The clinical effectiveness of different surveillance strategies to prevent colorectal cancer in people with intermediate-grade colorectal adenomas: a retrospective cohort analysis, and psychological and economic evaluations

Inclusion criteria

Patients with IR adenoma(s) and a baseline colonoscopy were eligible for inclusion in the study. Following the UK guideline, IR patients were defined as those with three or four small adenomas (of < 10 mm) or one or two adenomas, at least one of which was large (≥ 10 mm).

Exclusion criteria

Patients were excluded for having certain conditions if the condition increased their risk of CRC or could have led to an abnormal pattern of surveillance. Some diagnoses resulted in exclusion regardless of when they occurred, for example hereditary non-polyposis colorectal cancer (HNPCC), a genetic condition that confers an increased risk of cancer throughout an individual’s lifetime. Other conditions resulted in exclusion only if they were diagnosed at, or prior to, baseline, or, in other cases, patients were censored after diagnosis of a particular condition rather than excluded altogether.

Patients were excluded if they had any of the following diagnoses at, or prior to, baseline:

• CRC or inflammatory bowel disease (IBD)

• resection/anastomosis

• volvulus.

Patients were excluded if they had the any of the following diagnoses at any time:

• family history of familial adenomatous polyposis (FAP)

• HNPCC

• Cowden syndrome

• juvenile or hamartomatous polyps.

Patients with polyposis could be excluded depending on polyposis type and time of diagnosis. Details of time-dependent exclusions for polyposis and colitis can be found later in the report (see Appendix 5).

Patients were also excluded if they had no baseline colonoscopy, or had one or more procedures without a date, or had more than 40 endoscopic procedures recorded.

Data extraction

Linking endoscopy and pathology data

Patients identified from endoscopy records were matched to their pathology records using a combination of hospital number, name and date of birth. Patient study numbers were then assigned to the matched pathology records. Manual inspection of the data and preliminary analyses were performed at the hospital to check that a sufficient number of pathology records were linked to a patient and that they occurred on, or near, the date of an endoscopy. When there was cause for concern (e.g. very few endoscopies linked to pathology reports; or endoscopies at which a biopsy was taken did not have an associated pathology report; or a large number of pathology reports could not be linked to an endoscopy, suggesting that the endoscopy extract did not retrieve all records), further investigations were undertaken and the data were re-extracted from the endoscopy and pathology systems where necessary.

Polyp numbering

A polyp found at one endoscopy examination that was not removed or only partially removed could be seen again at a later examination. To ensure that there was no double-counting of polyps, each polyp was assigned a unique polyp number that could be used to link sightings of the same polyp at different examinations. This process was called ‘polyp numbering’.

In approximately 17,000 patients, polyps were found on at least two occasions and were reviewed for manual polyp numbering. All sightings of an individual polyp were assigned the same unique polyp number. Each polyp was also assigned a match probability (to the nearest 10%), to indicate the degree of certainty that two polyps were the same lesion. The polyp that appeared to have the greatest number of matches with a high degree of certainty was chosen as a reference polyp, and all possible matches were considered in relation to this polyp. Polyp numbering guidelines were used to match polyps accurately and methodically, using all of the available information from the endoscopy and pathology reports. Particular attention was given to the following factors, listed in order of importance. Sightings at different examinations were considered more likely to be the same polyp if:

1. they occurred in the same segment of the colon, or in adjacent segments

2. there was an indication that the polyp at the earlier examination was not removed or was only partially removed

3. the quality of bowel preparation at the first examination was poor, making it less likely that a lesion would be removed

4. the lesions had similar grades of dysplasia

5. the lesions were the same histological type

6. the lesions had similar degrees of villousness.

Quality checks were carried out by the study researchers, who manually reviewed and checked a random sample of records for which polyps had been numbered by other study researchers.

Polyps matched with an arbitrary probability of ≥ 70%, using the above criteria, were considered the same lesion. More details on polyp numbering can be found in Appendix 6.

Polyp groups

Sometimes endoscopy reports described groups of polyps using terms such as ‘several’, ‘many’ and ‘multiple’, rather than individual polyps. During manual coding, specific fields were used to record this information. Each group of polyps was recorded as a single record and populated with information such as site, shape and histology, where this was common to all polyps within the group. Descriptions of the size and number of polyps in the group (e.g. ‘tiny’, ‘multiple’) were recorded. Where information was given for an individual polyp within the group, a polyp record was created and linked to the group record. The whole group (and the individual polyps linked to it) was allocated a unique group number.

Patients with multiple polyps could have groups of polyps seen at more than one examination, and a group of polyps seen at a later examination could include some or all of the polyps seen at a previous examination. In order to link groups of polyps seen at more than one examination, a separate group linking number was assigned to each group of polyps. This task was completed after all polyp groups had been recorded for a patient. Groups of polyps seen at more than one examination were matched and a probability was assigned, indicating the study researcher’s certainty that groups of polyps seen at separate examinations were of the same group.

The records for groups of polyps were then expanded into individual polyp records so that they could be analysed. An estimate of the number of polyps in each group was deduced from a value coded for the approximate number where available; otherwise the average of the minimum and maximum number of polyps recorded by the endoscopist was used. Alternatively, a numeric value was estimated for each vague number description (e.g. ‘some’, ‘several’, ‘few’), taking the average value for all groups in which both the specific descriptor and a numeric value was reported; these values used to define the number of polyps in the such groups are shown in Table 3.

Additional information on the number of individual polyps seen at previous or subsequent examinations which were considered to be part of the same group was used to refine the estimate of the number of polyps in that group (see Appendix 6).

Once a final estimate had been derived for the total number of polyps in each group at each examination, a program was written to create individual polyp records. Where a polyp record was created based on the presence of a polyp at a previous or subsequent examination, the program assigned the same polyp number to the new polyp record, to show they were the same lesion.

Creating summary values for polyp characteristics

Most polyps were seen and removed at a single examination, and information about a polyp’s features was available from a single endoscopy and pathology report. Alternatively, a polyp might be seen at more than one examination with descriptive information contained in numerous endoscopy and pathology reports. In both of these scenarios, a single polyp characteristic might be coded for in multiple data fields. It was therefore necessary to create summary values for each lesion, taking into account information provided in reports on polyp characteristics at individual examinations and across examinations. However, the following issues had to be resolved first.

Size

Polyp size information was recorded in several fields on the database, as shown in Table 4.

Exact sizes (endoscopy or pathology size) were available for 65% of polyps (of all types, including adenomas) but 8% of polyps had a numeric size with a minor discrepancy, or a size range (minimum and maximum endoscopy size); both of these issues were resolved to give an accurate size. In only 6% of polyps was the size estimated based on a qualitative size description (endoscopy size descriptor). This does not account for other sightings of the same polyp, so the proportion without a precise, numerical size is likely to have been even smaller than this. These proportions relate to all patients for whom we had data, rather than just IR patients, as adenoma risk groups could not be discerned until summary values for size had been defined.

The ‘endoscopy size descriptor field’ was used in cases for which a ‘vague’, qualitative or approximate size description was given in the endoscopy report. A numerical value was derived for each size description by analysing reports in which both qualitative size descriptions and a precise numerical size were given. The median and interquartile range (IQR) were calculated for each numeric size field and cross-tabulated against associated categories of the endoscopy size descriptor field, as shown in Table 5.

The endoscopy size and minimum and maximum endoscopy sizes were combined using a hierarchy of rules to give a derived endoscopy size for each sighting of a polyp (see Appendices 7 and 8 for details). The numerical values assigned to the endoscopy size descriptor field were used as the derived endoscopy size descriptor. Most pathology reports provided a precise size, which was coded for each individual polyp biopsied or resected at an examination – this was taken as the derived pathology size. Derived endoscopy and pathology sizes were automatically assigned when possible. Study researchers manually reviewed polyps for which derived endoscopy and pathology sizes could not be assigned automatically.

Finally, the three derived polyp sizes – derived endoscopy size, derived endoscopy size descriptor and derived pathology size – were compared across examinations within a visit, and the largest of each derived size was identified. The largest derived sizes were compared and the largest of these was used as the summary polyp size. The only time the largest size was not used was if it was the derived endoscopy size descriptor, and the derived endoscopy and derived pathology size was also available, which were considered more accurate. Full details of these methods are provided in Appendices 7 and 8.

Histopathology

In all patients for whom data were collected, including low-, intermediate- and high-risk patients, histological data were available for 66% of polyps (all types of polyps, including adenomas). In some cases (34%), data on histological features of a polyp were missing because no biopsies were taken, a pathology report could not be identified at the hospital, or the polyp in question was not retrieved at endoscopy or not mentioned in the pathology report. This value does not account for other sightings of polyps – they may have been removed at another examination – and we would expect some of these polyps to have been insignificant and therefore not excised. Rules were applied to the data to resolve such issues and derive polyp histology, where possible. First, if a polyp had any degree of villousness or dysplasia coded then the polyp was assumed to be an adenoma. If the polyp was ≥ 10 mm in size and no histology was recorded at any sighting of the polyp, the histology was set to ‘specimen not seen’ or ‘not able to diagnose’. If the polyp without histology was ≥ 10 mm in size and the patient had at least one adenoma recorded then the polyp was then assumed to be an adenoma.

A polyp seen at more than one examination may not have been diagnosed as an adenoma until a later sighting. As baseline started from first sighting of an adenoma, it was necessary to apply adenomatous histology back to earlier sightings, provided that the sighting without histology occurred no more than 3 years prior to the adenoma diagnosis. Adenomatous histology was applied to earlier sightings of a polyp only if the histology for the earlier sighting was unknown or recorded as hyperplastic, granulation tissue, previous polypectomy site, normal mucosa, not possible to diagnose, or specimen not seen; this ensured that histology of greater severity than an adenoma was not overwritten.

A single polyp seen at more than one examination could have different histological features recorded at each sighting. To resolve these inconsistencies, histological types encountered in the study were split into two groups: group 1 consisted of the outcomes of interest (CRCs and adenomas), along with all histological types that could potentially occur in such lesions over time (Table 6); group 2 consisted of all other histological types (data not presented). Group 1 histological types were listed from most to least severe within the following groups – CRC, possible CRC, benign lesion, no polyp features/not possible to diagnose – as shown in Table 6. When there was no clear-cut order in terms of malignant potential, histological types were arbitrarily ordered by the specificity of the description. Initially, polyps with histology from groups 1 and 2 recorded at different sightings were reviewed to check whether or not there was a reporting or coding error. Then, for remaining polyps with histology from both groups, group 1 histology took precedence for the purpose of this study, except when the group 1 histology was uncertain or unimportant (e.g. ‘normal mucosa’, ‘granulation tissue’, ‘previous polypectomy site’, ‘not possible to diagnose’ or ‘specimen not seen’), in which case the group 2 histology took precedence.

The histology of adenomas was further defined using their greatest degree of villousness and worst dysplasia recorded within a visit.

Polyp location

The following rules were used to define a value for polyp location across all visits:

1. Where the segment was recorded at a surgical procedure, this took precedence over any segment recorded at other types of procedure.

2. If there was no surgical procedure, the most frequently described segment was taken.

3. If no segment was mentioned more frequently than another, the most distal segment was taken.

4. In cases where a segment range was given, the following rules were applied:

   • If only one range was described, the most proximal and distal segments were recorded on the database as the true range (proximal defined as descending colon to terminal ileum; distal defined as anus to sigmoid colon).

   • If several site ranges were described, the smallest segment range was used as the true range, provided that the difference in the position of the most proximal and distal segments in the range was ≤ 2. Table 7 was used to allocate a position to each segment in order to calculate this difference. If the segment range differed by more than two, the records were manually reviewed to reach a decision.

Polyp shape

It was unclear if the most appropriate method for assigning the true shape of a polyp would be to use an order of precedence, as with other polyp characteristics, or if the first description might be the most accurate, as the shape of a polyp may have been altered once it was biopsied/resected. Shape values included flat, sessile, pedunculated or subpedunculated. It was decided that the first recorded shape of a lesion would be used.

Procedure date and order

In most cases, the procedure date was simply the date of the endoscopy. However, if the endoscopy report was not available, the pathology report was used to derive the examination date. Up to three dates might be specified on the pathology report. The examination date was derived using the following order of precedence:

1. date that the biopsy specimen was taken

2. date that the biopsy specimen was received at the laboratory

3. date of the pathologist’s report.

In the rare cases when it was not possible to derive a procedure date, the patient was excluded from the study. Where procedures occurred on the same day, the reasons were specified and the examinations were numbered to assign an order, otherwise it was specified why it was not possible to do so.

Procedure type

The master database contained two types of procedural report: endoscopy reports extracted directly from endoscopy databases and pathology-based procedure reports generated using clinical and procedural information from the pathology report. The latter were created by study researchers in cases when no endoscopy report was available.

In cases where the procedure type was not reported or not specified (e.g. ‘endoscopy’), procedure type was derived by applying a hierarchy of rules based on available information. For example, when a procedure type was unknown, yet there was evidence that the transverse colon or beyond was reached, the procedure type was probably a colonoscopy. When information such as bowel preparation and depth of insertion was given, the procedure was probably a colonoscopy or flexible sigmoidoscopy (FS). Likewise, if a lesion with a size of ≥ 10 mm was removed, or multiple adenomas were removed, the procedure was also probably a colonoscopy or FS. Full details of rules for deriving procedure type are given in Appendix 7.

For some patients, it remained uncertain whether or not they had a baseline colonoscopy even after procedure type was derived (i.e. derived procedure type was ‘colonoscopy or FS’ at baseline). As patients had to have a baseline colonoscopy for inclusion in the study (a baseline colonoscopy was necessary to accurately stratify patients into risk groups), procedures that were derived as ‘colonoscopy or FS’ were reclassified as colonoscopies, based on adenoma risk group and type/timing of follow-up examinations. For example, patients with a derived procedure type of ‘colonoscopy or FS’ at baseline who were classified as IR or high risk (see Defining adenoma surveillance risk groups, below) were assumed to have had a colonoscopy at some point during baseline, and so the derived procedure was relabelled as such (see Appendix 7). Unlike baseline examinations, no derived procedure types were relabelled at follow-up examinations. Instead, for each follow-up visit, the most complete whole-colon examination available was defined using a hierarchy from ‘complete colonoscopy’ to ‘unknown procedure type’.

For patients without a baseline colonoscopy who had a colonoscopy at follow-up visit 1 (FUV1), the baseline visit was shifted so that FUV1 became the baseline visit and the original baseline visit became a ‘prior’ visit. To ensure that risk was not underestimated as a result of shifting baseline in this way, any adenomas found at prior examinations (original baseline) were used to determine risk as well as those found during the baseline visit.

Colonoscopy quality

Where there were several colonoscopies within a visit, the most complete examination and the best bowel preparation achieved at any colonoscopy was taken as the highest quality examination achieved at that visit. The quality and completeness of a colonoscopy was assessed, based on the segment of the colon reached, the most proximal polyp site, the quality of bowel cleansing prior to the examination and whether or not the examination was marked as incomplete.

The quality of the colonoscopy was important for defining visits (see Defining baseline and surveillance visits, below) as well as being a potential risk factor in the final data analysis.

Baseline visit

The baseline visit included the examination with the first adenoma sighting and any completion examinations that occurred within the subsequent 11 months. For high-risk adenomas, surveillance examinations are scheduled 1 year after the initial examination, in accordance with UK surveillance guidelines, so 11 months was chosen as the most appropriate time frame to capture any completion examinations into the baseline visit, without including high-risk follow-up examinations. After including all examinations within 11 months, a small proportion of patients had additional procedures that occurred shortly after the ‘latest’ baseline examination and thus needed to be included into the baseline visit. Baseline was therefore extended a second time, to include any examinations within 6 months of the latest baseline examination. Finally, in a handful of special scenarios, a third repeated extension was performed to capture examinations within 6 or 9 months of the latest baseline examination (6 months if the latest baseline examination was a colonoscopy and 9 months if it was a sigmoidoscopy). These rare cases included scenarios for which:

• the latest baseline examination was incomplete

• quality of bowel preparation at the latest baseline examination was poor

• a large polyp (≥ 15 mm) was seen at the latest baseline examination

• the same polyp was seen at the latest baseline examination and the next examination, which occurred within 6/9 months

• the latest baseline examination was followed directly by a surgical examination.

After the extension of baseline, the length of baseline was assessed; only 2% of patients with IR adenomas had a baseline that exceeded 11 months in length.

Surveillance visits

A surveillance or follow-up visit was defined using similar rules for baseline. A follow-up visit comprised the first examination after baseline (or after a follow-up visit) and any further examinations within the subsequent 11 months. As with the baseline visit, the final examination in a follow-up visit was identified, and the follow-up visit was extended as necessary, using the same criteria as for the extension of baseline. This procedure was repeated until all examinations had been grouped into a follow-up visit. Visits following a diagnosis of CRC, volvulus or resection/anastomosis were censored, as patient follow-up would be affected by such diagnoses.

Surveillance interval

Surveillance intervals were timed from the last most complete examination of one visit to the first examination of the next visit, as defined in the NHS BCSP. 40

List cleaning

The patient-linking-file that was left at each hospital by the study programmer inevitably contained some patient identifiers that had been entered incorrectly into the hospital databases. It was therefore necessary to use the HSCIC/NHSCR’s list cleaning and tracing service and NSS’s linking service to validate and link the patient records to their database.

When the data sets were sent to HSCIC/NHSCR, no match was found for 5% of the patients. This revealed a limitation of having missing information, in that there was a higher chance of the supplied information matching more than one patient on the HSCIC database, resulting in rejection of a match. The study programmer worked closely with HSCIC to create bespoke matching algorithms that accounted for minor differences in dates of birth, names and NHS numbers in order to get the correct match, and, in some cases, additional data were collected from hospital to resolve the differences. Ultimately, matches were found for 99.65% of all 253,798 patients by the HSCIC/NHSCR and NSS.

Duplicate patient records

The national data repositories provided a list of duplicate patients found across the cohort (including patients from England/Wales and Scotland). When all of the duplicates had been identified, each set of duplicate records on our master database were merged into one record and an audit log was kept to show which records had been merged.

Cancer matching

Cancer and mortality (deaths) data for patients in our cohort were obtained from national patient data repositories (HSCIC, NHSCR Scotland and NSS). These data had to be added to the master database, taking into account the patient and cancer data already present, to ensure that there was no duplicated or missing data. This process was termed ‘cancer matching’.

To identify duplicate records of cancers, a program was written to identify CRCs in the national repositories’ data set and link them with the procedures and individual polyp records (including cancers) on the master database. Data quality checks were carried out, and samples of records that had been linked automatically were manually reviewed.

Cancers were linked to individual polyp records based on a hierarchy involving the cancer diagnosis date from the external source, the date the polyp or cancer was identified in the hospital data, the location of lesions, the polyp number, the time between the date of cancer diagnosis, and the date of the procedure during which the lesion was identified. For cancers reported in hospital pathology reports but not in national repositories, the hospital data were accepted as conclusive evidence of cancer, except when the histology was recorded by the study researcher as ‘cancer in dispute’ or ‘cancer query’.

The histology for cancers recorded on the study database as ‘in situ’ cancers and ‘cancers in dispute’ was compared with data from the national registries and automatically reclassified if necessary, using a hierarchy of rules. For example, polyps mapped to an in situ cancer from external sources were reclassified as ‘assume adenoma’ with high-grade dysplasia (HGD) if they were not already coded as such. Similarly, polyps in the database not mapped to a cancer from external sources, but with a histology recorded as ‘cancer in dispute’, were reclassified as ‘assume adenoma’ with HGD. A full list of the rules is given in Appendix 7 (see rule 13).

Values for the cancer diagnosis date, and site of the cancer, were assigned by comparing the data recorded on the study database with data from the national registries and applying a hierarchy of rules to arrive at the true value. For example, if the external cancer date preceded the mapped endoscopy date then the external date was used. Likewise for site, if no site was given in the mapped endoscopy data (or the site was non-specific), the site used in the external cancer data was used. A full list of the rules is given in Appendix 7 (see rule 11).

Outcomes

The primary outcome measures were adenoma, AA and CRC detected at the first and second follow-up visits, and CRC incidence after baseline, and after first follow-up. Previously seen lesions were excluded from some analyses, as they were thought to be a proxy measure for patients undergoing polypectomy site surveillance, and confounded the analysis. Outcomes that had not been seen at a previous visit were termed ‘new’ outcomes (see Chapter 3, New and previously seen lesions at first follow-up).

Advanced adenoma was defined as an adenoma of ≥ 10 mm, or with villous or tubulovillous histology, or HGD. CRCs were ascertained using pathological data recorded on the study database and International Statistical Classification of Diseases and Related Health Problems (ICD) codes in data from national repositories. To determine which cancers from the national repositories were outcomes of interest, they were grouped according to site and morphology (details are given in Appendix 7, rules 11 and 13). Only cancers from national repositories that fell into the site groups ‘malignant lesions of the colon/rectum’ and certain ‘in situ neoplasm – colon’ were selected for the study. Specifically, outcomes included adenocarcinomas of the colorectum and carcinomas with unspecified morphology located between the rectum and caecum that were assumed to be adenocarcinomas. Cancers with unspecified morphology located at sites related to the anus were likely to be squamous cell carcinomas and were therefore not classed as outcomes unless they were linked to a rectal lesion, in which case they were assumed to be adenocarcinomas. CRCs reported as a cause of death in national repositories were classed as outcomes if the patient did not have cancer recorded in the cancer registry or hospital data.

Colorectal cancer sites were defined by the World Health Organization (WHO) ICD versions ICD-8, ICD-9 and ICD-10, and included site codes C18–C20 (www.who.int/classifications/icd/en/). Morphology of colorectal neoplasia was coded with the Manual of Tumor Nomenclature and Coding codes,41 the WHO International Classification of Diseases for Oncology (ICD-O) ICD-O-1 codes42 and ICD-O-2 codes. 43

Exposures

The main exposures of interest were the length of the surveillance interval between baseline and first follow-up, and between the first and second follow-ups. The surveillance interval was defined as the period of time from the last most complete colonic examination at one visit to the first examination of the next visit (as in the NHS BCSP). 40 In order to define interval, a patient’s examinations were split into baseline and follow-up visits (see Defining baseline and surveillance visits, above). Interval length was then calculated and converted into a categorical variable with seven groups: > 18 months, 2, 3, 4, 5 and 6 years (all ± 6 months) and ≥ 6.5 years. Patients with the shortest interval were used as a reference group to compare with those who were exposed to a longer interval.

The other exposure of interest was the effect of adenoma surveillance on risk of CRC after baseline. Patients who attended at least one follow-up visit at which cancer was not diagnosed were considered to be exposed to surveillance.

Risk factors and potential confounders

Patient, procedural and polyp characteristics at baseline and follow-up were assessed as a priori risk factors and confounders; these included age and gender, examination quality (based on completeness of examination, quality of bowel preparation and difficulties encountered), calendar year of examination and hospital attended, and the number, size, location and histology of polyps and adenomas, villousness and dysplasia. All potential risk factors and confounders examined are listed and defined in Table 8.

Grouping of variables

All of the aforementioned risk factors were considered separately for the baseline visit and FUV1. In some instances it was necessary to add an additional level to a variable; for example, at FUV1 some patients did not have any adenomas or a colonoscopy, whereas at baseline every individual had an adenoma and a colonoscopy. The quantitative variables interval length and calendar year were grouped into categorical variables for some analyses and used in their continuous form in other circumstances. The remaining quantitative variables (visit length, age, adenoma size, number of examinations, number of sightings of a unique adenoma and numbers of specific polyp types) were grouped into categorical variables. Standard categorisations were created for all categorical variables and these were used in the presentation of univariable results. When appropriate, the process of selecting risk factors for inclusion in multivariable models involved the investigation of the categorisation of some variables, and the final categorisation was selected by evaluating the difference in effect between levels of the variable. When data were missing for a particular variable, an ‘unknown’ category was created in order to avoid losing patients from the models, particularly those models adjusting for several confounders. Models were tested with, and without including, the ‘unknown’ category to assess the difference it made.

Follow-up visit 1 findings in relation to baseline findings

Initially, findings at FUV1 were investigated, considering any adenomas, AAs or CRCs, with a focus on AA and CRC outcomes. The relationship between baseline risk factors and findings at FUV1 was modelled using univariable logistic regression to estimate unadjusted odds ratios (OR). The association between interval length and baseline risk factors was evaluated using chi-squared tests. The relationship between interval from baseline to FUV1 and outcomes at FUV1 was explored both with and without adjustment for baseline risk factors using logistic regression models. Many risk factors for AA and CRC that were potential confounders were known already, based on the substantial body of evidence in the literature. 15,22,23 Owing to the large number of potential confounders, backwards stepwise logistic regression models and likelihood ratio tests (LRTs) were used to identify important confounders to be included in the models, with the significance level for inclusion set at 5%. Interval, our main variable of interest, was constrained to be included in all models. Models were also constructed to consider only ‘new’ outcomes, meaning that those lesions had not been previously seen before FUV1. Separate models for all outcomes were constructed for interval considered as a continuous variable and as a categorical variable. Effect modification of the association between interval and new findings at FUV1 by age and gender were investigated by fitting models with interaction parameters and performing a test for interaction; effect modification was investigated for only interval as a continuous variable, as this enabled examination of potential trends, and it was unlikely to be of any practical use to know whether or not the effect of interval was significantly different in a particular age group if there was no trend in the effect.

Risk factors associated with an interval of < 2 years were identified using logistic regression, and a backwards stepwise logistic regression model was used to identify independent predictors of an interval of < 2 years. All p-values from models were calculated using LRTs.

Follow-up visit 2 findings in relation to baseline and follow-up visit 1 findings

A similar approach to the analysis of outcomes at FUV1 was adopted for outcomes at follow-up visit 2 (FUV2). The relationships between FUV1 risk factors and AA and CRC at FUV2, and between baseline risk factors and AA and CRC at FUV2, were modelled using univariable logistic regression for each confounder separately. Owing to the small number of CRCs detected at FUV2, AA and CRC were grouped together and the outcome of interest was advanced neoplasia (AN). The relationship between interval from FUV1 to FUV2 and detection of AN at FUV2 was explored both with and without adjustment for FUV1 risk factors, baseline risk factors (including interval from baseline to FUV1) and cumulative baseline and FUV1 risk factors using logistic regression models. Backwards stepwise logistic regression models and LRTs were used to identify important confounders to be included in the models, with the significance level for inclusion set at 5%. The chosen confounders from each of these models were then added to a stepwise model to identify the most important factors. To compare the model fit of each of the constructed logistic regression models, pseudo R-squared values and the Akaike information criterion (AIC) were calculated. As before, our main variable of interest (interval to FUV2) was constrained to be included in all models. The complete model selection process was performed separately for interval considered as a continuous variable and as a categorical variable. All models considered only ‘new’ outcomes, that is lesions that had not been previously seen before FUV2. Effect modification of the association between continuous interval and new AN at FUV2 by age and gender was investigated by fitting models with interaction parameters and performing a test for interaction.

Colorectal cancer incidence after baseline

In the analysis of CRC incidence after baseline, for patients matched to national sources the cut-off for follow-up was either 31 December 2011 or 30 June 2012 (depending on the data source), and for unmatched patients it was the date of the patient’s last recorded procedure. All time-to-event data were censored at first CRC diagnosis, death, emigration or end of follow-up.

For the analysis of incidence following baseline, time at risk started from the latest most complete colonoscopy in baseline, and for the analysis of incidence following FUV1, time at risk started on the date of the first procedure in FUV1. If CRC was diagnosed at a follow-up visit, the follow-up visit was not included as a visit, as it did not offer any protection against CRC. Incident CRC outcomes included ‘new’ CRCs only, that is cancers arising in lesions that had not been seen at baseline.

‘One minus the Kaplan–Meier estimator of the survival function’ was used to illustrate the time to cancer diagnosis and to estimate the cumulative risk of cancer with 95% confidence intervals (CIs) at 3, 5 and 10 years. The effects of surveillance and patient, procedural and polyp characteristics at baseline and follow-up on long-term CRC incidence were examined using Cox proportional hazards models. Univariable models were used to estimate unadjusted hazard ratios (HRs). Independent predictors of cancer incidence were identified in a multivariable Cox proportional hazards model, using backward stepwise selection with a p-value of < 0.05 in the LRT to determine the retention of variables in the final model. The number of follow-up visits was included as a time-varying covariate and, as our main variable of interest, was constrained to be included in all adjusted models. Effect modification of the association between surveillance and long-term CRC risk by age and gender was investigated by fitting models with interaction parameters and performing a test for interaction.

For the analysis of risk after baseline, only baseline risk factors were considered. For the analysis of risk following FUV1, separate models were built, considering baseline factors only, FUV1 factors only and cumulative factors only. The risk factors identified from these models were then considered together and a final model selected. All p-values from models were calculated using LRTs.

The incidence of CRC was compared with that expected in the general population. Observed pys at risk were calculated by gender and 5-year age group. Expected numbers of CRC cases were calculated by multiplying the observed gender- and age-specific number of pys by the gender- and age-specific incidence in the general population of England in 2007. The ratio of observed to expected cases was reported as a standardised incidence ratio (SIR), and 95% CIs were computed assuming an exact Poisson distribution.

Sensitivity analyses and internal validation

We conducted several sensitivity analyses to investigate whether or not our methods were robust and did not introduce bias into the results. To assess the methods we used to define baseline, follow-up visits and interval, we restricted analyses of the effect of interval on the finding of new AA and CRC at FUV1 and the effect of surveillance on long-term CRC incidence after baseline: first, to patients with only one colonoscopy in baseline, and, second, to patients who had at least one complete colonoscopy at FUV1. To examine whether or not the definition of AA that was used had an impact on results, we performed a sensitivity analysis for the outcome of new AA detection at FUV1 with a definition of AA that excluded villous or tubulovillous histology, that is with AA defined as an adenoma with HGD or with a size of ≥ 10 mm. Finally, we conducted sensitivity analyses of the effect of surveillance on long-term CRC incidence when the cohort was restricted to patients who had at least 5 years and at least 7 years of time in which hospital data had been collected; this was to examine the possible effect of misclassification of attendance at follow-up visits on the estimated effect of surveillance.

To assess the predictive ability of the multivariable logistic models for the outcomes of new findings at follow-up and the multivariable Cox regression models for the analysis of long-term cancer incidence, we performed internal validation using k-fold cross-validation with k = 10. 49 For each model, the linear predictors were used to construct receiver operating characteristic (ROC) curves for each of the 10 validation sets, and the area under the ROC curve and its SE were calculated for each; the inverse variance weighted mean ROC curve and area below the curve were then calculated from these.

Examinations and findings

Table 13 shows the proportion of patients found to have adenomas (all types), AA and CRC at FUV1 according to interval from baseline. Overall, 1605 (35%) patients had adenomas, 723 (16%) had AA and 84 (2%) had CRC detected at FUV1. The proportion of patients with adenomas was relatively constant across different intervals and ranged from 34% to 40%, whereas the proportion of patients with AA showed more variation, ranging from 14% to 26%, and the proportion with CRC ranged from 0.5% to 5%. The proportion of patients with CRC detected at FUV1 tended to increase with increasing interval to FUV1.

Table 14 describes examinations undertaken during FUV1. For most patients, FUV1 comprised a single examination (88%) and in 72% of patients the most complete examination was a complete colonoscopy.

Baseline risk factors for findings at first follow-up

Using univariable analyses, we investigated the crude associations of baseline demographic, procedural, adenoma and polyp characteristics with findings at FUV1 in order to identify risk factors for adenomas, AA and CRC and to assess potential confounders of the association between interval and outcomes.

Demographic and procedural characteristics

Table 15 details the crude effect of baseline demographic and procedural characteristics on the odds of having adenomas (all types), AA or CRC found at FUV1.

Adenoma and polyp characteristics

Table 16 describes the crude relationship between characteristics of adenomas and polyps detected at baseline and adenomas, AA and CRC at FUV1.

Baseline risk factors and interval

We explored the relationship between baseline risk factors and length of the interval between baseline and FUV1 to assess whether or not any factors could be acting as confounders of the association between findings at FUV1 and interval (Tables 17 and 18).

All factors were highly significantly associated with interval at the 1% level except for gender (p = 0.462), family history of cancer (p = 0.067), a difficult examination (p = 0.150), large hyperplastic polyps (p = 0.645), number of polyps with unknown histology (p = 0.586), distal adenomas (p = 0.353) and distal polyps (p = 0.105). Results for non-significant factors are not presented here.

Patients of an older age, with an incomplete colonoscopy, poor bowel preparation, a large adenoma (≥ 20 mm), an adenoma with villous histology or HGD, a proximal adenoma or polyp, or multiple sightings of a unique adenoma at baseline tended to have a shorter interval. As all of these features were also associated with increased odds of finding an adenoma, AA or CRC at FUV1, they could potentially be confounding the association between findings at FUV1 and interval.

Effects of interval on findings at follow-up visit 1

Baseline risk factors for a short interval

Unexpectedly, little evidence of an association was found between interval and detection of adenomas or AA at FUV1, even after adjusting for a number of covariates. As a large proportion of patients returned sooner than expected for their first follow-up, crude and adjusted estimates of the effect of baseline characteristics on interval length were calculated to allow a more detailed examination of baseline predictors of a short interval. An arbitrary cut-off of 2 years from baseline was used to classify patients as having a short interval, as this was the median interval length to FUV1 in the hospital cohort. A logistic regression model was used and factors that were not significant in the model at the 95% level were not included in the final model, and were therefore not adjusted for. Table 22 shows baseline risk factors for a short interval.

Age was significantly associated with a short interval (p < 0.0001), before and after adjustment for confounding, with a tendency towards an increasing odds of a short interval with increasing age. After adjustment, there was a 6% greater odds of a short interval per year increase in the calendar year of the baseline visit (OR 1.06, 95% CI 1.04 to 1.08) and odds also increased for patients with multiple sightings of a single adenoma (p < 0.0003). Conversely, patients without a complete colonoscopy at baseline were significantly less likely to return early, possibly as a result of the experience of a difficult examination (OR 0.71, 95% CI 0.61 to 0.82). Patients with a longer baseline visit were less likely to have a short surveillance interval; however, most 95% CIs included 1 so it was not possible to discern a real effect (p < 0.0001); these results may be affected by adjustment for multiple sightings of an adenoma, as before adjustment there was a positive association between length of baseline and a short interval. Having a large adenoma (≥ 10 mm), an adenoma with HGD or a proximal polyp were also risk factors for a short interval.

The independent predictors of a short interval were also identified as risk factors for finding an adenoma, AA or CRC at FUV1. However, adjustment for these factors made little difference to the effect estimates for interval, and did not reveal an association between interval and adenoma (only associated when interval was modelled as a continuous variable) or AA at FUV1. One possibility is that an unmeasured confounder closely linked to a factor(s) associated with the outcome and exposure may have increased the risk of a short interval and of having adenomas, AA or CRC at FUV1. This would cause an exaggerated effect of a short interval on risk, resulting in a diminished effect of interval length overall. Multiple sightings of a single adenoma at baseline was identified as a strong risk factor for a short interval and for finding an adenoma or AA at FUV1, so it is possible that this factor was acting as a proxy measure for an important, unmeasured confounder. This possibility is explored in detail in the next section.

New and previously seen lesions at first follow-up

As described in the previous section, we hypothesised that an unmeasured confounder was masking the association between interval and the detection of adenoma, AA or CRC at FUV1. It was possible that a proportion of individuals had a short interval because they were undergoing polypectomy site surveillance. Such patients would have a large adenoma, probably seen multiple times during baseline for repeated treatment, and possibly with advanced features such as HGD. Polypectomy site surveillance would be carried out to check the site of a large lesion that might not have been completely removed at baseline, rather than to check for the occurrence of newly developed lesions or lesions missed at baseline (possibly because of a poor-quality examination). The UK Adenoma Surveillance guideline16 assumes that all detected lesions are removed at baseline before surveillance begins, and includes recommendations for the treatment and surveillance of incompletely removed lesions. Such patients may require repeated treatment over a number of examinations in order to achieve complete removal and are then expected to return for a further examination(s) to check the polyp site.

We hypothesised that patients undergoing polypectomy site surveillance would be more likely not only to return for follow-up sooner, but also to have a finding detected at FUV1 – the lesion under polypectomy site surveillance. This could potentially confound the relationship between interval and detection of an adenoma or AA at FUV1. Although difficult to recognise such cases from a retrospective series, it was thought that lesions detected at FUV1 which were previously seen at baseline (i.e. the same lesion) were more likely to have been found as a result of polypectomy site surveillance. The distribution of new and previously seen outcomes by interval was examined to determine whether or not this was likely to be the case.

Tables 23–25 show a breakdown of IR patients by interval length and outcome status. Patients were stratified into four groups: (1) those with no findings at FUV1; (2) those who have only a previously seen finding; (3) those with both previously seen and new findings; and (4) those who have only a new finding. The number of patients within each stratum was then assessed to determine whether or not it was appropriate to exclude previously seen findings from the analyses.

After stratifying patients by interval and outcome status, increasing interval length was associated with increased detection of new findings. Patients with a shorter interval had a greater proportion of previously seen lesions detected than those with a longer interval. No such trend was seen among the ‘new and previously seen’ findings group, although there were only a small number of patients in this group: 2% with adenomas, 1% with AA and < 1% with CRC.

Previously seen lesions detected at the first follow-up were most likely to represent lesions undergoing polypectomy site surveillance when found in patients with a short interval between baseline and follow-up. As interval length increased, it became less certain whether or not this was the case. Logistic regression was performed using any findings (see Tables 19–21) and then using only new findings at FUV1 (Tables 26–30), having removed all previously seen findings.

All previously seen lesions were removed regardless of the interval length, rather than just those detected in patients with a short interval to FUV1, in order to avoid the introduction of bias into the data set. If only previously seen lesions in patients with short interval were removed from the analysis then this could artificially increase the odds of an outcome among patients with a longer surveillance interval, which would overestimate the effect of interval.

Effect of interval on new findings at first follow-up

After removal of previously seen lesions to adjust for the confounding effect of polypectomy site surveillance, the association of interval with new findings at the first follow-up was examined using univariable and multivariable analyses.

Effect modification of the association between interval and new findings at follow-up visit 1

We proposed that there might be an interaction between interval and age or gender. We investigated interactions with interval to follow-up only as a continuous variable, as these results were more intuitive and enabled the examination of potential trends.

There was no evidence of effect modification by age group or gender on new adenomas (Figure 3). There was some evidence of effect modification for the finding of new AA at FUV1 (Figure 4). By age group, the test for interaction was highly significant (p = 0.0100), although there was no clear trend in the ORs. Increasing the interval had the greatest effect in the < 55 years age group but the decrease in effect was not monotonic (Figure 4). To test for a trend in the ORs, an interaction was fitted between interval and continuous age group; the p-value was 0.8987. Thus, the effect of interval differed between the categorical age groups, but there was no trend in the effect with increasing age group. By gender, the ORs suggested that increasing interval had a stronger effect in men than in women, but this difference was not statistically significant (p = 0.0663). There was no evidence of effect modification on new CRC (Figure 5).

FIGURE 3.

Effect of a 1-year increase in interval on the detection of new adenoma at FUV1 by age group and gender. a, ORs adjusted for the other covariates included in model 2 in Table 28.

FIGURE 4.

Effect of a 1-year increase in interval on the detection of new AA at FUV1 by age group and gender. a, ORs adjusted for the other covariates included in model 2 in Table 29.

FIGURE 5.

Effect of a 1-year increase in interval on the detection of new CRC at FUV1 by age group and gender. a, ORs adjusted for the other covariates included in model 2 in Table 30.

Although we detected a significant interaction between interval and age group, we did not model the interaction parameter in previously presented results, as it is likely to be impractical to offer different surveillance strategies based on age or gender in a clinical setting.

Characteristics and findings

Of the 4608 patients who attended FUV1, 1635 (36%) patients returned for FUV2 during our data collection period and were not censored for cancer diagnosed at first follow-up.

Table 31 details the findings (new and previously seen) at FUV2 according to the interval between FUV1 and FUV2. Adenomas were detected in 527 (32%) patients, AA in 232 (14%) patients and CRC in 17 (1%) patients. The adenoma detection rate was high regardless of interval, varying from 30% to 43%, whereas the proportion of patients with AA varied from 8% to 20%, and the proportion with CRC varied from none to 3%. There was little evidence of a trend in findings with increasing interval for any of the outcomes.

Table 32 shows the examinations undertaken at FUV2. In 89% of patients, FUV2 comprised a single procedure and was completed in 1 day. The most complete examination that we were able to glean from information provided on procedure type and polyp location was a complete colonoscopy in 74% of cases, and an incomplete colonoscopy in 15%. A further 5% are likely to have had a colonoscopy, as this is the most common procedure to offer patients undergoing surveillance in the UK, but 6% had only a FS.

New and previously seen lesions at second follow-up

Tables 33–35 show the status of findings at FUV2 – whether or not a lesion had been seen at a previous visit – stratified by the interval from FUV1 to FUV2. Similar to findings at FUV1, there was a trend towards an increasing proportion of new findings in patients with a longer interval, and a greater proportion of previously seen lesions in those with a shorter interval.

Based on these observations, all subsequent analyses of findings at FUV2 included only new findings, so as to allow the association between interval to FUV2 and finding at FUV2 to be examined without any confounding effects of polypectomy site surveillance, as was done in the analysis of new findings at FUV1.

The proportion of patients with new adenomas was high at both the first and second follow-ups, regardless of interval length. The high detection rate of adenomas meant that this outcome was not informative in terms of identifying an optimum surveillance strategy. For this reason, adenomas were not considered as an end point in subsequent analyses for FUV2, and only AA or CRC were used as outcomes.

Follow-up visit 1 risk factors for new advanced adenomas and colorectal cancer at follow-up visit 2

Univariable analyses were performed to assess the relationship between FUV1 characteristics and detection of new AA and CRC at FUV2. Table 36 describes new AA and CRC incidence at FUV2 according to patient characteristics and examinations at FUV1. Most patient or procedural characteristics were not significantly predictive. There was weak evidence that suboptimal bowel preparation increased the odds of new AA (p = 0.0178), but again 95% CIs included 1. There was some evidence of an association between new CRC at FUV2 and a difficult examination at FUV1 (OR 5.99, 95% CI 1.22 to 29.35; p = 0.0636).

Table 37 describes new AA and new CRC incidence at FUV2 according to characteristics of adenomas and polyps detected at FUV1. There was a tendency towards increasing odds of new AA at FUV2 with increasing number and size of adenomas, severity of histology and proximal location of adenomas at FUV1, as well as in the presence of proximal polyps or polyps of unknown histology. Odds of new AA tended to increase with repeated sightings of an adenoma during FUV1 but the association was not significant (p = 0.0609). No significant relationship was found between new CRC at FUV2 and characteristics of adenomas or polyps seen at FUV1, a finding that was most likely due to the very small number of CRC outcomes at FUV2.