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Article

Adherence to Clinical Practice Guidelines and Colorectal Cancer Survival: A Retrospective High-Resolution Population-Based Study in Spain

by
Francisco Carrasco-Peña
1,
Eloisa Bayo-Lozano
1,
Miguel Rodríguez-Barranco
2,3,4,
Dafina Petrova
2,3,4,*,
Rafael Marcos-Gragera
4,5,6,7,
Maria Carmen Carmona-Garcia
7,8,
Josep Maria Borras
9,10 and
Maria-José Sánchez
2,3,4,11
1
Radiation Oncology Department, University Hospital Virgen Macarena, 41009 Sevilla, Spain
2
Escuela Andaluza de Salud Pública, 18011 Granada, Spain
3
Instituto de Investigación Biosanitaria ibs.GRANADA, 18012 Granada, Spain
4
CIBER de Epidemiologia y Salud Pública (CIBERESP), 28029 Madrid, Spain
5
Medical Sciences Department, Faculty of Medicine, University of Girona (UdG), 17071 Girona, Spain
6
Epidemiology Unit and Girona Cancer Registry, Oncology Coordination Plan, Catalan Institute of Oncology, Department of Health, Government of Catalonia, 17007 Girona, Spain
7
Descriptive Epidemiology, Genetics and Cancer Prevention Group, Girona Biomedical Research Institute—IDIBGI, Salt, 17190 Girona, Spain
8
Medical Oncology Department, Catalan Institute of Oncology, University Hospital Dr Josep Trueta, 17007 Girona, Spain
9
Department of Clinical Sciences, IDIBELL, University of Barcelona, Hospitalet, 08908 Barcelona, Spain
10
Department of Health, Catalonian Cancer Strategy, Hospitalet, 08908 Barcelona, Spain
11
Department of Preventive Medicine and Public Health, University of Granada, 18010 Granada, Spain
*
Author to whom correspondence should be addressed.
Int. J. Environ. Res. Public Health 2020, 17(18), 6697; https://doi.org/10.3390/ijerph17186697
Submission received: 21 July 2020 / Revised: 6 September 2020 / Accepted: 9 September 2020 / Published: 14 September 2020
(This article belongs to the Special Issue Population Health and Health Services)

Abstract

:
Colorectal cancer (CRC) is the third most common cancer worldwide. Population-based, high-resolution studies are essential for the continuous evaluation and updating of diagnosis and treatment standards. This study aimed to assess adherence to clinical practice guidelines and investigate its relationship with survival. We conducted a retrospective high-resolution population-based study of 1050 incident CRC cases from the cancer registries of Granada and Girona, with a 5-year follow-up. We recorded clinical, diagnostic, and treatment-related information and assessed adherence to nine quality indicators of the relevant CRC guidelines. Overall adherence (on at least 75% of the indicators) significantly reduced the excess risk of death (RER) = 0.35 [95% confidence interval (CI) 0.28–0.45]. Analysis of the separate indicators showed that patients for whom complementary imaging tests were requested had better survival, RER = 0.58 [95% CI 0.46–0.73], as did patients with stage III colon cancer who underwent adjuvant chemotherapy, RER = 0.33, [95% CI 0.16–0.70]. Adherence to clinical practice guidelines can reduce the excess risk of dying from CRC by 65% [95% CI 55–72%]. Ordering complementary imagining tests that improve staging and treatment choice for all CRC patients and adjuvant chemotherapy for stage III colon cancer patients could be especially important. In contrast, controlled delays in starting some treatments appear not to decrease survival.

1. Introduction

Colorectal cancer (CRC) is the third most incident cancer worldwide in both sexes responsible for 10.2% of all cancer cases, after lung cancer (11.6%) and breast cancer (11.6%) [1]. According to the Spanish Network of Cancer Registries (REDECAN), in 2020 in Spain there will be 44,231 new CRC cases [2]. CRC will be the most frequent cancer considering both sexes and the second most frequent tumor after prostate cancer in men and breast cancer in women [2].
In relation to other European countries, in Spain CRC occupies an intermediate position in mortality. In particular, in 2018 15,167 people died from CRC, which was the second leading cause of death due to cancer in both sexes, representing 13.5% of cancer deaths in men and 13.7% of cancer deaths in women (www.mscbs.gob.es). In the European cancer registry-based study on survival and care of cancer patients (EUROCARE), for the period 2000–2007, CRC in Spain had an observed and relative 5-year-survival of 45.66% and 55.32%, respectively, in men and 47.62% and 55.01%, respectively, in women [3].
Research shows that two main factors influence CRC survival: the stage of the disease at the time of diagnosis and adherence to the relevant clinical practice guidelines regarding diagnosis and treatment. For instance, a key study by Allemani et al. [4] investigated why population-based CRC survival in the late 1990s was better in the United States compared to Europe, and concluded that the stage at diagnosis and adherence to clinical practice guidelines were the main causes of these differences. Similar conclusions were reached by Gatta et al. [5] in a study based on eleven European Cancer Registries.
Clinical practice guidelines define the recommended actions at each moment of the healthcare process based on the best scientific evidence available and thus reduce unwarranted variability in diagnostic testing and treatment. Population-based high-resolution studies, in which cancer registries systematically collect detailed clinical and pathological data beyond what is routinely recorded, are one of the best tools to examine how adherence to guidelines influences survival. In contrast to clinical studies which frequently exclude patients with advanced age, comorbidities, or lower socio-economic status, population-based studies include all patients in a given jurisdiction and are less prone to selection and referral biases [6]. This makes them an essential resource for the continuous evaluation and updating of diagnosis and treatment standards.
The aim of this study was to analyze the degree of adherence to clinical practice guidelines for CRC and investigate its relationship with survival in all incident CRC cases diagnosed in 2011 in two provinces in Spain. To our best knowledge, this is the first high-resolution population-based study to examine in detail adherence to CRC clinical practice guidelines in Spain.

2. Materials and Methods

We conducted a retrospective high-resolution population-based cohort study of all CRC cases (C18–C20 according to the 3rd edition of the International Classification of disease for Oncology, CIE-O-3 [7]), diagnosed during 2011 in persons older than 15 and residing in the provinces of Granada and Girona (Spain). The lower age limit was set at 15 to avoid distortions produced by the generally very low mortality in younger age groups. Granada and Girona were selected among the seven Spanish cancer registries participating in the European High-Resolution studies to represent Southern (Granada) and Northern (Girona) Spain and because they have similar population sizes, thereby contributing a similar number of CRC cases to the analysis.

2.1. Information Sources

The information was obtained from the Cancer Registries of Granada and Girona, which are both accredited by the International Agency for Research on Cancer (IARC). The registries record all cases of invasive cancer diagnosed for the first time in residents of the provinces of Granada and Girona, each with a population of about 920,000 and 760,000 inhabitants, respectively.
The information in both registries comes from public and private health centers in both provinces. The detection of cancer cases is based mostly on the information that comes from the Basic Minimum Data Set of hospital discharges (Conjunto Mínimo Básico de Datos, CMBD), and the Pathological Services. Other sources of information are the medical records provided by other hospital services in which cancer patients are diagnosed and/or treated.

2.2. Variables

Following the specific European High-Resolution Studies (http://www.hrstudies.eu/) protocols, trained cancer registries personnel accessed the clinical records of each case to confirm the CRC diagnosis and record sociodemographic, tumor characteristics, diagnostic, and treatment related data. The following variables were used:
Demographic and clinical variables. Sex, age at the time of diagnosis; date of incidence according to recommendations of the European Network of Cancer Registries (ENCR); the most valid method of diagnosis coded according to the ENCR (clinical, microscopic confirmation, imaging tests, biomarkers, autopsy); diagnostic modality (symptomatic, by screening); topography (anatomical site and subsite); tumor morphology (coded according to the International Classification of Diseases for Oncology (ICD-O)—3rd edition); degree of differentiation (I-well differentiated; II-moderately differentiated; III-poorly differentiated; IV-undifferentiated); stage at the time of diagnosis (clinical and post-surgical TNM, based on TNM Classification, 7th edition [8]); number of lymph nodes affected and number of lymph nodes examined; comorbidities based on the Charlson index [9]; and tobacco use (current smoker, ex-smoker, non-smoker).
Diagnostic examinations performed. We recorded whether the patients had undergone each of the following procedures: colonoscopy, barium enema, computed tomography, colonographic magnetic resonance imaging (MRI), extension preoperative study (liver, lung, brain, and bone with ultrasound, chest radiography, nuclear magnetic resonance (NMR), chest computed tomography (CT), echoendoscopy, abdominal CT).
Treatment-related variables. We recorded whether patients had undergone each of the following treatments (with type and mode): surgery, chemotherapy, radiotherapy, and targeted therapy.
Adherence to clinical practice guidelines. The relevant guidelines for both provinces were the Integrated Healthcare Process for Colorectal Cancer published by the Health Agency of Andalucía in 2011 [10] (for Granada) and the Onco-Guide of Colon and Rectum published in 2008 by the Health Department of the Catalan Government [11] (for Girona). Both documents define recommendations related to the diagnosis, treatment, and care of people diagnosed with CRC. In addition, both documents are based on international guidelines and offer similar recommendations. The quality indicators (QIs) used to measure adherence were those for which information was included in the European High-Resolution Studies protocols.
The specific QIs were the following: (QI1) whether the patient, following the CRC diagnosis, was assessed by the specific tumor commission before starting treatment; (QI2) whether the following complementary imaging tests were requested: colonoscopy, CT of the chest, abdomen and pelvis, and MRI of the pelvis; (QI3) whether the patient underwent surgery sooner than 30 days after the histological diagnosis; (QI4) whether the patient initiated neoadjuvant therapy (radiotherapy/chemotherapy or chemotherapy or radiotherapy) sooner than 30 days after the histological diagnosis; (QI5) whether the patient started adjuvant treatment sooner than 8 weeks after surgical treatment; (QI6) whether the patient underwent excision and analysis of at least 12 lymph nodes to allow for appropriate lymph node staging; (QI7) whether the patient, if diagnosed with a stage III colon carcinoma, underwent chemotherapy treatment; (QI8) whether the patient, if diagnosed with stage II or III carcinoma of the rectum underwent radiotherapy/chemotherapy or radiotherapy treatment with neoadjuvant or adjuvant intent; and (QI9) whether perioperative mortality occurred, defined as patient death in the first 30 days after surgical treatment.
We calculated adherence for each indicator (QI1 to QI9) and overall adherence which was defined as adherence on at least 75% of the indicators that apply to each patient.
Vital status. Patient follow-up was updated until 31 December 2016, based on the National Death Registry and the patients’ medical records, whereby cases reported only in the death certificate or identified by autopsy were excluded.

2.3. Statistical Analyses

We first describe the demographic and clinical characteristics of the sample using absolute and relative frequencies, also stratified as a function of tumor subsite: colon cancer (CC) or rectal cancer (RC). Significant differences in characteristics between subsites were contrasted by means of the Chi-Square test or the Fisher’s exact test (according to the fulfillment of the application conditions).
To analyze the relationship between adherence and survival, we calculated observed and net survival at 1, 3, and 5 years since the diagnosis of colorectal cancer and computed the relative excess risk of death (RER) as a function of adherence to the quality indicators. In particular, observed survival was calculated using the Kaplan–Meier method. Regarding net survival, to eliminate the possibility of death from other causes, this was calculated using the Pohar-Perme estimator [12], which represents the hypothetical survival that patients would have had if their cancer had been the only possible cause of death. For the calculation of the net survival, we used life tables and general mortality using the Elandt-Johnson method [13]. To estimate the RERs, we used generalized linear models with a Poisson error structure based on collapsed data using exact survival times in the net survival framework. RERs with 95% confidence intervals (CIs) were estimated by the studied factors using the maximum likelihood method.
Finally, we also performed analyses restricted to patients diagnosed with stage II or III disease because of the potentially stronger impact of the clinical guidelines in this group.
All statistical analyses were conducted in Stata v14 (StataCorp LP. 2015, College Station, TX, USA).

3. Results

A total of 1050 patients diagnosed with CRC (33.6% with RC and 66.4% with colon cancer CC) were included in the study. Table 1 shows patients’ characteristics at diagnosis, also as a function of tumor location. The majority of patients (60.9%) were men and aged above 65 (67.0%). Median age at diagnosis was 71 (interquartile range (IR): 54–88): 71 in men (IR: 54–88) and 72 in women (IR: 52–92). More than half of the patients (51.5%) presented at a late stage (TNM III or IV) (see Table 1).
The diagnostic exams and preoperative tests performed are listed in Table 2. Table 3 shows the treatments undergone for all CRC cases and as a function of location (CC or RC) and Tables S1 (CRC cases), S2 (CC cases), and S3 (RC cases) (Supplementary Material) show the combination of treatments administered.

3.1. Adherence to Clinical Practice Guidelines for Colorectal Cancer (CRC)

The adherence was calculated after excluding cases with missing data on each quality indicator. Overall adherence (defined as adherence on ≥75% of the indicators) was observed for 74.7% of the patients; for 19.5% of patients there was adherence on 50–74% of the indicators, and for 5.8% on ≤49% of the indicators.
The results for the separate indicators are shown in Table 4. Those with highest adherence were QI1, QI9, and QI6. In particular, 91.9% of CRC patients were evaluated by the specific tumor commission before staring treatment (QI1), 94.2% did not suffer perioperative mortality (QI9), and 74.6% had at least 12 lymph nodes excised and analyzed (QI6).
In contrast, the indicator with the worst adherence was QI4. In particular, only 34.9% of CRC patients started neoadjuvant therapy (radiotherapy/chemotherapy or chemotherapy or radiotherapy) sooner than 30 days after histological diagnosis (QI4). The mean and median number of days elapsed until neoadjuvant treatment start were 47 and 43, respectively (39 and 41 for CC and 48 and 44 for RC).
The rest of the indicators showed that for 62.0% of CRC patients the recommended complementary imaging tests were requested (QI2). Sixty-two percent underwent surgery sooner than 30 days after the histological diagnosis (QI3), with mean and median number of days elapsed until surgery of 36 and 26, respectively (33 and 20 for CC, and 45 and 37 for RC). Sixty-four percent of CRC patients started adjuvant treatment sooner than 8 weeks after surgical treatment (QI5). The mean and median number of days elapsed until adjuvant treatment start were 51 and 45, respectively (49 and 43 for CC and 59 and 56 for RC). Finally, 66.7% of patients diagnosed with a stage III CC underwent chemotherapy (QI7) and the percentage of RC patients with a diagnosis of stage II and III who underwent radiotherapy/chemotherapy or radiotherapy treatment with neoadjuvant or adjuvant intent was 73.4% (QI8).

3.2. Survival Analysis

Tables S4 (CRC cases), S5 (CC cancer), and S6 (RC cases) (Supplementary Material) show the observed and net survival of patients 1, 3, and 5 years after diagnosis as a function of demographic, clinical, and tumor characteristics. Stage at diagnosis was a strong determinant of survival (p-values ≤ 0.020). In particular, CRC patients diagnosed with Stage I disease had net survival of 95% at 1, 92% at 3, and 90% at 5 years after diagnosis. In contrast, patients diagnosed with stage IV disease had a net survival of only 50% at 1, 22% at 3, and 11% at 5 years after diagnosis (p < 0.001 for Stage I vs. Stage IV comparison). The same pattern was observed both for CC and RC cases separately (see Tables S5 and S6, respectively). Survival was also poorer in men compared to women (p = 0.015), in older compared to younger patients (p < 0.001 for “75+” vs. “<65”, and p = 0.012 for “65–74” vs. “<65” groups), and in patients with a higher comorbidity burden (p < 0.001 for high vs. no comorbidity and p = 0.034 for low vs. no comorbidity) (see Table S4).
Table 5 shows observed and net survival as a function of adherence to the QIs. Overall adherence (on ≥75% of indicators) reduced the excess risk of death by 65% (RER = 0.35, 95% CI 0.28–0.45, p < 0.001). This result was confirmed in an analysis restricted only to patients diagnosed with stage II or III disease (RER = 0.41, 95% CI 0.25–0.67. p < 0.001), suggesting almost 60% reduced excess risk of dying for cases where guidelines were followed (see Table S7). Considering the individual indicators, significant differences were observed on QI2, QI3, and QI7. In particular, patients for whom the recommended complementary imaging tests were requested (QI2) (RER = 0.58, 95% CI 0.46–0.73, p < 0.001) and patients diagnosed with a stage III CC who underwent chemotherapy (QI7) (RER = 0.33, 95% CI 0.16–0.70, p = 0.004) had a reduced excess risk of death. Patients who underwent surgery sooner than 30 days after the histological diagnosis had an increased excess risk of death (RER = 1.77, 95% CI 1.17–2.66, p = 0.007) but this difference was not significant when analysis was restricted to patients diagnosed in stages II and III (RER = 2.30, 95% CI 0.99–5.32, p = 0.053).

4. Discussion

This population-based study of patients diagnosed with primary invasive CRC during 2011 in two provinces (Granada and Girona) in Spain analyzed the adherence to clinical practice guidelines regarding diagnosis and treatment and the effect of adherence on survival up to five years after diagnosis. Results showed that overall adherence to the clinical practice guidelines (on ≥75% of indicators) improved survival, reducing excess risk of death by 60–65% (depending on whether all patients are considered or only those diagnosed in stages II and III, respectively). Detailed analyses of the separate indicators suggested that ordering complementary imagining tests that improve staging and treatment choice for all CRC patients and adjuvant chemotherapy for stage III colon cancer patients could improve survival. In contrast, controlled delays in starting some treatments appeared not to decrease survival.
Adherence to clinical practice guidelines for CRC has recently been examined in other countries including Canada [14] and The Netherlands [15]. In particular, a population-based study in a Canadian province examined adherence to adjuvant chemotherapy in patients with stage II or III colorectal cancer [14], whereas in The Netherlands a survey of medical oncologists examined adherence to clinical guidelines for systemic treatment for high-risk stage II and III colon and metastatic colorectal cancer [15]. However, these studies did not investigate the relationship between adherence and survival. Hence, the current study adds valuable information regarding the implications of a broad set of clinical guidelines for patient survival, using population-based data and including all patients in the selected regions, regardless of stage at diagnosis.
In the current study, more than half of patients were diagnosed at later stages (26.4% stage III and 25.1% stage IV). The observed distribution by stage was similar to that recorded by Minicozzi et al. [16] in an analysis of the differences in the stage and treatment of CRC in Italy and France, and in other publications [4,17,18]. Stage at diagnosis was strongly related to survival, in line with previous results by Gatta et al. [5], confirming stage at diagnosis as one of the strongest determinants of survival.
The analysis of adherence to clinical guidelines on the separate indicators showed significant improvement in survival only on two indicators (QI2 and QI7). In particular, considering the individual indicators, QI1 (assessment by the specific tumor commission before starting treatment) was not associated with survival, which could be due to the high adherence in the current study (91.9%), which is also higher than that reported in other studies (e.g., 70.1% in Munro et al. [19]).
Complementary imaging studies (colonoscopy, CT of the chest, abdomen and pelvis, and MRI of the pelvis) were requested for 62% of patients (QI2). These patients had better survival, in particular a 42% reduced excess risk of dying, compared to patients for whom no complementary imaging studies were requested. This result could be explained by the additional information provided by the complementary tests, which could have improved the staging of the lesion and helped improve the choice of treatment. This is supported by studies examining the role of CT of the chest, abdomen, and pelvis as part of an extended diagnostic examination or in studies evaluating the importance of pelvic MRI or colonoscopy in local staging, with repercussions for survival [20].
Regarding QI3, net survival was higher in the group of patients in whom the surgery was performed later than the established limit. This could be due to the proximity of the mean and median values observed in the sample (36 and 26, respectively) to the date established as the limit by the guidelines (30 days). Our study and previous findings corroborate that a controlled delay of the surgical treatment does not have an impact on survival [21]. The lack of effect of QI4 (starting neoadjuvant treatment sooner than 30 days after the histological diagnosis) suggests that also a controlled delay in starting neoadjuvant therapy may have no impact on survival.
Multiple studies have analyzed the delay in administering the first treatment and its impact on the risk of death from CRC without reaching definitive conclusions. While some studies establish a clear relationship between survival and delay greater than 30 days [22], others do not find a difference [23] and others find no differences in survival for a period of up to 34 weeks [24].
The percentage of patients who started adjuvant treatment sooner than 8 weeks after surgical treatment was 63.9% (QI5). The cut-off considered in the guidelines was 6 weeks, however, different studies and meta-analyses [25] have established 8 weeks as the time limit after which a delay in the start of chemotherapy would have an impact on survival, so we used 8 weeks as a criterion. However, in our study there were no significant differences in survival when the cut-off point was set at 6 or 8 weeks, nor when the analysis was restricted to patients in stages II and III when the benefit of chemotherapy is clearly established. Again, a possible explanation for the lack of significant differences may be the proximity of the mean and median waiting times in our study (51 and 45 days, respectively) to the cut-off established by the guidelines (56 days or 8 weeks).
Scientific evidence establishes that at least 12 lymph nodes must be sampled to perform adequate staging, considering it an independent prognostic factor and key in decision-making for patients who can benefit from adjuvant chemotherapy, especially those diagnosed with stage II and III CC [26]. This criterion was met for 74.6% of patients in the current study (QI6), who also had somewhat better survival. However, as was the case in other studies such as those by Berberoglu et al. [27], the difference was not significant.
QI7 showed that 66.7% of CC patients diagnosed with stage III disease underwent chemotherapy and this was associated with better survival in all scenarios analyzed, whereby the excess risk of death was reduced by 67%. Chemotherapy improves local control, disease-free survival [28], and global survival [29]. This is why systemic treatment should be a standard for this group of patients. However, in our study only 66.7% of patients underwent adjuvant treatment, a percentage that is still greater than that reported by other European [4] and North-American [14] cancer registries.
The relevant guidelines for our study population established that patients diagnosed with stage II or III RC should undergo radiotherapy/chemotherapy or radiotherapy treatment with neoadjuvant or adjuvant intent. The adherence to this recommendation was assessed by IQ8 at 73.4%, and patients who adhered to this indicator showed better survival. However, contrary to results published by Peng et al. [30], this difference was not significant.
The percentage of patients who died in the first 30 days after surgery was 5.8% (QI9), a result similar to that found in The Netherlands [31]. It is still above the average published by the Spanish Association of Surgeons, which is 1.8% [32]; however, their estimate was not based on population-based data and was not externally audited. Excluding urgent surgery (20% of cases) from the estimate resulted in 2.9% perioperative mortality (3.3% for CC and 2.3% for RC).
Overall, results published by other US and European registries regarding perioperative mortality vary between 2% and 6% [4]. Some of the factors that have an important influence on perioperative mortality are age and comorbidities as can be evidenced by the study of Chin-Chia et al. [33]. In this study patients who were older and had a higher Charlson comorbidity index had 106% higher risk of death, independent of sex, socioeconomic status, demographic region, and treatment modality (neoadjuvant or adjuvant). In our study, perioperative mortality was higher among older patients, patients with a higher Charlson comorbidities index, and patients who underwent neoadjuvant (vs. adjuvant) treatment (see Table S8).
A limitation of the current study was that it was based on data from two provinces only. However, this was the first population-based high-resolution study examining adherence to clinical practice guidelines for CRC and survival in Spain. In addition, comparing the results across provinces was not among the goals of the current study but it should be addressed in future research because regional differences in survival have been observed for other cancers [34]. It would be especially relevant to do this for the regions with highest incidence and mortality from colorectal cancer and further benchmark it with results from other countries. There is important variability in treatments administered both within and between countries, as is the case for radiotherapy [35,36,37] and chemotherapy [15].

5. Conclusions

Survival was strongly influenced by the stage at diagnosis and adherence to the clinical guidelines. The specific guidelines that showed significant differences were ordering complementary imaging tests and undergoing adjuvant chemotherapy treatment in the case of patients diagnosed with a stage III CC. In contrast, controlled delays in starting some treatments appeared not to decrease survival. Nevertheless, overall adherence (on ≥75% of the indicators) also showed improved CRC survival.

Supplementary Materials

The following are available online at https://www.mdpi.com/1660-4601/17/18/6697/s1. Table S1: Distribution of colorectal cancer patients according to the combination of treatments received; Table S2: Distribution of colon cancer patients according to the combination of treatments received; Table S3: Distribution of rectal cancer patients according to the combination of treatments received; Table S4: Observed and net survival of colorectal cancer patients at 1,3 and 5 years since diagnosis; Table S5: Observed and net survival of colon cancer patients at 1,3 and 5 years since diagnosis; Table S6: Observed and net survival of rectal cancer patients at 1,3 and 5 years since diagnosis; Table S7: Observed (OS) and net survival (NS) at 1,3 and 5 years since diagnosis of stage II/III colorectal cancer patients and relative excess risk of death (RER) as a function of adherence to the quality indicators (QIs); Table S8: Peri-operative mortality as a function of key patient and treatment characteristics.

Author Contributions

Conceptualization, E.B.-L. and M.-J.S..; methodology, M.R.-B., R.M.-G., M.C.C.-G., J.M.B., M.-J.S..; software, M.R.-B..; validation, D.P., J.M.B.; formal analysis, F.C.-P., E.B.-L., M.R.-B., M.-J.S.; investigation, F.C.-P., M.R.-B., R.M.-G., M.C.C.-G.; resources, R.M.-G., M.C.C.-G., M.-J.S.; data curation, M.R.-B., R.M.-G., M.C.C.-G.; writing—original draft preparation, F.C.-P., D.P.; writing—review and editing, F.C.-P., E.B.-L., M.R.-B., D.P., R.M.-G., M.C.C.-G., J.M.B., M.-J.S.; visualization, F.C.-P., M.R.-B.; supervision, E.B.-L., M.-J.S..; project administration, E.B.-L., M.-J.S.; funding acquisition, M.-J.S. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported in part by ERANET within the framework of the call on “Translational research on tertiary prevention in cancer patients” (TRANSCAN) with funding from the Spanish National Institute of Health Carlos III (grant number AC14/00036). Maria José Sánchez was also supported by the Andalusian Department of Health, Research, Development, and Innovation office project grant PI-0152/2017. The work conducted was part of HIGHCARE (High-resolution project on prognosis and care of cancer patients). The funding sources had no role in the study design, collection, analysis or interpretation of data, the writing of the report, or the decision to submit the article for publication.

Acknowledgments

We thank Pamela Minicozzi and Milena Sant for the development of the protocol and data collection tools for the European High-Resolution studies. This paper is part of the doctoral thesis of Francisco-Javier Carrasco-Peña, first author of the paper, in the context of the Inter-University Health Sciences Doctoral Program offered jointly by the University of Sevilla, the University of Jaén, and the Andalusian School of Public Health.

Conflicts of Interest

The authors declare that there are no conflict of interest regarding the publication of this article.

Compliance with Ethical Standards

This study involves a secondary data analysis from existing data and records. The information was recorded by the investigators in such a manner that subjects could not be identified, directly or through identifiers linked to the subjects. The participating cancer registries have data management policies in place allowing for the preservation of individual patients’ confidentiality including the ethical approvals from local mandatory bodies. For this type of study formal consent is not required.

References

  1. Bray, F.; Ferlay, J.; Soerjomataram, I.; Siegel, R.L.; Torre, L.A.; Jemal, A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA A Cancer J. Clin. 2018, 68, 394–424. [Google Scholar] [CrossRef] [Green Version]
  2. Estimaciones de la incidencia del cáncer en España, 2020. Red Española de Registros de Cáncer (REDECAN). 2020. Available online: https://redecan.org/redecan.org/es/Informe_incidencia_REDECAN_2020.pdf (accessed on 11 September 2020).
  3. Holleczek, B.; Rossi, S.; Domenic, A.; Innos, K.; Minicozzi, P.; Francisci, S.; Hackl, M.; Eisemann, N.; Brenner, H.; EUROCARE-5 Working Group. On-going improvement and persistent differences in the survival for patients with colon and rectum cancer across Europe 1999–2007—Results from the EUROCARE-5 study. Eur. J. Cancer 2015, 51, 2158–2168. [Google Scholar] [CrossRef]
  4. Allemani, C.; Rachet, B.; Weir, H.K.; Richardson, L.C.; Lepage, C.; Faivre, J.; Gatta, G.; Capocaccia, R.; Sant, M.; Baili, P.; et al. Colorectal cancer survival in the USA and Europe: A CONCORD high-resolution study. BMJ Open 2013, 3, e003055. [Google Scholar] [CrossRef] [Green Version]
  5. Gatta, G.; Capocaccia, R.; Sant, M.; Bell, C.M.J.; Coebergh, J.W.W.; Damhuis, R.A.M.; Faivre, J.; Martinez-Garcia, C.; Pawlega, J.; De Leon, M.P.; et al. Understanding variations in survival for colorectal cancer in Europe: A EUROCARE high resolution study. Gut 2000, 47, 533–538. [Google Scholar] [CrossRef] [Green Version]
  6. Booth, C.M.; Tannock, I.F. Randomised controlled trials and population-based observational research: Partners in the evolution of medical evidence. Br. J. Cancer 2014, 110, 551–555. [Google Scholar] [CrossRef] [Green Version]
  7. Allen, P.W. ICDO—International Classification of Diseases for Oncology. Pathology 1991, 23, 280. [Google Scholar] [CrossRef]
  8. Choi, S.Y.; Lim, B.; Han, J.H.; Kyung, Y.S.; An, D.H.; Kim, H.; Lee, W.; Chae, H.K.; Lee, J.; Choi, W.; et al. MP09-08 Percent Tumor Volume vs. The Subclassification of American Joint Committee on Cancer Staging System on Prediction of Biochemical Recurrence in Patients with Pathologic T2 Prostate Cancer. J. Urol. 2019, 201. [Google Scholar] [CrossRef] [Green Version]
  9. Charlson, M.E.; Pompei, P.; Ales, K.L.; MacKenzie, C. A new method of classifying prognostic comorbidity in longitudinal studies: Development and validation. J. Chronic Dis. 1987, 40, 373–383. [Google Scholar] [CrossRef]
  10. Junta de Andalucía. Consejería de Salud. CÁNCER colorrectal: Proceso asistencial integrado. 2ª ed. Sevilla: Consejería de Salud. 2011. Available online: https://www.juntadeandalucia.es/export/drupaljda/salud_5af1956e2d7f6_cancer_colorrectal_2e.pdf (accessed on 11 September 2020).
  11. Generalitat de Catalunya. Departament de Salut. OncoGuia de Còlon i recte. Actualització 2008. Departament de Salut. 2008. Available online: http://hospiolot.com/mitjans/serveis/cartera-serveis/consultes-externes/activitat-especialitzada/oncologia/Oncoguia-de-colon-i-recte.pdf (accessed on 11 September 2020).
  12. Perme, M.P.; Stare, J.; Estève, J. On Estimation in Relative Survival. Biometrics 2011, 68, 113–120. [Google Scholar] [CrossRef]
  13. Dickman, P.W.; Coviello, E. Estimating and Modeling Relative Survival. Stata J. Promot. Commun. Stat. Stata 2015, 15, 186–215. [Google Scholar] [CrossRef] [Green Version]
  14. Rayson, D.; Urquhart, R.; Cox, M.; Grunfeld, E.; Porter, G. Adherence to Clinical Practice Guidelines for Adjuvant Chemotherapy for Colorectal Cancer in a Canadian Province: A Population-Based Analysis. J. Oncol. Pract. 2012, 8, 253–259. [Google Scholar] [CrossRef] [Green Version]
  15. Keikes, L.; Van Oijen, M.G.H.; Lemmens, V.; Koopman, M.; Punt, C.J. Evaluation of Guideline Adherence in Colorectal Cancer Treatment in The Netherlands: A Survey Among Medical Oncologists by the Dutch Colorectal Cancer Group. Clin. Color. Cancer 2018, 17, 58–64. [Google Scholar] [CrossRef] [Green Version]
  16. Minicozzi, P.; Bouvier, A.-M.; Faivre, J.; Sant, M.; Velten, M.; Launoy, G.; Bouvier, V.; Faivre, J.; Bouvier, A.-M.; Woronoff, A.; et al. Management of rectal cancers in relation to treatment guidelines: A population-based study comparing Italian and French patients. Dig. Liver Dis. 2014, 46, 645–651. [Google Scholar] [CrossRef]
  17. Russo, A.G.; Andreano, A.; Sartore-Bianchi, A.; Mauri, G.; DeCarli, A.; Siena, S. Increased incidence of colon cancer among individuals younger than 50 years: A 17 years analysis from the cancer registry of the municipality of Milan, Italy. Cancer Epidemiol. 2019, 60, 134–140. [Google Scholar] [CrossRef]
  18. Ciccolallo, L.; Capocaccia, R.; Coleman, M.P.; Berrino, F.; Coebergh, J.W.W.; Damhuis, R.A.M.; Faivre, J.; Martinez-Garcia, C.; Møller, H.; De Leon, M.P.; et al. Survival differences between European and US patients with colorectal cancer: Role of stage at diagnosis and surgery. Gut 2005, 54, 268–273. [Google Scholar] [CrossRef] [Green Version]
  19. Munro, A.J.; Brown, M.; Niblock, P.G.; Steele, R.J.C.; Carey, F.A. Do Multidisciplinary Team (MDT) processes influence survival in patients with colorectal cancer? A population-based experience. BMC Cancer 2015, 15, 686. [Google Scholar] [CrossRef] [Green Version]
  20. Balyasnikova, S.; Brown, G. Optimal Imaging Strategies for Rectal Cancer Staging and Ongoing Management. Curr. Treat. Options Oncol. 2016, 17, 32. [Google Scholar] [CrossRef] [Green Version]
  21. Amri, R.; Bordeianou, L.G.; Sylla, P.; Berger, D.L. Treatment Delay in Surgically-Treated Colon Cancer: Does It Affect Outcomes? Ann. Surg. Oncol. 2014, 21, 3909–3916. [Google Scholar] [CrossRef]
  22. Lee, Y.-H.; Kung, P.-T.; Wang, Y.-H.; Kuo, W.-Y.; Kao, S.-L.; Tsai, W.-C. Effect of length of time from diagnosis to treatment on colorectal cancer survival: A population-based study. PLoS ONE 2019, 14, e0210465. [Google Scholar] [CrossRef] [Green Version]
  23. Ramos, M.; Esteva, M.; Cabeza, E.; Campillo, C.; Llobera, J.; Aguiló, A. Relationship of diagnostic and therapeutic delay with survival in colorectal cancer: A review. Eur. J. Cancer 2007, 43, 2467–2478. [Google Scholar] [CrossRef]
  24. Murchie, P.; A Raja, E.; Brewster, D.H.; Campbell, N.C.; Ritchie, L.D.; Robertson, R.; Samuel, L.; Gray, N.M.; Lee, A.J. Time from first presentation in primary care to treatment of symptomatic colorectal cancer: Effect on disease stage and survival. Br. J. Cancer 2014, 111, 461–469. [Google Scholar] [CrossRef]
  25. Des Guetz, G.; Nicolas, P.; Perret, G.Y.; Morere, J.F.; Uzzan, B. Does delaying adjuvant chemotherapy after curative surgery for colorectal cancer impair survival? A meta-analysis. Eur. J. Cancer 2010, 46, 1049–1055. [Google Scholar] [CrossRef]
  26. Sarli, L.; Bader, G.; Iusco, D.; Salvemini, C.; Di Mauro, D.; Mazzeo, A.; Regina, G.; Roncoroni, L. Number of lymph nodes examined and prognosis of TNM stage II colorectal cancer. Eur. J. Cancer 2005, 41, 272–279. [Google Scholar] [CrossRef]
  27. Berberoglu, U. Prognostic significance of total lymph node number in patients with T1-4N0M0 colorectal cancer. Hepatogastroenterology 2004, 51, 1689–1693. [Google Scholar]
  28. André, T.; De Gramont, A.; Vernerey, D.; Chibaudel, B.; Bonnetain, F.; Tijeras-Raballand, A.; Scriva, A.; Hickish, T.; Tabernero, J.; Van Laethem, J.L.; et al. Adjuvant Fluorouracil, Leucovorin, and Oxaliplatin in Stage II to III Colon Cancer: Updated 10-Year Survival and Outcomes According to BRAF Mutation and Mismatch Repair Status of the MOSAIC Study. J. Clin. Oncol. 2015, 33, 4176–4187. [Google Scholar] [CrossRef]
  29. André, T.; Boni, C.; Navarro, M.; Tabernero, J.; Hickish, T.; Topham, C.; Bonetti, A.; Clingan, P.; Bridgewater, J.; Rivera, F.; et al. Improved Overall Survival With Oxaliplatin, Fluorouracil, and Leucovorin As Adjuvant Treatment in Stage II or III Colon Cancer in the MOSAIC Trial. J. Clin. Oncol. 2009, 27, 3109–3116. [Google Scholar] [CrossRef] [Green Version]
  30. Peng, L.C.; Milsom, J.; Garrett, K.; Nandakumar, G.; Coplowitz, S.; Parashar, B.; Nori, D.; Chao, K.C.; Wernicke, A. Surveillance, Epidemiology, and End Results-based analysis of the impact of preoperative or postoperative radiotherapy on survival outcomes for T3N0 rectal cancer. Cancer Epidemiol. 2014, 38, 73–78. [Google Scholar] [CrossRef]
  31. Van Eeghen, E.E.; Boer, F.C.D.; Loffeld, R. Thirty days post-operative mortality after surgery for colorectal cancer: A descriptive study. J. Gastrointest. Oncol. 2015, 6, 613–617. [Google Scholar]
  32. Ortiz, H.; Biondo, S.; Codina, A.; Ciga, M.Á.; Enríquez-Navascués, J.M.; Espín, E.; Garcia-Granero, A.; Roig, J.V. Variabilidad interhospitalaria de la mortalidad postoperatoria en el proyecto del cáncer de recto de la Asociación Española de Cirujanos. La influencia del volumen quirúrgico. Cirugía Española 2016, 94, 22–30. [Google Scholar] [CrossRef]
  33. Wu, C.-C.; Hsu, T.-W.; Chang, C.-M.; Yu, C.-H.; Lee, C.-C. Age-Adjusted Charlson Comorbidity Index Scores as Predictor of Survival in Colorectal Cancer Patients Who Underwent Surgical Resection and Chemoradiation. Medicine 2015, 94, e431. [Google Scholar] [CrossRef]
  34. Rodriguez-Barranco, M.; Salamanca-Fernández, E.; Fajardo, M.L.; Bayo, E.; Chang-Chan, Y.-L.; Expósito, J.; García, C.; Tallón, J.; Minicozzi, P.; Sant, M.; et al. Patient, tumor, and healthcare factors associated with regional variability in lung cancer survival: A Spanish high-resolution population-based study. Clin. Transl. Oncol. 2018, 21, 621–629. [Google Scholar] [CrossRef] [Green Version]
  35. Lievens, Y.; De Schutter, H.; Stellamans, K.; Rosskamp, M.; Van Eycken, L. Radiotherapy access in Belgium: How far are we from evidence-based utilisation? Eur. J. Cancer 2017, 84, 102–113. [Google Scholar] [CrossRef]
  36. Corral, J.; Solà, J.; Galceran, J.; Marcos-Gragera, R.; Carulla, M.; Izquierdo, Á.; Vilardell, L.; Llauradó, L.; Espinàs, J.A.; Borras, J.M. A population perspective on the use of external beam radiotherapy in Catalonia, Spain. Clin. Transl. Oncol. 2020, 1–8. [Google Scholar] [CrossRef]
  37. Morris, E.J.; Finan, P.; Spencer, K.; Geh, I.; Crellin, A.; Quirke, P.; Thomas, J.; Lawton, S.; Adams, R.; Sebag-Montefiore, D.J. Wide Variation in the Use of Radiotherapy in the Management of Surgically Treated Rectal Cancer Across the English National Health Service. Clin. Oncol. 2016, 28, 522–531. [Google Scholar] [CrossRef] [Green Version]
Table 1. Distribution of colorectal cancer patients according to characteristics at diagnosis.
Table 1. Distribution of colorectal cancer patients according to characteristics at diagnosis.
Sub-Site
ColorectalColonRectump-Value
n(%)n(%)n(%)
Total1050(100.0)697(100.0)353(100.0)
GenderMale639(60.9)425(61.0)214(60.6)
Female411(39.1)272(39.0)139(39.4)0.912
Age group<65346(33.0)223(32.0)123(34.8)
65–74272(25.9)182(26.1)90(25.5)
75+432(41.1)292(41.9)140(39.7)0.678
Charlson comorbidity indexNo comorbidity (0–1)517(49.2)328(47.1)189(53.5)
Low comorbidity (2)165(15.7)113(16.2)52(14.7)
High comorbidity (3+)368(35.0)256(36.7)112(31.7)0.135
SmokerYes, currently129(13.9)76(12.3)53(17.3)
Yes, previously297(32.1)199(32.1)98(31.9)
No, never500(54.0)344(55.6)156(50.8)0.104
GradingGrade I, well differentiated165(15.7)105(15.1)60(17.0)
Grade II, moderately differentiated595(56.7)400(57.4)195(55.2)
Grade III, poorly differentiated90(8.6)68(9.8)22(6.2)
Grade IV, undifferentiated6(0.6)4(0.6)2(0.6)
Not determined, not graded194(18.5)120(17.2)74(21.0)0.187
Modality of diagnosisSymptomatic tumour1030(98.3)683(98.1)347(98.6)
Screened-detected18(1.7)13(1.9)5(1.4)0.599
MultifocalityYes42(4.0)35(5.1)7(2.0)
No1001(96.0)658(94.9)343(98.0)0.018
Basis of diagnosisDCO1(0.1)0(0.0)1(0.3)
Clinical39(3.7)31(4.4)8(2.3)
Microscopic1010(96.2)666(95.6)344(97.5)0.054
Histological typeAdenocarcinoma974(92.8)648(93.0)326(92.4)
Other76(7.2)49(7.0)27(7.6)0.715
TNM7 StageI179(17.0)111(15.9)68(19.3)
II278(26.5)203(29.1)75(21.2)
III277(26.4)166(23.8)111(31.4)
IV264(25.1)183(26.3)81(22.9)
Unknown52(5.0)34(4.9)18(5.1)0.010
TT1107(10.2)73(10.5)34(9.6)
T298(9.3)60(8.6)38(10.8)
T3572(54.5)369(52.9)203(57.5)
T4183(17.4)126(18.1)57(16.1)
Tx90(8.6)69(9.9)21(5.9)0.136
NN0482(45.9)349(50.1)133(37.7)
N1229(21.8)150(21.5)79(22.4)
N2/N+213(20.3)117(16.8)96(27.2)
Nx126(12.0)81(11.6)45(12.7)<0.001
Life status (at 31/12/2016)Alive536(51.0)353(50.6)183(51.8)
Dead514(49.0)344(49.4)170(48.2)0.714
DCO: Death certificate only; TNM7: TNM Classification System 7th Edition.
Table 2. Distribution of colorectal cancer patients according to diagnostic exams and preoperative tests.
Table 2. Distribution of colorectal cancer patients according to diagnostic exams and preoperative tests.
Sub-Site
ColorectalColonRectump-Value
n(%)n(%)n(%)
Total1050(100.0)697(100.0)353(100.0)
ColonoscopyNot done152(14.5)135(19.4)17(4.8)
Done, complete610(58.2)375(53.8)235(66.8)
Done, incomplete287(27.4)187(26.8)100(28.4)<0.001
Barium enemaDone71(6.9)51(7.5)20(5.8)
Not done959(93.1)633(92.5)326(94.2)0.316
Computed Tomography Magnetic Resonance Imaging (CT MRI) ColonographyDone146(14.2)27(4.0)119(34.5)
Not done882(85.8)656(96.0)226(65.5)<0.001
Number of lymph nodes examined<11 lymph nodes435(42.7)263(38.7)172(50.7)
≤12 lymph nodes583(57.3)416(61.3)167(49.3)<0.001
Lung imagingDone1025(99.2)679(99.3)346(99.1)
Not done8(0.8)5(0.7)3(0.9)0.698
Liver imagingDone1023(98.9)681(99.4)342(98.0)
Not done11(1.1)4(0.6)7(2.0)0.082
Brain imagingDone457(44.4)301(44.2)156(44.8)
Not done572(55.6)380(55.8)192(55.2)0.848
Skeleton imagingDone471(45.8)306(44.9)165(47.4)
Not done558(54.2)375(55.1)183(52.6)0.450
Pre-operative echographyDone626(60.8)417(61.1)209(60.2)
Not done404(39.2)266(38.9)138(39.8)0.798
Pre-operative thoracic xRayDone858(83.2)576(84.3)282(81.0)
Not done173(16.8)107(15.7)66(19.0)0.180
Pre-operative thoracic CTDone840(81.5)538(78.8)302(86.8)
Not done191(18.5)145(21.2)46(13.2)0.002
Pre-operative abdominal CTDone940(91.2)623(91.2)317(91.1)
Not done91(8.8)60(8.8)31(8.9)0.974
Pre-operative MRIDone266(26.1)45(6.6)221(64.4)
Not done755(73.9)633(93.4)122(35.6)<0.001
Pre-operative echoendoscopyDone457(44.4)263(38.5)194(56.1)
Not done572(55.6)420(61.5)152(43.9)<0.001
Table 3. Distribution of colorectal cancer patients according to treatment received.
Table 3. Distribution of colorectal cancer patients according to treatment received.
Sub-Site
ColorectalColonRectump-Value
n(%)n(%)n(%)
Total1050(100.0)697(100.0)353(100.0)
SurgeryNot done173(16.5)106(15.3)67(19.1)
Total colectomy29(2.8)25(3.6)4(1.1)
Hemi-colectomy337(32.2)326(46.9)11(3.1)
Anterior resection179(17.1)16(2.3)163(46.4)
Segmental resection203(19.4)182(26.2)21(6.0)
Abdomino-perineal resection65(6.2)6(0.9)59(16.8)
Other or unknown type60(5.7)34(4.9)26(7.4)<0.001
Type of hospital admissionPlanned689(79.2)431(73.3)258(91.5)
Emergency181(20.8)157(26.7)24(8.5)<0.001
Mode of surgeryOpen surgery688(79.4)468(79.7)220(78.9)
Laparoscopic surgery178(20.6)119(20.3)59(21.1)0.766
Reasons for no surgeryMedical contraindications17(10.1)11(10.7)6(9.2)
Patient refusal23(13.7)13(12.6)10(15.4)
Advanced cancer97(57.7)64(62.1)33(50.8)
Other23(13.7)11(10.7)12(18.5)
No indications8(4.8)4(3.9)4(6.2)0.545
Involvement of surgical marginsR0 resection695(97.7)463(97.9)232(97.5)
R1 resection16(2.3)10(2.1)6(2.5)0.730
Resection of metastasisR0 resection64(43.0)48(44.4)16(39.0)
R2 resection54(36.2)41(38.0)13(31.7)
R2: no resection31(20.8)19(17.6)12(29.3)0.291
ColostomyDone246(26.1)89(13.9)157(52.2)
Not done697(73.9)553(86.1)144(47.8)<0.001
Type of colostomyPermanent129(53.5)47(54.0)82(53.2)
Temporary97(40.2)29(33.3)68(44.2)
Alone. without resection15(6.2)11(12.6)4(2.6)0.005
ChemotherapyDone485(47.0)280(40.9)205(59.2)
Not done546(53.0)405(59.1)141(40.8)<0.001
Modality of chemotherapyNeo-adjuvant126(26.0)14(5.0)112(54.6)
Adjuvant264(54.4)202(72.1)62(30.2)
Perioperative0(0.0)0(0.0)0(0.0)
Palliative95(19.6)64(22.9)31(15.1)<0.001
Reasons for no chemotherapyMedical contraindications104(19.3)76(19.0)28(20.1)
Patient refusal33(6.1)21(5.3)12(8.6)
Other89(16.5)67(16.8)22(15.8)
No indications313(58.1)236(59.0)77(55.4)0.516
RadiotherapyDone184(17.8)4(0.6)180(52.2)
Not done850(82.2)685(99.4)165(47.8)<0.001
Modality of radiotherapyNeo-adjuvant125(67.9)1(25.0)124(68.9)
Adjuvant46(25.0)0(0.0)46(25.6)
Palliative13(7.1)3(75.0)10(5.6)<0.001
Reasons for no radiotherapyMedical contraindications23(2.7)8(1.2)15(9.1)
Patient refusal12(1.4)3(.4)9(5.5)
Other65(7.7)43(6.3)22(13.4)
No indications744(88.2)626(92.1)118(72.0)<0.001
Targeted Treatment (TT)Done62(6.0)45(6.6)17(5.0)
Not done966(94.0)640(93.4)326(95.0)0.306
R0: No residual tumor; R1: Microscopic residual tumor; R2: Macroscopic residual tumor.
Table 4. Number (and percentage) of colorectal cancer patients as a function of adherence to the quality indicators (QIs).
Table 4. Number (and percentage) of colorectal cancer patients as a function of adherence to the quality indicators (QIs).
Quality IndicatorSub-Site
TotalColonRectum
NoYesNoYesNoYes
n(%)n(%)n(%)n(%)n(%)n(%)
QI1: the patient, following the CRC diagnosis, was assessed by the specific tumor commission before starting treatment.85(8.1)961(91.9)63(9.1)632(90.9)22(6.3)329(93.7)
QI2: complementary imaging tests were requested: colonoscopy, CT of the chest, abdomen and pelvis, and MRI of the pelvis.399(38.0)651(62.0)258(37.0)439(63.0)141(39.9)212(60.1)
QI3: the patient underwent surgery sooner than 30 days after the histological diagnosis.280(38.5)448(61.5)201(35.2)370(64.8)79(50.3)78(49.7)
QI4: the patient initiated neoadjuvant therapy (radiotherapy/chemotherapy or chemotherapy or radiotherapy) sooner than 30 days after the histological diagnosis.95(65.1)51(34.9)8(53.3)7(46.7)87(66.4)44(33.6)
QI5: the patient started adjuvant treatment sooner than 8 weeks after surgical treatment.95(36.1)168(63.9)59(29.2)143(70.8)36(59.0)25(41.0)
QI6: the patient underwent excision and analysis of at least 12 lymph nodes to allow for appropriate lymph node staging.198(25.4)583(74.6)119(22.2)416(77.8)79(32.1)167(67.9)
QI7: the patient, if diagnosed with a stage III colon carcinoma, underwent chemotherapy treatment.56(33.3)112(66.7)56(33.3)112(66.7)-
QI8: the patient, if diagnosed with stage II or III carcinoma of the rectum underwent radiotherapy/chemotherapy or radiotherapy treatment with neoadjuvant or adjuvant intent.62(26.6)171(73.4)-62(26.6)171(73.4)
QI9: perioperative mortality, defined as patient death in the first 30 days after surgical treatment821(94.2)51(5.8)550(93.4)39(6.6)271(95.8)12(4.2)
Table 5. Observed (OS) and net survival (NS) at 1, 3 and 5 years since diagnosis of colorectal cancer and relative excess risk of death (RER) as a function of adherence to the quality indicators (QIs).
Table 5. Observed (OS) and net survival (NS) at 1, 3 and 5 years since diagnosis of colorectal cancer and relative excess risk of death (RER) as a function of adherence to the quality indicators (QIs).
Quality IndicatorYears Since DiagnosisRelative Excess Risk of Death
1 Year3 Years5 YearsRER95% CIp-Value
OSNS95% CIOSNS95% CIOSNS95% CI
QI1No69.471.9(60–80.8)57.663.1(49.7–73.9)51.860.7(45.9–72.6)1 -
Yes77.479.8(76.9–82.4)60.166.2(62.6–69.5)52.062.4(58.3–66.1)1.21(0.70–2.08)0.495
QI2No66.368.8(63.7–73.4)49.855.9(50.1–61.3)43.354.6(48.1–60.7)1 -
Yes83.385.6(82.3–88.3)66.272.1(67.9–75.9)57.367.0(62.1–71.3)0.58(0.46–0.73)<0.001
QI3No88.691.5(86.6–94.6)75.783.9(77.2–88.8)66.881.1(73–87)1 -
Yes82.284.7(80.6–87.9)66.373.2(67.9–77.7)58.471.0(64.9–76.2)1.77(1.17–2.66)0.007
QI4No90.592.4(83.4–96.6)74.779.8(68.4–87.5)61.167.7(54.9–77.6)1 -
Yes90.291.5(78.1–96.8)68.672.4(56.4–83.3)58.863.2(46.2–76.2)1.27(0.65–2.50)0.479
QI5No96.899.3(41–100)76.883.2(71.3–90.5)66.377.3(63.7–86.3)1 -
Yes93.595.1(89.5–97.8)76.881.1(73.2–87)66.173.0(63.9–80.1)1.10(0.61–1.98)0.749
QI6No83.486.0(79.6–90.5)68.876.1(67.9–82.4)60.874.4(64.7–81.9)1 -
Yes88.491.0(87.9–93.4)72.179.5(75.1–83.2)62.174.8(69.6–79.3)1.00(0.68–1.47)0.995
QI7No69.675.3(59.3–85.7)46.458.7(39.7–73.5)42.964.7(40.2–81.3)1 -
Yes95.597.4(88.6–99.4)77.782.8(72.6–89.4)70.578.9(67.2–86.8)0.33(0.16–0.70)0.004
QI8No79.082.7(68.7–90.8)69.481.2(62.5–91.1)58.184.0(56.1–94.9)1 -
Yes93.595.7(88.2–98.5)77.483.4(73.5–89.9)66.975.8(64.3–84.1)0.92(0.40–2.14)0.848
Overall adherence (≥75% of indicators)No71.173.8(69.2–77.7)54.160.2(54.9–65.2)47.057.7(51.7–63.2)1 -
Yes81.483.5(79.9–86.5)64.770.6(66–74.6)56.065.9(60.8–70.6)0.35(0.28–0.45)<0.001

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Carrasco-Peña, F.; Bayo-Lozano, E.; Rodríguez-Barranco, M.; Petrova, D.; Marcos-Gragera, R.; Carmona-Garcia, M.C.; Borras, J.M.; Sánchez, M.-J. Adherence to Clinical Practice Guidelines and Colorectal Cancer Survival: A Retrospective High-Resolution Population-Based Study in Spain. Int. J. Environ. Res. Public Health 2020, 17, 6697. https://doi.org/10.3390/ijerph17186697

AMA Style

Carrasco-Peña F, Bayo-Lozano E, Rodríguez-Barranco M, Petrova D, Marcos-Gragera R, Carmona-Garcia MC, Borras JM, Sánchez M-J. Adherence to Clinical Practice Guidelines and Colorectal Cancer Survival: A Retrospective High-Resolution Population-Based Study in Spain. International Journal of Environmental Research and Public Health. 2020; 17(18):6697. https://doi.org/10.3390/ijerph17186697

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Carrasco-Peña, Francisco, Eloisa Bayo-Lozano, Miguel Rodríguez-Barranco, Dafina Petrova, Rafael Marcos-Gragera, Maria Carmen Carmona-Garcia, Josep Maria Borras, and Maria-José Sánchez. 2020. "Adherence to Clinical Practice Guidelines and Colorectal Cancer Survival: A Retrospective High-Resolution Population-Based Study in Spain" International Journal of Environmental Research and Public Health 17, no. 18: 6697. https://doi.org/10.3390/ijerph17186697

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