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The United Kingdom has lower survival figures for all types of cancers compared to many European countries despite similar national expenditures on health. This discrepancy may be linked to long diagnostic and treatment delays.
The aim of this study was to determine whether delays experienced by patients with colorectal cancer (CRC) affect their survival.
This observational study utilized the Somerset Cancer Register to identify patients with CRC who were diagnosed on the basis of positive histology findings. The effects of diagnostic and treatment delays and their subdivisions on outcomes were investigated using Cox proportional hazards regression. Kaplan-Meier plots were used to illustrate group differences.
A total of 648 patients (375 males, 57.9% males) were included in this study. We found that neither diagnostic delay nor treatment delay had an effect on the overall survival in patients with CRC (χ23=1.5,
Diagnostic and treatment delays had no effect on the survival of this cohort of patients with CRC. The utility of the 2-week wait referral system is therefore questioned. Timely screening with subsequent early referral and access to diagnostics may have a more beneficial effect.
Colorectal cancer (CRC) is the second most common cause of cancer-related deaths in the United Kingdom, and it accounted for 42,000 cases of cancer diagnoses in 2018 [
Although surgery with curative intent is the preferred treatment modality for CRC [
Thomson and Forman [
Previous studies have shown mixed results, while some studies have found no association [
Data were obtained from the Somerset Cancer Register, which is a database that collects wait times and outcomes data in line with the national database requirements [
A total of 5456 patients were investigated for CRC. Patients not diagnosed with CRC were excluded (n=4386). To ensure database validity, the patients’ sources of referral were examined. Of the excluded patients, 4118 (93.9%) patients within the first exclusion were referred through the 2-week wait pathway. In the United Kingdom, a 2-week wait referral is an urgent referral made by a patient’s general practitioner, wherein the patient should be seen within a 14-day period by a secondary care specialist. Such a referral should be made when a patient presents with symptoms that may indicate cancer. Of the 4118 patients with CRC, 246 were diagnosed through the 2-week wait pathway, representing a 5.9% conversion rate. This is in line with the 5.4% conversion rate that was reported for bowel cancer observed at the national level [
Patients with comorbid conditions of the gastrointestinal tract were excluded. This included patients with metastases from other primary cancers (n=11) or benign neoplasms (n=75). Patients with metastasis to the gastrointestinal tract may experience shorter diagnostic delays as a result of heightened physiological disturbance and yet exhibit worse outcomes [
Patient groups that were not diagnosed with colorectal cancer following a positive histology finding of a primary colorectal tumor (n=160).
Category of patients excluded | Patients, n (%) |
A clinical diagnosis alone (patient symptomatology + a radiological investigation) | 138 (86.2) |
Diagnosis made after a positive serological tumor marker result | 1 (0.6) |
Unknown basis of diagnosis | 1 (0.6) |
Patients with an unrecorded basis of diagnosis | 20 (12.5) |
The algorithm used for patient inclusion. CRC: colorectal cancer; GI, gastrointestinal.
This was a multicenter population-based observational study. When assessing survival, other studies have demonstrated different trends based on the cancer type [
Patients included from the national bowel cancer screening program (n=92) were particularly susceptible to lead time bias. This bias occurs when outcomes are measured following diagnoses that reflect different starting points along the natural history of a cancer [
Patients receiving treatment for their CRCs were necessarily alive between receiving a diagnosis and initiating treatment. This period is described as an immortal time, wherein the study outcome cannot occur [
The effect of health care provider delay on survival was investigated. Survival was measured until death or censoring. Patients were censored at the last known live follow-up or at the end of the study period if no record of a follow-up is available; however, they were not recorded as deceased.
Delays were categorized into diagnostic and treatment delays. Delays and their subdivisions were analyzed separately as each delay type represents a discrete segment of the patient pathway [
Representation of the delays and delay subdivisions considered for the analysis. T1: diagnostic delay; T1a: delay from referral based on symptoms to receipt of referral; T1b: referral delay; T1c: delay between hospital appointment and diagnosis; T2: treatment delay; T2a: delay between diagnosis and multidisciplinary team (MDT) meeting date; T2b: considered for those patients who received a surgical intervention; Ttotal: total delay from referral to surgery or treatment.
The covariates considered in this study were related to the patient demographics, including age, gender, and ethnicity. The data of the location, histology, grade, and stage of the tumor were also included. Patient performance status, which reflects the functional status of the patients [
The median and IQR were calculated for diagnostic, referral, and treatment delays along with the delay quartiles. A survival analysis was conducted for all the delays and their subdivisions. Kaplan-Meier survival estimates were plotted for diagnostic and treatment delays by quartile. Group differences were analyzed using the log-rank test. The Cox proportional hazards regression analysis was used to investigate the effect of the covariates and to adjust for the confounding factors. To ensure the result validity, multiple sensitivity analyses were performed. Although deaths are regularly reported to the registry, diagnostic and treatment delay analyses were repeated for patients with a known live follow-up or death date. Next, all models were stratified by cancer stage, as stage may act as an intermediate factor between diagnostic delay and survival and it drives treatment regimens [
Of the 648 eligible patients, 375 were males (57.9%) and 272 were females (41.9%). Gender was not recorded for 1 patient (0.1%). The mean age was 69 years (range 29-96 years; 95% CI 67.8-70.2). There were 243 (37.5%) cases of rectal cancer and 405 (62.5%) cases of colon cancers. Of the 243 patients with rectal cancer, 30 (12.3%) died. Among the 405 patients with colon cancer, 38 (9.4%) died. The mean follow-up period for the patients with a known live follow-up was 383 days (95% CI 276.76-399.2). Patient characteristics are summarized in
Patient characteristics by cancer type (N=648).
Patient characteristics | Colon cancer cohort (N=405), n (%) | Rectal cancer cohort (N=243), n (%) | |
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|||
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≤60 | 92 (22.7) | 53 (21.8) |
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61-65 | 52 (12.8) | 32 (13.2) |
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66-70 | 52 (12.8) | 48 (19.8) |
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71-75 | 57 (14.1) | 46 (18.9) |
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76-80 | 65 (16.0) | 30 (12.3) |
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81-84 | 51 (12.6) | 12 (4.9) |
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≥85 | 36 (8.8) | 22 (9.1) |
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Male | 229 (56.6) | 146 (60.1) |
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Female | 176 (43.4) | 96 (39.5) |
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Unknown gender | 0 (0) | 1 (0.4) |
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Caucasian | 173 (42.7) | 104 (42.8) |
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Black | 25 (6.2) | 8 (3.3) |
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Asian | 20 (4.9) | 8 (3.3) |
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Mixed | 2 (0.5) | 2 (0.8) |
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Other | 41 (10.1) | 26 (10.7) |
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Unknown | 144 (35.5) | 95 (39.1) |
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Proximal colon | 169 (41.7) | N/Ab |
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Transverse colon | 39 (9.6) | N/A |
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Distal colon | 186 (45.9) | N/A |
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Unspecified colon | 11 (2.7) | N/A |
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Rectosigmoid junction | N/A | 31 (12.8) |
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Rectum | N/A | 212 (87.2) |
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I | 60 (14.8) | 44 (18.1) |
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II | 65 (16.0) | 43 (17.7) |
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III | 159 (39.3) | 94 (38.7) |
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IV | 73 (18.0) | 36 (14.8) |
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Unknown | 48 (11.9) | 26 (10.7) |
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Adenocarcinoma | 364 (89.9) | 208 (85.6) |
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Mucinous adenocarcinoma | 16 (4.0) | 7 (2.9) |
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Signet ring cell carcinoma | 2 (0.5) | 0 (0) |
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Neuroendocrine tumor | 4 (1.0) | 3 (1.2) |
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Liposarcoma | 1 (0.2) | 0 (0) |
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Other carcinoma | 11 (2.7) | 14 (5.8) |
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Unknown histology | 7 (1.7) | 11 (4.5) |
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Well differentiated (G1) | 7 (1.7) | 3 (1.2) |
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Moderately differentiated (G2) | 264 (65.2) | 162 (66.6) |
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Poorly differentiated (G3) | 87 (21.5) | 41 (16.9) |
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Anaplastic (G4) | 1 (0.2) | 1 (0.4) |
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Cannot be assessed (GX) | 6 (1.5) | 5 (2.1) |
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Unknown differentiation | 40 (9.9) | 31 (12.8) |
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Active monitoring | 4 (1.0) | 10 (0.4) |
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Chemotherapy | 71 (17.5) | 56 (23.0) |
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Palliative care | 15 (3.7) | 7 (2.9) |
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Surgery | 292 (72.1) | 140 (57.6) |
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Radiotherapy | 2 (0.5) | 21 (8.6) |
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Unknown treatment | 21 (5.2) | 18 (7.4) |
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Adjuvant | 21 (5.2) | 7 (2.9) |
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Curative | 268 (66.2) | 128 (52.6) |
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Diagnostic | 6 (1.5) | 5 (2.1) |
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Monitoring | 4 (1.0) | 1 (0.4) |
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Neoadjuvant | 6 (1.5) | 7 (2.9) |
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Palliative | 30 (7.4) | 25 (10.3) |
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Radical/curative | 3 (0.7) | 17 (7.0) |
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Unknown | 67 (16.5) | 53 (21.8) |
aProximal colorectal cancers are defined as cancers arising from the caecum up to and including the splenic flexure [
bNot applicable.
cDukes’ staging was reconciled with the TNM staging system as follows [
Diagnostic delays were calculated for 361 (89.1%) of the 405 patients with colon cancer and 216 (88.8%) of the 243 patients with rectal cancer. The median diagnostic delay was 34 days for both cancers (IQR 19-59 and 22-63 days, respectively). An analysis of the relationship between the cancer stage and diagnostic delay was performed. Diagnostic delays were right skewed and not normally distributed following the Kolmogorov-Smirnov test (
Referral delay was calculated for 390 (96.3%) of the 405 patients with colon cancer and 238 (97.9%) of the 243 patients with rectal cancer. The median referral delay was 10 days (IQR 4-15 days) for patients with colon cancer and 11 days (IQR 6-16 days) for patients with rectal cancer. The majority of the patients with colon cancer (285/390, 73.1%) and rectal cancer (172/238, 72.3%) experienced a referral delay of less than 2 weeks. However, 13.1% (51/390) of the patients with colon cancer and 13.4% (32/238) of the patients with rectal cancer experienced a referral delay of at least one month.
Treatment delays were calculated for 327 (80.1%) of the 405 patients with colon cancer and 208 (85.6%) of the 243 patients with rectal cancer. The median treatment delay was 31 days (IQR 19-55 days) for patients with colon cancer and 42 days (IQR 27-106 days) for patients with rectal cancer. In all, 16.5% (54/327) of the patients with colon cancer and 11.5% (24/208) of the patients with rectal cancer experienced a treatment delay of <2 weeks. The majority of the patients with colon and rectal cancer experienced a treatment delay of ≥4 weeks (168/327, 51.4% and 142/208, 68.3%, respectively). Treatment delays displayed a similar skewness to diagnostic delays and were not significantly associated with cancer stage in either patients with colon or patients with rectal cancer (
The log-rank test indicated no difference between long-term survival and diagnostic delay quartile (
Kaplan-Meier plot illustrating the survival function by diagnostic delay quartile with time.
Kaplan-Meier plot illustrating the survival function by treatment delay quartile with time.
The relationship between diagnostic delay and survival in rectal cancer appears nonsignificant in the log-rank test (
Kaplan-Meier plot illustrating the survival function by diagnostic delay quartile with time.
Kaplan-Meier plot illustrating the survival function by treatment delay quartile with time.
In the analysis of total delay, treatment modality, intent, and setting were not included as covariates. Total delays were not significantly related to survival in either patients with colon cancer (
Patient numbers and significance values for total delay, referral delay, and delay subdivision analyses.
Delay | Patients with colon cancer (N=405) | Patients with rectal cancer (N=243) | ||
|
Patients, n (%) | Patients, n (%) | ||
T1aa | 399 (98.5) | .12 | 243 (100) | .64 |
T1b (referral delay)b | 390 (96.3) | .74 | 237 (97.5) | .25 |
T1cc | 344 (84.9) | .29 | 213 (87.6) | .048 |
T2ad | 298 (73.5) | .56 | 187 (76.9) | .25 |
T2b (surgical patients only)e | 237 (58.5) | .89 | 128 (52.7) | .69 |
Ttotal (total delay)f | 375 (92.6) | .75 | 222 (91.3) | .35 |
aDelay between referral for symptoms and receipt of the referral by the hospital.
bDelay between referral based on symptoms and date of hospital appointment (referral delay).
cDelay between date of hospital appointment and date of diagnosis.
dDelay between date of diagnosis and multidisciplinary meeting date.
eDelay between date of diagnosis and admission for surgery.
fDelay between referral based on symptoms and date of the first surgical procedure or treatment (total delay).
There was good concordance between all models except for the effect of diagnostic delays on survival in patients with rectal cancer. A borderline result was obtained when censored patients were excluded (
Results of the sensitivity analyses.
Types of sensitivity analyses and delays | Patients with colon cancer ( |
Patients with rectal cancer ( |
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Diagnostic delay | .10 | .05 |
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Treatment delay | .09 | .34 |
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Diagnostic delay | .24 | .01a |
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Treatment delay | .12 | .72 |
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Diagnostic delay | .64 | .03b |
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Treatment delay | .70 | .58 |
aThe statistically significant relationship between diagnostic delay and survival in the rectal cancer cohort remained consistent when stratifying by cancer stage, where the first quartile group was significantly less likely to die than the fourth quartile group (hazard ratio 0.141, 95% CI 0.034-0.590;
bWhen excluding tumor grade and stage, patients with the shortest delays were significantly less likely to die than those with the longest delays (hazard ratio 0.165, 95% CI 0.044-0.616,
This observational study investigated the relationship between health care provider delays and survival of patients with CRC. The median diagnostic delays were 34 days for both cancer types, while the median treatment delays for the patients with colon cancer and rectal cancer were 31 and 42 days, respectively. Contrary to the stated hypothesis, the health care provider delays had no effect on survival in this cohort.
Although longer diagnostic delays were associated with worse survival in the rectal cancer cohort, this relationship was statistically nonsignificant when restricting the analysis to patients with a known follow-up date or date of death. Further, although it is necessary to censor the patients who emigrate, are lost to follow-up, or for whom no date of death is recorded but who have not yet had a follow-up appointment, the nonsignificant result in this model may indicate that a disproportionately greater number of patients with shorter diagnostic delays were censored in the initial analysis. Considering this limitation, any conclusion regarding diagnostic delays in the rectal cancer cohort should be made tentatively.
Nonetheless, analysis of the delay subdivisions indicated that the delay between the first hospital appointment and diagnosis significantly affects survival. This may suggest that the effect on outcomes is due to unmeasured confounders relating to the nature of a patient’s diagnostic pathway. For example, frail patients may receive a computed tomography colonoscopy prior to an endoscopic procedure. These patients could experience longer diagnostic delays but are more likely to die. Future research should therefore adjust for the nature of the diagnostic testing performed, as this may confound the diagnostic interval and survival, thereby creating a spurious positive correlation between diagnostic delay and risk of death [
Previous studies have shown longer diagnostic delays in patients with colon cancer [
Risk of death increases for each stepwise progression in the cancer stage [
Previous literature has produced mixed results regarding the association between diagnostic delay and tumor stage. Ramos et al [
The paucity of evidence for a relationship between delay and survival in this study supports the results of previously published studies [
There have also been various approaches to data analysis in this field. In a general practitioner–based study of 268 patients, a Danish group treated diagnostic delay as a continuous variable and conducted a restricted cubic spline regression analysis. This analysis revealed that patients who experienced >5 weeks of delay had a greater risk of death [
A subsequent study of 958 patients with CRC by Murchie et al [
Such conflicting results indicate that the relationship between health care provider delay and survival of patients with CRC remains uncertain [
Few studies have explored the effect of delays on postoperative outcomes such as readmission or complication rates. Psychosocial factors such as quality of life and anxiety are seldom assessed. Such outcomes should increasingly become the focus of future research.
Timeliness and quality are not necessarily congruent and expediting the care of patients may be detrimental in certain circumstances. For example, McConnell et al [
The Kaplan-Meier and Cox regression methods assume that censoring is independent of a patient’s risk of death. This may not have been the case, given the change in the significance between diagnostic delay and survival in the sensitivity analysis, which excluded censored patients. This suggests that the initial model underestimated the survival of patients with the shortest delays. However, others utilizing this technique have found the opposite, with censored patients being less likely to die, and therefore may have overestimated mortality in their analyses [
It was not possible to consider the initial presenting symptoms in this study. However, rectal bleeding has been associated with both poor [
There were also limitations associated with utilizing registry data. First, an analysis of patient delay was not possible, which is defined as the time between a patient noticing symptoms and presenting these symptoms to the general practitioner. However, patient delay data is often accrued through interviews or questionnaires, making recall bias difficult to avoid [
Despite these limitations, this study has several strengths. Registry data was entered synchronously with clinical practice, making this analysis resilient to recall bias [
This observational study investigated the effect of health care delays on survival in patients with CRC. It is reasonable to conclude that the relatively short health care provider delays experienced by patients in the United Kingdom are not likely to affect the outcomes. Promoting effective screening programs should remain a high public health priority.
colorectal cancer
exponential distribution of the sojourn time
AA was involved in data acquisition, study design, statistical analysis, and write-up of this manuscript. CA was involved in data acquisition, preprocessing, and a full review of the work. PZ was involved in the study design and many of the research study’s conclusions.
None declared.