit (HR = 0.90; P = 0.18), and a significant increase in ORR (OR = 0.67; P = 0.04). PBT showed no benefit in the first-line setting. Restricted analysis to two studies (first- and second-line setting), where the treatment effect of PBT was prospectively analyzed according to tumor KRAS status, showed significant PFS (HR = 0.77), OS (HR = 0.84), and ORR (OR = 2.06) advantage. Our two published meta-analyses support and certainly complement the conclusions derived by Dahabreh et al (1).
1. Dahabreh IJ, Terasawa T, Castaldi PJ, Trikalinos TA. Systematic review: Anti-epidermal growth factor receptor treatment effect modification by KRAS mutations in advanced colorectal cancer. Ann Intern Med. 2011;154(1):37-49.
2. Ibrahim EM, Zekri JM, Bin Sadiq BM. Cetuximab-based therapy for metastatic colorectal cancer: a meta-analysis of the effect of K-ras mutations. Int J Colorectal Dis. 2010;25(6):713-21.
3. Ibrahim EM, Abouelkhair KM. Clinical outcome of panitumumab for metastatic colorectal cancer with wild-type KRAS status: a meta-analysis of randomized clinical trials. Med Oncol. 2011. Jan 9. [Epub ahead of print].
Gastroenterology/Hepatology, Hematology/Oncology, Gastrointestinal Cancer, Colorectal Cancer.
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