Abstract
Initial studies have investigated the association between inflammation and colorectal cancer (CRC) using C-reactive protein (CRP) as a pro-inflammatory biomarker and have noted inconsistent results among women. We here report findings from a large prospective study with repeat measurements of CRP, as well as serum-amyloid A (SAA), an additional biomarker of inflammation, and risk of CRC. In the Women’s Health Initiative Observational Study, we examined associations of CRP and SAA with CRC using repeat assessments (baseline and 3-year follow-up) among 953 matched case-control pairs for CRP and 966 pairs for SAA. Multivariate-adjusted conditional-logistic regression models were used with two-sided tests of significance. Receiver operating characteristic (ROC) curve analysis assessed their utility as early detection markers. Colon cancer risk (odds ratio, OR, and 95% confidence intervals) among women in the highest quintiles of CRP or SAA compared to those in the lowest quintiles was ORcolon/CRP=1.37 (0.95-1.97, p-trend=0.04) and ORcolon/SAA=1.26 (0.88-1.80, p-trend=0.10), respectively. Women with elevated concentrations of both CRP and SAA had an increased risk of ORcolon=1.50 (1.12-2.00, p-value=0.006) compared to those with low concentrations. No positive associations were observed with rectal cancer and weaker associations for CRC overall. Temporal changes in biomarkers over 3-years did not predict risk. The area under the 6-month ROC curve for CRP+SAA was 0.62 (95%CI 0.55-0.68). Elevated inflammatory biomarkers are associated with an increased risk of CRC, mainly colon cancer. Nevertheless, changes in the biomarkers over time do not suggest that they merit consideration as early-detection markers for CRC.
Keywords: C-reactive protein (CRP), serum amyloid A (SAA), colorectal cancer, women, early detection
Introduction
Inflammation plays a role in colorectal carcinogenesis based on experimental, clinical and epidemiological data 1-4. Non-steroidal anti-inflammatory drug (NSAID) use is associated with reduced risk of colorectal adenomas and cancer in both observational and randomized controlled studies 1, 5-8.
C-reactive protein (CRP) and serum amyloid A (SAA) are non-specific hepatic inflammatory markers produced in response to infection, trauma and other inflammatory states 9, 10. Acutely, their serum concentrations increase and slowly return to normal over some days. However, a persistent elevation occurs with chronic inflammation 9, 10. Although, there is a positive correlation (r =0.52) between CRP and SAA concentrations 11, 12, studies have shown that SAA may be a more sensitive marker of inflammation in certain disease states 12. Also, SAA has been more strongly associated with breast-cancer survival than CRP 13. Prospective epidemiological studies that have investigated the association of serum CRP with colorectal cancer (CRC) risk have reported disparate results, particularly among women 14-27. There have been no prospective studies on the association between SAA and CRC risk.
Apart from the limited sample size of some previous studies, CRP measurements were performed only once. Thus, these studies could not ascertain how long-term CRP, and changes in CRP, concentrations before cancer diagnosis may be related to CRC risk. Furthermore, no previous studies have investigated the clinical utility of CRP and SAA as early-detection markers for CRC. Current screening modalities such as fecal occult blood testing (FOBT) have limited sensitivity and specificity 28, while others (colonoscopy and sigmoidoscopy) are costly, associated with not insignificant complications and are underused 28, 29. Hence there is a need for blood-based biomarkers of early detection for use in conjunction with other screening modalities.
To extend knowledge on the role of inflammation in CRC development, and to assess the utility of CRP and SAA as putative biomarkers of early detection, we investigated the associations of CRP and SAA with CRC risk using serum samples collected at baseline and year-3 follow-up in a large case-control study nested within the Women’s Health Initiative Observational Study (WHI-OS).
Methods
Study population
The WHI-OS is a prospective cohort study that enrolled 93 676 women between 1993 and 1998 at 40 U.S. institutions, with detailed protocols and extensive quality control mechanisms 30, 31. Women were eligible for the WHI-OS if they were postmenopausal, aged 50 to79 years and unlikely to relocate or die within three years. Details on characteristics of the WHI-OS cohort and study design are described elsewhere 30, 31. CRC cases were annually identified and adjudicated through reviews of the medical records and pathology reports as of April 24, 2008 32. Cancer cases were centrally reviewed, identified and classified using SEER program guidelines 32. Clinical outcomes were reported annually by self-administered medical history update questionnaires and in a clinic follow-up visit at year-3. Here, we further excluded women with history of CRC (n=959), CRC in-situ (n=46), CRC from death report only (n=52), body mass index (BMI) <=15 or >=50 kg/m2 (n=502). Controls, who were randomly selected using risk-set sampling, were women in the WHI-OS who were alive and cancer-free at the time of case diagnosis. Controls were matched based on age (±3 years), race/ethnicity, clinical center, and date of blood-draw (±6 months for baseline and year-3 blood draws), and baseline hysterectomy status. The present study included 988 incident cases of CRC and 988 matched controls. Matched pairs for women where the CRP (n=35) or SAA (n=22) values were individually missing were excluded from the analysis. Thus, 953 matched pairs were available for the CRP analysis and 966 matched pairs for the SAA analysis.
Written informed consent was obtained and the study was IRB approved at the WHI Clinical Coordinating Center at the Fred Hutchinson Cancer Research Center as well as at 40 clinical centers and the German Cancer Research Center.
Data Collection
Self-reported data on demographic and health-related characteristics were collected at baseline 30. Baseline height and weight were measured and body mass index (BMI) was computed (weight[kg]/height[m2]). Blood was drawn at baseline and year-3 follow-up using standardized protocols.
Assays
CRP and SAA were quantified at baseline and year-3 follow-up at the Clinical Immunology Laboratory (University of Washington) by latex-enhanced nephelometry, (BNII, Siemens) including both internal laboratory controls and blinded WHI duplicates. Coefficients of variation (CVs) for WHI blind duplicate samples were 4.9% for SAA and 4.1% for CRP.
Statistical analysis
We compared baseline characteristics of cases and controls using t-tests (for continuous variables) and Chi-square tests (for categorical variables). Odds ratios and 95% CIs (OR, 95% CI) were estimated using conditional logistic regression models. Baseline CRP and SAA were used in the primary analyses. All models were adjusted for age (50-54, 55-59, 60-64, 65-69, 70-74, 75-79 years). Multivariate models included age and a set of baseline variables chosen a priori for adjustment of potential confounding, including baseline BMI, race/ethnicity (White, Black, other race/ethnicity), past medical history of colonoscopy (yes/no), physical activity (0-3, 3≤11.75, >11.75 MET-hr/wk), postmenopausal hormone use (HT) (never, past, current), pack-years of smoking (continuous variable; estimated as the product of the number of smoking years and the number of cigarettes smoked daily until the time of baseline examination) and NSAID use. Only age, BMI, HT use, previous history of colonoscopy and pack-years of smoking, were included in the final model because they were the only covariates that affected the ORs by >10%.
Quintile cut-off points for both biomarkers were determined based on the distribution among controls. Tests of linear trend across increasing categories were conducted by modeling the median values of each category as a single continuous variable and assessing significance using Wald test. Furthermore, we investigated the impact of long-term biomarker concentrations on CRC risk by categorizing the study participants into four groups using a median split at baseline and year-3 follow-up as cut-off.
We investigated CRC risk using a combination of the two inflammatory biomarkers by stratifying the women into four groups based on their combined CRP and SAA concentrations. For each biomarker, the women were dichotomized into high and low based on median levels among controls. The four groups were (i) women with low CRP/SAA, (ii) women with high CRP/low SAA, (iii) women with low CRP/high SAA, (iv) women with high CRP/SAA.
We explored the impact of changes in biomarker concentrations over the 3-year follow-up period on CRC risk by calculating the percentage changes in each biomarker and relating to risk. Quintile cut-off points were determined based on percentage changes among controls. To assess the clinical utility of CRP and SAA as early detection markers, we considered the receiver operating characteristic (ROC) curve analysis and used area under the ROC curve (AUC) as a global summary of the discriminatory capacity of the markers. Time-dependent ROC curves evaluated whether the biomarkers can signal CRC cases 6-month or 1-year prior to diagnosis from normal controls. For the ROC curves, we took biomarker measures (baseline or year-3) obtained within 6-months or 1-year of diagnosis from cases, and contrasted them to those from controls. Seventy-eight cases were eligible for the 6-month ROC curve analysis and 161 for the 1-year analysis. The ROC curve was considered first for individual markers. Further, we calculated the ROC curve for CRP and SAA combined, with combinatory algorithm determined by adding up scores based on quintiles of CRP and SAA for each participant. For example, a participant who was in the lowest quintile for both markers would score as 1+1=2, whereas an individual in the highest quintiles would score as 5+5=10.
Secondary analyses were carried out according to tumor site, stage and excluding cases with high CRP concentrations >10mg/L (n=119), because such high values may indicate acute infection. We stratified the analyses by postmenopausal HT and BMI. Lastly, we conducted the analyses excluding cases diagnosed within 3 years of blood draw and the results were identical (data not shown). Statistical significance was defined as p<0.05. All statistical tests were two-sided. Analyses were conducted using SAS (V9.2, SAS Institute, Inc., Cary, NC, USA).
Results
Mean age was 67±7 years for cases and controls (Table 1). Case women had significantly higher BMI, smoked more cigarettes, were less physically active compared to controls. Cases had higher CRP concentrations than controls at baseline (median; 3.0 mg/L vs 2.5 mg/L, p-value=0.007) and at year-3 follow-up (median; 3.0 mg/L vs 2.5 mg/L, p-value=0.047). For SAA, there were no significant differences in serum concentrations between cases and controls at baseline (median; 5.6 mg/L vs 5.3 mg/L, p-value=0.08) and year-3 follow-up (median; 5.6 mg/L vs 5.6 mg/L, p-value=0.57). There was a significant increase in mean CRP concentration from baseline to year-3 follow-up among cases (0.58 mg/L, p-value=0.046) but not among controls (Supplementary Table 1, online publication only). CRP and SAA were moderately correlated at baseline and year-3 follow-up; r=0.53 and 0.57 (p-values<0.0001), respectively. Likewise, there were strong correlations between baseline and year-3 biomarker concentrations (r=0.69, p≤0.0001 for CRP and r=0.71, p≤0.0001 for SAA) (data not shown).
Table 1.
Baseline characteristics of colorectal cancer cases and controls in the Women’s Health Initiative Observational Study (WHI-OS)
| Cases | Controls | P-value | |||
|---|---|---|---|---|---|
|
| |||||
| Characteristics | n | Mean (SD) or % |
n | Mean (SD) or % |
|
| Age (years) | 988 | 67 (7) | 988 | 67 (7) | 0.50 |
| 50 – 54 | 58 | 5.9 | 55 | 5.6 | 0.96 |
| 55 – 59 | 105 | 10.6 | 104 | 10.5 | |
| 60 – 64 | 190 | 19.2 | 192 | 19.4 | |
| 65 – 69 | 260 | 26.3 | 245 | 24.8 | |
| 70 – 74 | 230 | 23.3 | 246 | 24.9 | |
| 75 – 79 | 145 | 14.7 | 146 | 14.8 | |
| Body-Mass Index (kg/m2)** | 976 | 28.1 (6.0) | 978 | 27.1 (5.9) | 0.0001 |
| < 25.0 | 342 | 35.1 | 394 | 40.3 | 0.002 |
| 25.0 – 29.9 | 331 | 33.9 | 355 | 36.3 | |
| 30 – 34.9 | 187 | 19.2 | 143 | 14.6 | |
| ≥ 35.0 | 116 | 11.8 | 86 | 8.8 | |
| Ethnicity (several categories) | 988 | 100 | 988 | 100 | 1.0 |
| White | 842 | 85.2 | 842 | 85.2 | |
| Black or African-American | 88 | 8.9 | 88 | 8.9 | |
| Others*** | 58 | 5.9 | 58 | 5.9 | |
| Family Income ($) | 950 | 100 | 940 | 100 | 0.08 |
| Less than 34,999 | 457 | 48.1 | 421 | 44.8 | |
| 35,000 to 74,999 | 343 | 36.1 | 329 | 35.0 | |
| 75,000 or more | 125 | 13.1 | 162 | 17.2 | |
| Don’t know | 25 | 2.6 | 28 | 3.0 | |
| Education (high school or less) | 195 | 19.9 | 223 | 22.8 | 0.12 |
| Residence Location (U.S. region) | 988 | 100 | 988 | 100 | 0.42 |
| Northeast | 255 | 25.8 | 227 | 22.3 | |
| South | 223 | 22.6 | 240 | 24.3 | |
| Midwest | 228 | 23.1 | 222 | 22.5 | |
| West | 282 | 28.5 | 299 | 30.3 | |
| Pack-years smoking | 951 | 13.0 (21.7) | 951 | 8.9 (17.0) | <0.0001 |
| NSAID use (ever) | 180 | 18.2 | 176 | 17.8 | 0.81 |
| Minutes of moderate or strenuous activity per week |
975 | 95.9 (135.9) | 979 | 109.1 (143.4) | 0.04 |
| Family History of Colorectal Cancer (yes) | 192 | 21 | 163 | 18 | 0.1 |
| History of Colonoscopy or Sigmoidoscopy (yes) |
508 | 52 | 589 | 60 | 0.0003 |
| History of Colon Polyp Removal (yes) | 123 | 25 | 105 | 18 | 0.008 |
| Tumor location (proximal, distal, rectal)* | 990 | 100 | - | - | - |
| Proximal | 577 | 58.3 | - | - | - |
| Distal | 211 | 21.3 | - | - | - |
| Rectal | 184 | 18.6 | - | - | - |
| Overlapping/Unknown | 18 | 1.8 | - | - | - |
| Tumor grade* | 990 | 100 | |||
| Well differentiated | 75 | 7.6 | - | - | - |
| Moderately differentiated | 616 | 62.2 | - | - | - |
| Poorly differentiated | 202 | 20.4 | - | - | - |
| Anaplastic | 12 | 1.2 | - | - | - |
| Unknown/not done | 85 | 8.6 | - | - | - |
| Tumor stage (SEER staging)* | 989 | 100 | - | - | - |
| Localized | 431 | 43.6 | |||
| Regional | 409 | 41.3 | - | - | - |
| Distant | 127 | 12.8 | - | - | - |
| Unknown/not done | 22 | 2.2 | - | - | - |
| CRP, Median (IQR) | |||||
| Baseline (mg/L) | 968 | 3.0 (4.7) | 971 | 2.5 (4.2) | 0.007 |
| Year 3 (mg/L) | 782 | 3.0 (4.8) | 885 | 2.5 (4.2) | 0.047 |
| Difference (mg/L) | 766 | 0.05 (2.3) | 875 | 0.0 (2.1) | 0.11 |
| SAA, Median (IQR) | |||||
| Baseline (IQR) | 972 | 5.6 (6.2) | 979 | 5.3 (5.9) | 0.08 |
| Year 3 (mg/L) | 787 | 5.6 (6.2) | 891 | 5.6 (6.2) | 0.57 |
| Difference (mg/L) | 773 | 0.1 (3.1) | 885 | 0.2 (2.8) | 0.50 |
Measured at baseline.
Others - Hispanic, Asian or Pacific Islander, American Indian or Alaskan Native, missing
Two individuals are listed as having both colon cancer and colorectal cancer, so information on both tumors is reported here.
Baseline CRP concentrations were positively associated with CRC risk (Table 2). The ORs of CRC among women in the highest quintiles of CRP compared to those in the lowest quintiles were 1.29 (95%CI 0.97-1.70, p-trend=0.01) and 1.30 (0.93-1.82, p-trend=0.02) in the age-and multivariate-adjusted analyses, respectively. Multivariate-adjusted ORs comparing highest to lowest quintiles of serum CRP for colon and rectal cancers were 1.37 (0.95-1.97, p-trend=0.04) and 0.88 (0.36-2.15, p-trend=0.59), respectively.
Table 2.
Odds ratios (ORs) and 95% confidence intervals of colorectal cancer by quintile of baseline CRP concentrations
| Quintiles of baseline CRP (mg/L)1 | |||||||
|---|---|---|---|---|---|---|---|
| Cases/controls | 1 ≤ 0.9 |
2 > 0.9 – 1.9 |
3 > 1.9 – 3.2 |
4 > 3.2 – 5.9 |
5 > 5.9 |
P trend2 | |
| All participants | 377 | 357 | 363 | 397 | 445 | ||
| Age-adjusted OR (95% CI) | 953/9533 | 1.0 (ref) | 0.90 (0.67,1.21) | 1.03 (0.76,1.38) | 1.15 (0.86,1.53) | 1.29 (0.97,1.70) | 0.01 |
| Multivariate OR (95% CI)4 | 845/845 | 1.0 (ref) | 0.89 (0.64,1.23) | 1.01 (0.72,1.40) | 1.11 (0.80,1.55) | 1.30 (0.93,1.82) | 0.02 |
| By tumor site | |||||||
| Colon | |||||||
| Age-adjusted OR (95% CI) | 759/759 | 1.0 (ref) | 0.94 (0.68,1.30) | 1.11 (0.79,1.54) | 1.19 (0.86,1.64) | 1.34 (0.98,1.82) | 0.02 |
| Multivariate OR (95% CI) | 679/679 | 1.0 (ref) | 0.96 (0.67,1.38) | 1.11 (0.77,1.61) | 1.14 (0.79,1.64) | 1.37 (0.95,1.97) | 0.04 |
| Proximal | |||||||
| Age-adjusted OR (95% CI) | 554/554 | 1.0 (ref) | 1.00 (0.68,1.47) | 1.17 (0.79,1.73) | 1.36 (0.93,1.98) | 1.32 (0.92,1.91) | 0.07 |
| Multivariate OR (95% CI) | 495/495 | 1.0 (ref) | 0.99 (0.65,1.51) | 1.20 (0.78,1.86) | 1.33 (0.87,2.04) | 1.32 (0.86,2.03) | 0.13 |
| Distal | |||||||
| Age-adjusted OR (95% CI) | 205/205 | 1.0 (ref) | 0.78 (0.41,1.49) | 0.90 (0.48,1.70) | 0.77 (0.40,1.46) | 1.32 (0.73,2.39) | 0.15 |
| Multivariate OR (95% CI) | 184/184 | 1.0 (ref) | 1.01 (0.48,2.14) | 0.89 (0.44,1.83) | 0.66 (0.31,1.41) | 1.60 (0.78,3.29) | 0.12 |
| Rectal | |||||||
| Age-adjusted OR (95% CI) | 178/178 | 1.0 (ref) | 0.64 (0.29,1.40) | 0.63 (0.30,1.31) | 0.97 (0.48,1.93) | 0.97 (0.48,1.94) | 0.49 |
| Multivariate OR (95% CI) | 150/150 | 1.0 (ref) | 0.56 (0.23,1.39) | 0.50 (0.20,1.21) | 1.01 (0.43,2.41) | 0.88 (0.36,2.15) | 0.59 |
| By stage | |||||||
| Local/regional | |||||||
| Age-adjusted OR (95% CI) | 814/814 | 1.0 (ref) | 0.79 (0.57,1.10) | 0.89 (0.65,1.22) | 1.12 (0.82,1.53) | 1.19 (0.88,1.61) | 0.02 |
| Multivariate OR (95% CI) | 717/717 | 1.0 (ref) | 0.75 (0.52,1.07) | 0.86 (0.60,1.24) | 1.10 (0.76,1.59) | 1.16 (0.81,1.66) | 0.05 |
| Metastatic | |||||||
| Age-adjusted OR (95% CI) | 120/120 | 1.0 (ref) | 1.62 (0.72,3.65) | 2.32 (0.91,5.92) | 1.30 (0.59,2.86) | 2.45 (1.02,5.90) | 0.17 |
| Multivariate OR (95% CI) | 111/111 | 1.0 (ref) | 2.14 (0.84,5.50) | 3.67 (1.22,11.0) | 1.87 (0.73,4.77) | 4.24 (1.34,13.4) | 0.10 |
Quintiles based on controls. CRP Q1 median=0.6 mg/L, Q2 median=1.4 mg/L, Q3 median=2.5 mg/L, Q4 median=4.5 mg/L, Q5 median=9.1 mg/L.
P-value based on quintile median trend test.
The numbers do not add up to 988 because there were 35 participants with missing CRP; hence the women and their matched pairs were dropped from the analyses
Multivariate model adjusted for age (50-54, 55-59, 60-64, 65-69, 70-74, 75-79 years), body mass index (BMI) at baseline, hormone replacement therapy (HT) use (never, past, current), previous colonoscopy (yes/no), and pack-years of smoking.
Though the ORs were in the same direction as for CRP, the associations between SAA and CRC risk were weaker (Table 3). The age-and multivariate-adjusted ORs were 1.22 (0.92-1.62, p-trend =0.11) and 1.19 (0.84-1.58, p-trend=0.23), respectively. For colon and rectal tumors, the multivariate-adjusted ORs were 1.26 (0.88-1.80, p-trend=0.10) and 0.72 (0.33-1.57, p-trend=0.19), respectively.
Table 3.
Odds ratios (ORs) and 95% confidence intervals of colorectal cancer by quintile of baseline SAA concentrations
| Quintiles of baseline SAA (mg/L)1 | |||||||
|---|---|---|---|---|---|---|---|
| Cases/controls | 1 ≤ 3.0 |
2 > 3.0 – 4.3 |
3 > 4.3 – 6.2 |
4 > 6.2 – 10.5 |
5 > 10.5 |
P trend2 | |
| All participants | 390 | 353 | 380 | 408 | 420 | ||
| Age-adjusted OR (95% CI) | 966/9663 | 1.0 (ref) | 1.01 (0.76,1.35) | 1.14 (0.85,1.53) | 1.24 (0.94,1.65) | 1.22 (0.92,1.62) | 0.11 |
| Multivariate OR (95% CI)4 | 857/857 | 1.0 (ref) | 0.98 (0.71,1.35) | 1.18 (0.86,1.62) | 1.16 (0.84,1.58) | 1.19 (0.84,1.58) | 0.23 |
| By tumor site | |||||||
| Colon | |||||||
| Age-adjusted OR (95% CI) | 772/772 | 1.0 (ref) | 0.92 (0.66,1.26) | 1.22 (0.88,1.68) | 1.36 (0.99,1.86) | 1.30 (0.94,1.78) | 0.04 |
| Multivariate OR (95% CI) | 691/691 | 1.0 (ref) | 0.87 (0.61,1.24) | 1.30 (0.91,1.86) | 1.29 (0.91,1.82) | 1.26 (0.88,1.80) | 0.10 |
| Proximal | |||||||
| Age-adjusted OR (95% CI) | 565/565 | 1.0 (ref) | 1.07 (0.74,1.56) | 1.24 (0.85,1.80) | 1.60 (1.11,2.31) | 1.33 (0.91,1.92) | 0.09 |
| Multivariate OR (95% CI) | 506/506 | 1.0 (ref) | 1.07 (0.71,1.60) | 1.31 (0.87,1.97) | 1.56 (1.04,2.33) | 1.26 (0.82,1.93) | 0.27 |
| Distal | |||||||
| Age-adjusted OR (95% CI) | 207/207 | 1.0 (ref) | 0.53 (0.27,1.03) | 1.14 (0.58,2.21) | 0.79 (0.42,1.50) | 1.15 (0.61,2.19) | 0.22 |
| Multivariate OR (95% CI) | 185/185 | 1.0 (ref) | 0.39 (0.18,0.88) | 1.16 (0.55,2.44) | 0.66 (0.32,1.37) | 1.15 (0.56,2.37) | 0.15 |
| Rectal | |||||||
| Age-adjusted OR (95% CI) | 179/179 | 1.0 (ref) | 1.42 (0.69,2.96) | 0.77 (0.36,1.68) | 0.78 (0.38,1.60) | 0.78 (0.40,1.52) | 0.23 |
| Multivariate OR (95% CI) | 151/151 | 1.0 (ref) | 1.45 (0.62,3.43) | 0.68 (0.28,1.65) | 0.60 (0.25,1.42) | 0.72 (0.33,1.57) | 0.19 |
| By stage | |||||||
| Local/regional | |||||||
| Age-adjusted OR (95% CI) | 823/823 | 1.0 (ref) | 0.86 (0.62,1.17) | 1.02 (0.74,1.40) | 1.15 (0.85,1.55) | 1.08 (0.80,1.47) | 0.26 |
| Multivariate OR (95% CI) | 725/725 | 1.0 (ref) | 0.83 (0.58,1.17) | 1.04 (0.74,1.47) | 1.04 (0.75,1.47) | 1.01 (0.71,1.44) | 0.59 |
| Metastatic | |||||||
| Age-adjusted OR (95% CI) | 124/124 | 1.0 (ref) | 2.89 (1.24,6.77) | 2.72 (1.13,6.54) | 2.24 (0.90,5.58) | 2.98 (1.23,7.23) | 0.17 |
| Multivariate OR (95% CI) | 115/115 | 1.0 (ref) | 2.89 (1.15,7.22) | 2.90 (1.11,7.59) | 1.91 (0.71,5.14) | 3.49 (1.24,9.84) | 0.16 |
Quintiles based on controls. SAA Q1 median=2.3 mg/L, Q2 median=3.7 mg/L, Q3 median=5.2 mg/L, Q4 median=7.9 mg/L, Q5 median=15.15 mg/L.
P-value based on quintile median trend test.
The numbers do not add up to 988 because there were 22 participants with missing SAA; hence the women and their matched pairs were dropped from the analyses
Multivariate model adjusted for age (50-54, 55-59, 60-64, 65-69, 70-74, 75-79 years), body mass index (BMI) at baseline, hormone replacement therapy (HT) use (never, past, current), previous colonoscopy (yes/no), and pack-years of smoking.
In stratified analyses among women with data on both biomarkers (Table 4), women with high CRP/SAA had an OR=1.38 (1.07-1.79, p-value=0.01) compared to women with low CRP/SAA. As previously observed, the increased risk was apparent for colon cancer (OR=1.50, 1.11-2.00, p-value=0.006), but not rectal cancer. The association between CRP/SAA and CRC risk was slightly stronger in analyses not including BMI in the multivariate model (Table 4b).
Table 4.
Odds ratios (ORs) and 95% confidence intervals of colorectal cancer associated with combined CRP and SAA concentrations
| Combined CRP and SAA1 | ||||||||
|---|---|---|---|---|---|---|---|---|
| Low CRP Low SAA |
Low CRP High SAA |
High CRP Low SAA |
High CRP High SAA |
|||||
|
| ||||||||
| Cases/controls | OR | P-value | OR | P | OR | P-value | ||
| All participants | 701 | 325 | 318 | 586 | ||||
| Age-adjusted OR (95% CI) | 945/945 | 1.0 (ref) | 1.16 (0.88,1.52) | 0.31 | 1.20 (0.90,1.58) | 0.21 | 1.35 (1.08,1.69) | 0.008 |
| Multivariate OR (95% CI)2 | 837/837 | 1.0 (ref) | 1.17 (0.86,1.58) | 0.31 | 1.19 (0.87,1.62) | 0.28 | 1.38 (1.07,1.79) | 0.01 |
| By tumor site | ||||||||
| Colon | ||||||||
| Age-adjusted OR (95% CI) | 754/754 | 1.0 (ref) | 1.29 (0.95,1.76) | 0.11 | 1.08 (0.79,1.47) | 0.63 | 1.48 (1.15,1.90) | 0.002 |
| Multivariate OR (95% CI) | 674/674 | 1.0 (ref) | 1.36 (0.97,1.91) | 0.07 | 1.10 (0.78,1.54) | 0.60 | 1.50 (1.12,2.00) | 0.006 |
| Proximal | ||||||||
| Age-adjusted OR (95% CI) | 550/550 | 1.0 (ref) | 1.42 (1.00,2.03) | 0.053 | 1.10 (0.76,1.57) | 0.62 | 1.48 (1.11,1.97) | 0.008 |
| Multivariate OR (95% CI) | 491/491 | 1.0 (ref) | 1.49 (1.01,2.18) | 0.04 | 1.13 (0.76,1.67) | 0.55 | 1.50 (1.07,2.09) | 0.02 |
| Distal | ||||||||
| Age-adjusted OR (95% CI) | 204/204 | 1.0 (ref) | 0.86 (0.46,1.66) | 0.66 | 0.94 (0.50,1.76) | 0.84 | 1.42 (0.85,2.36) | 0.18 |
| Multivariate OR (95% CI) | 183/183 | 1.0 (ref) | 0.89 (0.42,1.91) | 0.77 | 0.88 (0.43,1.82) | 0.73 | 1.52 (0.83,2.77) | 0.18 |
| Rectal | ||||||||
| Age-adjusted OR (95% CI) | 176/176 | 1.0 (ref) | 0.56 (0.28,1.10) | 0.09 | 1.89 (0.92,3.90) | 0.08 | 0.91 (0.53,1.56) | 0.74 |
| Multivariate OR (95% CI) | 148/148 | 1.0 (ref) | 0.39 (0.17,0.92) | 0.03 | 1.73 (0.72,4.14) | 0.22 | 0.90 (0.46,1.78) | 0.77 |
| By stage | ||||||||
| Local/regional | ||||||||
| Age-adjusted OR (95% CI) | 807/807 | 1.0 (ref) | 1.12 (0.83,1.52) | 0.47 | 1.24 (0.91,1.68) | 0.17 | 1.34 (1.05,1.70) | 0.02 |
| Multivariate OR (95% CI) | 710/710 | 1.0 (ref) | 1.11 (0.79,1.55) | 0.55 | 1.27 (0.90,1.79) | 0.17 | 1.35 (1.02,1.79) | 0.03 |
| Metastatic | ||||||||
| Age-adjusted OR (95% CI) | 120/120 | 1.0 (ref) | 1.04 (0.51,2.15) | 0.91 | 0.92 (0.44,1.92) | 0.82 | 1.77 (0.89,3.51) | 0.10 |
| Multivariate OR (95% CI) | 111/111 | 1.0 (ref) | 1.11 (0.50,2.49) | 0.79 | 0.98 (0.42,2.26) | 0.95 | 2.35 (1.00,5.54) | 0.05 |
Categories based on CRP and SAA baseline medians among controls. CRP median=2.5 mg/L; SAA median=5.3mg/L.
Multivariate model adjusted for age (50-54, 55-59, 60-64, 65-69, 70-74, 75-79 years), body mass index (BMI) at baseline, hormone replacement therapy (HT) use (never, past, current), previous colonoscopy (yes/no), and pack-years of smoking.
Table 4b.
Odds ratios (ORs) and 95% confidence intervals of colorectal cancer associated with combined CRP and SAA concentrations (excluding BMI)
| Combined CRP and SAA1 | ||||||||
|---|---|---|---|---|---|---|---|---|
| Low CRP Low SAA |
Low CRP High SAA |
High CRP Low SAA |
High CRP High SAA |
|||||
|
| ||||||||
| Cases/controls | OR | P-value | OR | P | OR | P-value | ||
| All participants | 701 | 325 | 318 | 586 | ||||
| Multivariate OR (95% CI)2 | 857/857 | 1.0 (ref) | 1.16 (0.86,1.57) | 0.32 | 1.28 (0.95,1.74) | 0.11 | 1.49 (1.17,1.90) | 0.001 |
| By tumor site | ||||||||
| Colon | ||||||||
| Multivariate OR (95% CI) | 690/690 | 1.0 (ref) | 1.38 (0.99,1.93) | 0.06 | 1.17 (0.84,1.64) | 0.35 | 1.64 (1.25,2.16) | 0.0004 |
| Proximal | ||||||||
| Multivariate OR (95% CI) | 503/503 | 1.0 (ref) | 1.50 (1.03,2.19) | 0.04 | 1.18 (0.80,1.73) | 0.42 | 1.62 (1.19,2.22) | 0.003 |
| Distal | ||||||||
| Multivariate OR (95% CI) | 187/187 | 1.0 (ref) | 0.91 (0.43,1.91) | 0.80 | 1.03 (0.51,2.07) | 0.94 | 1.64 (0.91,2.95) | 0.10 |
| Rectal | ||||||||
| Multivariate OR (95% CI) | 152/152 | 1.0 (ref) | 0.37 (0.16,0.85) | 0.02 | 1.77 (0.77,4.08) | 0.18 | 0.86 (0.46,1.62) | 0.65 |
| By stage | ||||||||
| Local/regional | ||||||||
| Multivariate OR (95% CI) | 729/729 | 1.0 (ref) | 1.09 (0.78,1.52) | 0.61 | 1.36 (0.97,1.90) | 0.07 | 1.43 (1.10,1.86) | 0.008 |
| Metastatic | ||||||||
| Multivariate OR (95% CI) | 112/112 | 1.0 (ref) | 1.18 (0.53,2.63) | 0.69 | 0.98 (0.43,2.25) | 0.96 | 2.75 (1.20,6.27) | 0.02 |
Categories based on CRP and SAA baseline medians among controls. CRP median=2.5 mg/L; SAA median=5.3mg/L.
Multivariate model adjusted for age (50-54, 55-59, 60-64, 65-69, 70-74, 75-79 years), hormone replacement therapy (HT) use (never, past, current), previous colonoscopy (yes/no), and pack-years of smoking.
We also investigated the impact of long-term high CRP concentrations on CRC risk and observed marginally significant increased risk (ORhigh/high vs. ORlow/low for CRC=1.25 (1.00-1.56, p-value=0.05) in the age-adjusted, but not in the multivariate-adjusted (ORhigh/high vs. ORlow/low for CRC=1.23, 0.95-1.58 p-value=0.11) model. (Supplementary Table 2, online publication only). Compared to analysis using baseline CRP concentrations, somewhat stronger and statistically significant associations were observed for proximal colon cancer; ORhigh/high vs. ORlow/low =1.43 (1.03-1.97, p-value=0.03). Similar to CRP, long-term high SAA concentrations were associated with significantly increased risk of proximal colon cancer, ORhigh/high vs. ORlow/low=1.50 (1.10-2.04, p-value=0.01) (Supplementary Table 3, online publication only).
In analyses stratified by BMI categories, there was no indication of an increased risk among women with BMI <25 kg/m2 (Supplementary Table 4, online publication only). However, among overweight women (BMI 25-30 kg/m2), the ORs of colorectal, colon and proximal colon cancers associated with elevated CRP concentrations were 1.46 (0.83-2.56, p-trend=0.04), 1.36 (0.74-2.48, p-trend=0.11) and 1.85 (0.91-3.76, p-trend=0.03), respectively. Similarly elevated risks, although not statistically significant, were observed among obese women (p-interaction=0.59, 0.23 and 0.17 for CRC, colon and proximal colon, respectively). There was no evidence of effect modification by any HT use (p-interaction=0.75 for CRC). The associations did not differ by type of HT (estrogen alone and estrogen+progesterone combination) (data not shown).
The largest quintile increase in CRP concentration from baseline to year-3 follow-up (>73 %) was associated with a non-significant increased risk of CRC (OR=1.34, 0.91-1.95, p-trend=0.13) (Table 5). No tumor-site-specific differences were observed. For SAA, the associations were weaker and the ORs were closer to unity (Table 6).
Table 5.
Odds ratios (ORs) and 95% confidence intervals of colorectal cancer associated with percentage changes in CRP concentrations from baseline examination to 3-year follow-up
| Quintiles of percentage change in CRP1 | |||||||
|---|---|---|---|---|---|---|---|
| Cases/controls | 1 ≤ −45.3% |
2 > −45.3 – −15.7% |
3 > −15.7 – 12.1% |
4 > 12.1 – 73.4% |
5 > 73.4% |
P trend2 | |
| All participants | 310 | 316 | 326 | 349 | 340 | ||
| Age-adjusted OR (95% CI) | 748/748 | 1.0 (ref) | 1.05 (0.75,1.47) | 1.05 (0.75,1.48) | 1.28 (0.92,1.78) | 1.19 (0.84,1.69) | 0.29 |
| Multivariate OR (95% CI)3 | 662/622 | 1.0 (ref) | 1.17 (0.81,1.69) | 1.06 (0.73,1.54) | 1.40 (0.98,2.01) | 1.34 (0.91,1.95) | 0.13 |
| By tumor site | |||||||
| Colon | |||||||
| Age-adjusted OR (95% CI) | 610/610 | 1.0 (ref) | 0.97 (0.67,1.41) | 1.07 (0.73,1.57) | 1.18 (0.82,1.69) | 1.11 (0.75,1.65) | 0.47 |
| Multivariate OR (95% CI) | 544/544 | 1.0 (ref) | 1.05 (0.70,1.59) | 1.07 (0.71,1.62) | 1.23 (0.83,1.82) | 1.23 (0.80,1.90) | 0.28 |
| Proximal | |||||||
| Age-adjusted OR (95% CI) | 450/450 | 1.0 (ref) | 1.07 (0.69,1.66) | 1.00 (0.65,1.55) | 1.17 (0.78,1.77) | 1.25 (0.78,1.99) | 0.29 |
| Multivariate OR (95% CI) | 401/401 | 1.0 (ref) | 1.12 (0.70,1.81) | 1.02 (0.64,1.62) | 1.21 (0.78,1.89) | 1.33 (0.80,2.21) | 0.24 |
| Distal | |||||||
| Age-adjusted OR (95% CI) | 160/160 | 1.0 (ref) | 0.85 (0.40,1.82) | 1.35 (0.61,2.97) | 1.36 (0.64,2.91) | 0.95 (0.44,2.06) | 0.83 |
| Multivariate OR (95% CI) | 143/143 | 1.0 (ref) | 1.11 (0.48,2.58) | 1.32 (0.55,3.21) | 1.51 (0.65,3.51) | 1.24 (0.52,3.00) | 0.68 |
| Rectal | |||||||
| Age-adjusted OR (95% CI) | 131/131 | 1.0 (ref) | 1.23 (0.57,2.65) | 0.87 (0.38,2.00) | 1.87 (0.81,4.31) | 1.46 (0.65,3.27) | 0.33 |
| Multivariate OR (95% CI) | 111/111 | 1.0 (ref) | 1.62 (0.63,4.16) | 1.01 (0.38,2.67) | 2.94 (1.04,8.29) | 1.65 (0.68,4.03) | 0.33 |
| By stage | |||||||
| Local/regional | |||||||
| Age-adjusted OR (95% CI) | 660/660 | 1.0 (ref) | 1.00 (0.70,1.43) | 1.06 (0.74,1.52) | 1.31 (0.92,1.87) | 1.12 (0.76,1.61) | 0.50 |
| Multivariate OR (95% CI) | 581/581 | 1.0 (ref) | 1.10 (0.74,1.62) | 1.05 (0.71,1.57) | 1.41 (0.95,2.01) | 1.22 (0.80,1.84) | 0.30 |
| Metastatic | |||||||
| Age-adjusted OR (95% CI) | 79/79 | 1.0 (ref) | 1.34 (0.45,4.04) | 0.90 (0.27,3.00) | 1.21 (0.45,3.25) | 1.89 (0.67,5.39) | 0.17 |
| Multivariate OR (95% CI) | 73/73 | 1.0 (ref) | 1.44 (0.41,5.05) | 0.99 (0.25,3.87) | 1.73 (0.58,5.16) | 2.03 (0.63,6.54) | 0.20 |
Quintiles based on controls. CRP Q1 median=−62.5 mg/L, Q2 median=−31.3 mg/L, Q3 median=0.0 mg/L, Q4 median=35.5 mg/L, Q5 median=178.8 mg/L.
P-value based on quintile median trend test.
Multivariate model adjusted for age (50-54, 55-59, 60-64, 65-69, 70-74, 75-79 years), body mass index (BMI) at baseline, hormone replacement therapy (HT) use (never, past, current), previous colonoscopy (yes/no), and pack-years of smoking.
Table 6.
Odds ratios (ORs) and 95% confidence intervals of colorectal cancer associated with percentage changes in SAA concentrations from baseline examination to 3-year follow-up
| Quintiles of percentage change in SAA1 | |||||||
|---|---|---|---|---|---|---|---|
| Cases/controls | 1 ≤ −27.9% |
2 > −27.9 – −5.56% |
3 > −5.56 – 13.3% |
4 > 13.3 – 49.1% |
5 > 49.1% |
P trend2 | |
| All participants | 326 | 351 | 306 | 337 | 338 | ||
| Age-adjusted OR (95% CI) | 765/765 | 1.0 (ref) | 1.06 (0.76,1.47) | 0.80 (0.56,1.13) | 1.00 (0.72,1.40) | 0.97 (0.69,1.36) | 0.82 |
| Multivariate OR (95% CI)3 | 678/678 | 1.0 (ref) | 1.08 (0.76,1.55) | 0.81 (0.55,1.18) | 0.96 (0.67,1.38) | 1.05 (0.72,1.51) | 0.94 |
| By tumor site | |||||||
| Colon | |||||||
| Age-adjusted OR (95% CI) | 626/626 | 1.0 (ref) | 1.05 (0.73,1.52) | 1.83 (0.56,1.22) | 1.05 (0.72,1.53) | 0.99 (0.67,1.45) | 0.96 |
| Multivariate OR (95% CI) | 559/559 | 1.0 (ref) | 1.07 (0.72,1.59) | 0.81 (0.54,1.24) | 1.04 (0.69,1.56) | 1.04 (0.69,1.56) | 0.99 |
| Proximal | |||||||
| Age-adjusted OR (95% CI) | 462/462 | 1.0 (ref) | 1.03 (0.67,1.57) | 0.71 (0.45,1.12) | 1.15 (0.75,1.77) | 0.95 (0.61,1.49) | 0.98 |
| Multivariate OR (95% CI) | 413/413 | 1.0 (ref) | 1.01 (0.64,1.60) | 0.69 (0.42,1.12) | 1.16 (0.73,1.86) | 0.99 (0.61,1.61) | 0.87 |
| Distal | |||||||
| Age-adjusted OR (95% CI) | 164/164 | 1.0 (ref) | 1.17 (0.56,2.46) | 1.13 (0.52,2.44) | 0.77 (0.34,1.74) | 1.02 (0.48,2.20) | 0.87 |
| Multivariate OR (95% CI) | 146/146 | 1.0 (ref) | 1.38 (0.58,3.27) | 1.21 (0.49,2.95) | 0.68 (0.26,1.75) | 0.99 (0.41,2.39) | 0.70 |
| Rectal | |||||||
| Age-adjusted OR (95% CI) | 132/132 | 1.0 (ref) | 0.94 (0.40,2.21) | 0.82 (0.35,1.86) | 0.85 (0.39,1.86) | 0.92 (0.41,2.04) | 0.80 |
| Multivariate OR (95% CI) | 112/112 | 1.0 (ref) | 0.87 (0.35,2.18) | 0.95 (0.34,2.62) | 0.73 (0.31,1.74) | 1.06 (0.44,2.52) | 0.94 |
| By stage | |||||||
| Local/regional | |||||||
| Age-adjusted OR (95% CI) | 672/672 | 1.0 (ref) | 0.98 (0.69,1.40) | 0.74 (0.51,1.07) | 0.93 (0.65,1.32) | 0.89 (0.62,1.28) | 0.55 |
| Multivariate OR (95% CI) | 592/592 | 1.0 (ref) | 0.97 (0.66,1.43) | 0.68 (0.46,1.03) | 0.88 (0.60,1.31) | 0.90 (0.60,1.35) | 0.61 |
| Metastatic | |||||||
| Age-adjusted OR (95% CI) | 83/83 | 1.0 (ref) | 1.59 (0.56,4.56) | 1.61 (0.52,5.04) | 2.37 (0.72,7.81) | 1.94 (0.70,5.40) | 0.24 |
| Multivariate OR (95% CI) | 77/77 | 1.0 (ref) | 1.64 (0.51,5.23) | 2.31 (0.63,8.41) | 3.31 (0.85,12.89) | 2.70 (0.83,8.18) | 0.11 |
Quintiles based on controls. SAA Q1 median=-44.6 mg/L, Q2 median=-16.1 mg/L, Q3 median=4.08 mg/L, Q4 median=26.7 mg/L, Q5 median=83.8 mg/L.
P-value based on quintile median trend test.
Multivariate model adjusted for age (50-54, 55-59, 60-64, 65-69, 70-74, 75-79 years), body mass index (BMI) at baseline, hormone replacement therapy (HT) use (never, past, current), previous colonoscopy (yes/no), and pack-years of smoking.
We tested the value of CRP as a biomarker for early detection by evaluating the AUC for cancers diagnosed within 6-months of blood-draw. The AUCs for CRP and SAA were 0.62 (95%CI 0.55-0.68) and 0.60 (0.53-0.67), respectively, indicating that the markers, when used alone, are not adequate early detection markers. We also explored if combining SAA and CRP will lead to clinically meaningful incremental value compared with using CRP alone but SAA did not provide improvement on the ROC curve (AUC=0.62, 95%CI 0.56-0.68) (Supplementary Figure 1, online publication only). Identical AUCs were obtained for cancers diagnosed within 1-year of blood-draw (data not shown).
The results were not altered in secondary analyses excluding cases with high CRP values (>10mg/L) or cases diagnosed within two years of enrolment (data not shown).
Discussion
In the largest prospective study to date among women, we observed a modest positive association between baseline CRP concentrations and CRC risk which was limited to colon cancers; no corresponding significant associations were observed for SAA. Women with high levels of both CRP and SAA combined had an increased risk of CRC, particularly colon cancer, compared to those with low levels of both biomarkers. Women with consistently high levels of either CRP or SAA concentrations had a significantly increased risk of proximal colon cancer. No positive associations were observed between the inflammatory factors and rectal cancer. CRP does not, however, appear suitable as an early detection marker for CRC, either used alone or in combination with SAA.
In spite of the compelling data linking chronic inflammation with colorectal carcinogenesis 2-4, 7, epidemiological studies investigating the association of CRP and CRC risk have been equivocal. The three studies conducted among women 19, 22, 24 have mainly reported inverse associations, contrary to what is expected 16, 18. In the Women’s Health Study19 with 169 CRC cases over a 10-year period, women with CRP >3.0mg/L had a borderline statistically significantly reduced risk of CRC (OR=0.66, 0.43-1.03) and a 56% significantly reduced risk of colon cancer. Similarly, within the Nurses’ Health Study (280 CRC cases), 24 elevated CRP concentrations were associated with a 35% lower risk of CRC.
Our study with 953 cases (for CRP), the largest to date among women, supports the role of inflammation in colorectal carcinogenesis, mainly within the colon. Prior to our study, the EPIC study with 1096 cases, of which 545 were women, reported a significant 74% increased risk of colon cancer among men with high CRP concentrations, however, the excess risk among women was non-significant (+6%) 26.
We specifically investigated BMI, as it is closely linked to CRP, as well as other mechanisms related to CRC risk (e.g. insulin levels and sex hormone levels). Although there were somewhat stronger associations between CRP and CRC risk in analyses excluding BMI, and our stratified analyses suggest stronger associations between CRP and CRC risk in heavier women, we observed no significant interactions between BMI and CRC risk.
One reason why the results from our study differ from those of other studies may be because of the sample size. We had almost twice the number of CRC cases as the previous largest study among women, the EPIC study. This large number allowed us to obtain fairly robust risk estimates for the different tumor sites. Thus, the results from our large study offer important new evidence that inflammation, determined by serum CRP and SAA concentrations, is positively associated with CRC risk among women. However, there may also be other possible reasons for divergent results: for example, compared to the EPIC study, our population was more homogenous, all postmenopausal (vs. 74% of the women in the EPIC study), more likely to use HT and on the average older (68 vs. 59 years) 26. We had comparable number of rectal cancer cases (184 cases) as in the EPIC study (182 cases) and similar to results from the EPIC study, we observed no association between elevated CRP concentrations and rectal cancer risk. This lack of association, noted in previous studies and confirmed in our study most likely reflects the difference in the biology of the colon and rectum.
To the best of our knowledge, no previous study has evaluated the association of SAA with CRC risk. Although, CRP and SAA are major acute-phase reactants, they differ in many respects. The cytokine regulation of SAA production is different from that of CRP and it is suggested that SAA and CRP may respond differently to various stimuli 33. CRP has many immune-related functions, such as opsonization and activation of the classical complement binding, while SAA participates in cholesterol transport, extracellular matrix degradation and recruitment of inflammatory cells 13, 34, 35. In our study, the risk estimates of colorectal cancer in relation to SAA were in the same direction as those for CRP but of slightly differing magnitudes, suggesting that though these biomarkers may be able to predict CRC, their abilities vary. The reasons why SAA was less predictive of an inflammatory etiology for CRC are not clear since it is a more sensitive inflammatory biomarker in certain conditions 36. When CRP and SAA were categorized dichotomously, there was significant improvement in the fit of the colon cancer model if both biomarkers were considered in combination vs. individually. Here a 1.5-fold increased risk of colon cancer was observed among women with elevated concentrations of both biomarkers. This suggests a somewhat greater robustness for a combination of both biomarkers in relation to colon cancer risk, similar to what was recently observed for lung cancer where the combination of CRP and IL-8 was more robustly related to lung cancer risk than either marker alone 37.
Our study showed that although CRP is associated with an increased risk of CRC, it is too non-specific to be suitable as an early detection marker. Also, based on the ROC analysis, the incremental value of adding SAA to CRP in predicting CRC or colon cancer risk was not strong. Today’s screening modalities for CRC are effective, but costly or invasive (colonoscopy) or have limited sensitivity and specificity (FOBT). Thus the development of new blood-based markers is a high priority. Elevations in CRP concentrations could potentially aid in risk prediction and targeted screening, however, the rise in CRP levels among cases was too small and inconsistent to be an independent marker for early detection. Nevertheless, we do not want to exclude that CRP may have utility as part of a multivariate panel of blood-based biomarkers or used in conjunction with other screening modalities.
Strengths of our study include its prospective design, large size and the fact that we measured the inflammatory biomarkers at two time points which allowed us to investigate the impact of changes in, and long-term, biomarker concentrations on CRC risk. Compared to previous studies among women, our study had the largest number of cases which enabled us to undertake stratified analysis by tumor site and stage. We also assessed CRC risk by combining the two inflammatory markers, thereby, providing more robust risk estimates for accurate classification of chronic inflammatory exposure. A limitation of our study is that it is limited to postmenopausal women. Also, since our study is an observational study, we cannot completely rule out residual confounding even though we adjusted for known confounders.
We have demonstrated that elevated biomarkers of inflammation are associated with CRC risk, notably colon cancer, thereby supporting the role of inflammation in colorectal carcinogenesis. Nevertheless, the ROC curve and analyses involving multiple measurements preclude the use of CRP and SAA as independent early detection markers for CRC.
Supplementary Material
Novelty.
This is (a) the largest study investigating the association between C-reactive-protein and colorectal cancer (CRC) risk among women and the first investigating serum-amyloid-A; (b) the first study exploring how changes in these biomarkers over a three-year period are associated with CRC risk and determining their usefulness as early detection markers.
Impact statement.
Although CRP, and to some extent SAA, were positively associated with CRC risk, they had low discriminatory capacity as early detection markers.
Acknowledgments
We would like to thank the study participants of the Women’s Health Initiative Observational Study, the study staff and WHI investigators.
Funding The WHI program is funded by the National Heart, Lung, and Blood Institute, NIH, U.S. Department of Health and Human Services through contracts N01WH22110, 24152, 32100-2, 32105-6, 32108-9, 32111-13, 32115, 32118-32119, 32122, 42107-26, 42129-32, and 44221. This work was supported by research grants from the National Institute for Health [NIH R01 CA120523 and N01WH22110 to CM Ulrich].
Role of funding source The funding source had no role in the study design, interpretation of data and publication of results.
Footnotes
Conflict of interests None declared
Program Office: (National Heart, Lung, and Blood Institute, Bethesda, Maryland) Jacques Rossouw, Shari Ludlam, Dale Burwen, Joan McGowan, Leslie Ford, and Nancy Geller
Clinical Coordinating Center: Clinical Coordinating Center: (Fred Hutchinson Cancer Research Center, Seattle, WA) Garnet Anderson, Ross Prentice, Andrea LaCroix, and Charles Kooperberg
Investigators and Academic Centers: (Brigham and Women’s Hospital, Harvard Medical School, Boston, MA) JoAnn E. Manson; (MedStar Health Research Institute/Howard University, Washington, DC) Barbara V. Howard; (Stanford Prevention Research Center, Stanford, CA) Marcia L. Stefanick; (The Ohio State University, Columbus, OH) Rebecca Jackson; (University of Arizona, Tucson/Phoenix, AZ) Cynthia A. Thomson; (University at Buffalo, Buffalo, NY) Jean Wactawski-Wende; (University of Florida, Gainesville/Jacksonville, FL) Marian Limacher; (University of Iowa, Iowa City/Davenport, IA) Robert Wallace; (University of Pittsburgh, Pittsburgh, PA) Lewis Kuller; (Wake Forest University School of Medicine, Winston-Salem, NC) Sally Shumaker
Women’s Health Initiative Memory Study: (Wake Forest University School of Medicine, Winston-Salem, NC) Sally Shumaker
References
- 1.Ulrich CM, Bigler J, Potter JD. Non-steroidal anti-inflammatory drugs for cancer prevention: promise, perils and pharmacogenetics. Nat Rev Cancer. 2006;6:130–40. doi: 10.1038/nrc1801. [DOI] [PubMed] [Google Scholar]
- 2.Coussens LM, Werb Z. Inflammation and cancer. Nature. 2002;420:860–7. doi: 10.1038/nature01322. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Ullman TA, Itzkowitz SH. Intestinal inflammation and cancer. Gastroenterology. 2011;140:1807–16. doi: 10.1053/j.gastro.2011.01.057. [DOI] [PubMed] [Google Scholar]
- 4.Canavan C, Abrams KR, Mayberry J. Meta-analysis: colorectal and small bowel cancer risk in patients with Crohn’s disease. Aliment Pharm Therap. 2006;23:1097–104. doi: 10.1111/j.1365-2036.2006.02854.x. [DOI] [PubMed] [Google Scholar]
- 5.Flossmann E, Rothwell PM. Effect of aspirin on long-term risk of colorectal cancer: consistent evidence from randomised and observational studies. Lancet. 2007;369:1603–13. doi: 10.1016/S0140-6736(07)60747-8. [DOI] [PubMed] [Google Scholar]
- 6.Cole BF, Logan RF, Halabi S, Benamouzig R, Sandler RS, Grainge MJ, Chaussade S, Baron JA. Aspirin for the chemoprevention of colorectal adenomas: meta-analysis of the randomized trials. J Natl Cancer Inst. 2009;101:256–66. doi: 10.1093/jnci/djn485. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Rothwell PM, Wilson M, Elwin CE, Norrving B, Algra A, Warlow CP, Meade TW. Long-term effect of aspirin on colorectal cancer incidence and mortality: 20-year follow-up of five randomised trials. Lancet. 2010;376:1741–50. doi: 10.1016/S0140-6736(10)61543-7. [DOI] [PubMed] [Google Scholar]
- 8.Ruder EH, Laiyemo AO, Graubard BI, Hollenbeck AR, Schatzkin A, Cross AJ. Non-Steroidal Anti-Inflammatory Drugs and Colorectal Cancer Risk in a Large, Prospective Cohort. Am J Gastroenterol. 2011 doi: 10.1038/ajg.2011.38. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Gabay C, Kushner I. Acute-phase proteins and other systemic responses to inflammation. N Engl J Med. 1999;340:448–54. doi: 10.1056/NEJM199902113400607. [DOI] [PubMed] [Google Scholar]
- 10.MacGregor AJ, Gallimore JR, Spector TD, Pepys MB. Genetic effects on baseline values of C-reactive protein and serum amyloid a protein: a comparison of monozygotic and dizygotic twins. Clin Chem. 2004;50:130–4. doi: 10.1373/clinchem.2003.028258. [DOI] [PubMed] [Google Scholar]
- 11.Maury CP. Comparative study of serum amyloid A protein and C-reactive protein in disease. Clin Sci (Lond) 1985;68:233–8. doi: 10.1042/cs0680233. [DOI] [PubMed] [Google Scholar]
- 12.Raynes JG, Cooper EH. Comparison of serum amyloid A protein and C-reactive protein concentrations in cancer and non-malignant disease. J Clin Pathol. 1983;36:798–803. doi: 10.1136/jcp.36.7.798. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Pierce BL, Ballard-Barbash R, Bernstein L, Baumgartner RN, Neuhouser ML, Wener MH, Baumgartner KB, Gilliland FD, Sorensen BE, McTiernan A, Ulrich CM. Elevated biomarkers of inflammation are associated with reduced survival among breast cancer patients. J Clin Oncol. 2009;27:3437–44. doi: 10.1200/JCO.2008.18.9068. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Erlinger TP, Platz EA, Rifai N, Helzlsouer KJ. C-reactive protein and the risk of incident colorectal cancer. JAMA. 2004;291:585–90. doi: 10.1001/jama.291.5.585. [DOI] [PubMed] [Google Scholar]
- 15.Il’yasova D, Colbert LH, Harris TB, Newman AB, Bauer DC, Satterfield S, Kritchevsky SB. Circulating levels of inflammatory markers and cancer risk in the health aging and body composition cohort. Cancer Epidemiol Biomarkers Prev. 2005;14:2413–8. doi: 10.1158/1055-9965.EPI-05-0316. [DOI] [PubMed] [Google Scholar]
- 16.Gunter MJ, Stolzenberg-Solomon R, Cross AJ, Leitzmann MF, Weinstein S, Wood RJ, Virtamo J, Taylor PR, Albanes D, Sinha R. A prospective study of serum C-reactive protein and colorectal cancer risk in men. Cancer Res. 2006;66:2483–7. doi: 10.1158/0008-5472.CAN-05-3631. [DOI] [PubMed] [Google Scholar]
- 17.Otani T, Iwasaki M, Sasazuki S, Inoue M, Tsugane S. Plasma C-reactive protein and risk of colorectal cancer in a nested case-control study: Japan Public Health Center-based prospective study. Cancer Epidemiol Biomarkers Prev. 2006;15:690–5. doi: 10.1158/1055-9965.EPI-05-0708. [DOI] [PubMed] [Google Scholar]
- 18.Prizment AE, Anderson KE, Visvanathan K, Folsom AR. Association of inflammatory markers with colorectal cancer incidence in the atherosclerosis risk in communities study. Cancer Epidemiol Biomarkers Prev. 2011;20:297–307. doi: 10.1158/1055-9965.EPI-10-1146. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Zhang SM, Buring JE, Lee IM, Cook NR, Ridker PM. C-reactive protein levels are not associated with increased risk for colorectal cancer in women. Ann Intern Med. 2005;142:425–32. doi: 10.7326/0003-4819-142-6-200503150-00008. [DOI] [PubMed] [Google Scholar]
- 20.Ito Y, Suzuki K, Tamakoshi K, Wakai K, Kojima M, Ozasa K, Watanabe Y, Kawado M, Hashimoto S, Suzuki S, Tokudome S, Toyoshima H, et al. Colorectal cancer and serum C-reactive protein levels: a case-control study nested in the JACC Study. J Epidemiol. 2005;15(Suppl 2):S185–9. doi: 10.2188/jea.15.S185. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Siemes C, Visser LE, Coebergh JW, Splinter TA, Witteman JC, Uitterlinden AG, Hofman A, Pols HA, Stricker BH. C-reactive protein levels, variation in the C-reactive protein gene, and cancer risk: the Rotterdam Study. J Clin Oncol. 2006;24:5216–22. doi: 10.1200/JCO.2006.07.1381. [DOI] [PubMed] [Google Scholar]
- 22.Heikkila K, Harris R, Lowe G, Rumley A, Yarnell J, Gallacher J, Ben-Shlomo Y, Ebrahim S, Lawlor DA. Associations of circulating C-reactive protein and interleukin-6 with cancer risk: findings from two prospective cohorts and a meta-analysis. Cancer Causes Control. 2009;20:15–26. doi: 10.1007/s10552-008-9212-z. [DOI] [PubMed] [Google Scholar]
- 23.Allin KH, Bojesen SE, Nordestgaard BG. Baseline C-reactive protein is associated with incident cancer and survival in patients with cancer. J Clin Oncol. 2009;27:2217–24. doi: 10.1200/JCO.2008.19.8440. [DOI] [PubMed] [Google Scholar]
- 24.Chan AT, Ogino S, Giovannucci EL, Fuchs CS. Inflammatory markers are associated with risk of colorectal cancer and chemopreventive response to anti-inflammatory drugs. Gastroenterology. 2011;140:799–808. doi: 10.1053/j.gastro.2010.11.041. quiz e11. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Tsilidis KK, Branchini C, Guallar E, Helzlsouer KJ, Erlinger TP, Platz EA. C-reactive protein and colorectal cancer risk: a systematic review of prospective studies. Int J Cancer. 2008;123:1133–40. doi: 10.1002/ijc.23606. [DOI] [PubMed] [Google Scholar]
- 26.Aleksandrova K, Jenab M, Boeing H, Jansen E, Bueno-de-Mesquita HB, Rinaldi S, Riboli E, Overvad K, Dahm CC, Olsen A, Tjonneland A, Boutron-Ruault MC, et al. Circulating C-reactive protein concentrations and risks of colon and rectal cancer: a nested case-control study within the European Prospective Investigation into Cancer and Nutrition. Am J Epidemiol. 2010;172:407–18. doi: 10.1093/aje/kwq135. [DOI] [PubMed] [Google Scholar]
- 27.Toriola AT, Ulrich CM. Is there a potential use for C-reactive protein as a diagnostic and prognostic marker for colorectal cancer? Future Oncol. 2011;7:1125–8. doi: 10.2217/fon.11.92. [DOI] [PubMed] [Google Scholar]
- 28.Levin B, Lieberman DA, McFarland B, Andrews KS, Brooks D, Bond J, Dash C, Giardiello FM, Glick S, Johnson D, Johnson CD, Levin TR, et al. Screening and surveillance for the early detection of colorectal cancer and adenomatous polyps, 2008: a joint guideline from the American Cancer Society, the US Multi-Society Task Force on Colorectal Cancer, and the American College of Radiology. Gastroenterology. 2008;134:1570–95. doi: 10.1053/j.gastro.2008.02.002. [DOI] [PubMed] [Google Scholar]
- 29.Centers for Disease Control and Prevention Colorectal cancer screening rates: prevention and early detection: keys to reducing deaths. 2011;vol. 2011 [Google Scholar]
- 30.Langer RD, White E, Lewis CE, Kotchen JM, Hendrix SL, Trevisan M. The Women’s Health Initiative Observational Study: baseline characteristics of participants and reliability of baseline measures. Ann Epidemiol. 2003;13:S107–21. doi: 10.1016/s1047-2797(03)00047-4. [DOI] [PubMed] [Google Scholar]
- 31.Design of the Women’s Health Initiative clinical trial and observational study. The Women’s Health Initiative Study Group. Control Clin Trials. 1998;19:61–109. doi: 10.1016/s0197-2456(97)00078-0. [DOI] [PubMed] [Google Scholar]
- 32.Curb JD, McTiernan A, Heckbert SR, Kooperberg C, Stanford J, Nevitt M, Johnson KC, Proulx-Burns L, Pastore L, Criqui M, Daugherty S. Outcomes ascertainment and adjudication methods in the Women’s Health Initiative. Ann Epidemiol. 2003;13:S122–8. doi: 10.1016/s1047-2797(03)00048-6. [DOI] [PubMed] [Google Scholar]
- 33.Poole S, Walker D, Gaines Das RE, Gallimore JR, Pepys MB. The first international standard for serum amyloid A protein (SAA). Evaluation in an international collaborative study. J Immunol Methods. 1998;214:1–10. doi: 10.1016/s0022-1759(98)00057-x. [DOI] [PubMed] [Google Scholar]
- 34.Manley PN, Ancsin JB, Kisilevsky R. Rapid recycling of cholesterol: the joint biologic role of C-reactive protein and serum amyloid A. Med Hypotheses. 2006;66:784–92. doi: 10.1016/j.mehy.2005.10.018. [DOI] [PubMed] [Google Scholar]
- 35.Schultz DR, Arnold PI. Properties of four acute phase proteins: C-reactive protein, serum amyloid A protein, alpha 1-acid glycoprotein, and fibrinogen. Semin Arthritis Rheum. 1990;20:129–47. doi: 10.1016/0049-0172(90)90055-k. [DOI] [PubMed] [Google Scholar]
- 36.Malle E, Sodin-Semrl S, Kovacevic A. Serum amyloid A: an acute-phase protein involved in tumour pathogenesis. Cell Mol Life Sci. 2009;66:9–26. doi: 10.1007/s00018-008-8321-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37.Pine SR, Mechanic LE, Enewold L, Chaturvedi AK, Katki HA, Zheng YL, Bowman ED, Engels EA, Caporaso NE, Harris CC. Increased Levels of Circulating Interleukin 6, Interleukin 8, C-Reactive Protein, and Risk of Lung Cancer. J Natl Cancer Inst. 2011 doi: 10.1093/jnci/djr216. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.