Statins for preventing colorectal adenoma and carcinoma

  • Protocol
  • Intervention

Authors

  • Dipika Bansal,

    Corresponding author
    1. National Institute of Pharmaceutical Education and Research (NIPER), Clinical Research Unit, Department of Pharmacy Practice, Mohali, Punjab, India
    • Dipika Bansal, Clinical Research Unit, Department of Pharmacy Practice, National Institute of Pharmaceutical Education and Research (NIPER), F-307, Research Block, NIPER, Sector 67, Mohali, Punjab, 160062, India. dipikabansal079@gmail.com. dipikabansal@niper.ac.in.

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  • Kapil Gudala,

    1. National Institute of Pharmaceutical Education and Research (NIPER), Department of Pharmacy Practice, Mohali, Punjab, India
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  • Krishna Undela

    1. JSS College of Pharmacy, JSS University, Department of Pharmacy Practice, Mysore, Karnataka, India
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Abstract

This is the protocol for a review and there is no abstract. The objectives are as follows:

The primary objectives are to assess the effect of statins on the incidence of colorectal adenomatous polyps and on the incidence of CRC compared with placebo. A secondary objective is to evaluate the incidence of adverse effects resulting from this intervention.

Background

Description of the condition

Colorectal cancer (CRC) is a malignant neoplasm that occurs as a result of uncontrolled cell proliferation in the colon and rectum. It is the third most common cancer in men (746,000 incident cases, 10.0% of all cancers) and the second most common cancer in women (614,000 incident cases, 9.2% of all cancers) worldwide (GLOBOCAN 2012). The highest incidence of CRC is found in developed countries, such as Australia, New Zealand, Canada, the USA and parts of Europe, whereas the lowest incidence is found in developing countries, such as China, India, parts of Africa and South America. More than six lakh (600.000) incident deaths are reported to occur from CRC worldwide, accounting for 8.5% of all cancer deaths, making CRC the fourth most common cause of cancer-related death (GLOBOCAN 2012).

CRC is thought to progress through various morphological stages, including polyp formation and malignant conversion (Kinzler 1996). Adenomatous polyps are common in adults aged over 50 years. Though a majority of these polyps do not develop into adenocarcinoma, their clinical importance is determined by their histology and size. Most CRC screening studies evaluate the detection rate of invasive CRC and advanced adenomas (conventionally defined as polyps greater than or equal to 10 mm in size, or histologically having high-grade dysplasia or significant villous components). It usually takes more than a decade for a small premalignant adenoma to become a malignant neoplasm (Winawer 1999). This slow development provides an opportunity to prevent CRC in people at increased risk of developing CRC.

The risk of developing CRC increases with advancing age; more than 90% cases occur in people aged over 50 years. Other risk factors include inflammatory bowel disease, a personal or family history of CRC or colorectal polyps, and the presence of a genetic syndrome such as familial adenomatous polyposis (FAP) or Lynch syndrome. Certain lifestyle factors such as physical inactivity, a low fibre and high-fat diet, obesity, and alcohol and tobacco consumption may also contribute to an increased risk of CRC (Rasool 2013).

CRC is expensive to treat. The cost of treatment in the USA was estimated to be 14 billion USD in 2010 and is projected to reach 17 billion USD by the year 2020 (Mariotto 2011). The average lifetime cost in 2000 (in Canadian dollars, CAD) for managing individuals with CRC ranged from 20,319 CAD per case for stage I colon cancer to 39,182 CAD per case for stage III rectal cancer (Maroun 2003). The total lifetime treatment cost for the cohort of individuals with CRC in the year 2000 was estimated to be over 333 million CAD for colon and 187 million CAD for rectal cancer. Hospitalisation represented 61% to 65% of the cost of CRC management (Maroun 2003).

The prognosis of CRC is determined by factors such as the size, location and histology of the primary tumour, and the degree of involvement of the lymph nodes and the spread of cancer to other tissues (metastases). As with other cancers, advances in medical and surgical techniques as well as adjuvant therapy have led to only a modest improvement in survival for individuals presenting with advanced neoplasms (Krook 1991; Moertel 1990). According to the American Cancer Society, the five-year survival rate for CRC ranges from 74% for stage I to 6% for stage IV cancer (American Cancer Society 2013). Due to the rising burden of this disease and the limitations of behavioural interventions, there is an urgent need for novel chemopreventive agents to reduce the morbidity and mortality from CRC.

Description of the intervention

Statins are small-molecule inhibitors of 3-hydroxy-3-methylglutaryl coenzyme-A (HMG-CoA) reductase. Statins are cholesterol-lowering agents and are effective in the management of individuals with hypercholesterolaemia. They are available in immediate- and extended-release forms. Dosages range from 20 mg to 80 mg per day, depending on the indication for usage. The bioavailability of statins ranges from 5% to 60%; the elimination half-life of statins ranges from 1 hour to 19 hours (Schachter 2004).

How the intervention might work

Statins are primarily used as cholesterol-reducing agents. However, post-hoc analyses of randomised controlled clinical trials have revealed statins to also have chemopreventive effect for a number of different cancers (Graaf 2004). The pleiotropic effects of statins may be related to their interactions with diverse signalling pathways and targets including the enzyme 3-hydroxy-3-methylglutaryl coenzyme-A (HMG-CoA) reductase which is located at the apex of a molecular pathway called the mevalonate cascade (Liao 2005). Statins have been found to work against critical cellular functions involved in the control of tumour initiation, progression and metastasis (Graaf 2004). The effects of statins can occur through HMG-CoA reductase-dependent or HMG-CoA reductase-independent pathways (Demierre 2005).

HMG-CoA reductase-dependent pathway

By inhibiting the biosynthesis of mevalonate, statins also inhibit the formation of downstream lipid isoprenoid intermediates such as farnesyl pyrophosphate (FPP) and geranylgeranyl pyrophosphate (GGPP) (Demierre 2005). Isoprenoids are lipid moieties that are added to various proteins, including G-proteins and the G-protein subunits Ras, Rho, Rab, Rac and Rap, during post-translational modification (prenylation) and anchor these proteins to the cell membrane. Post-translational prenylation by FPP or GGPP is essential for G-protein function (G-proteins are known to affect signalling pathways along the spectrum from cancer formation to progression) (Edwards 1999; Mo 2004). FPP helps prenylate proteins in the Ras, Rheb and PTP4A3 families, whereas GGPP helps prenylate proteins in the Rho, Rac and Cdc42 families. A few G-proteins (including RhoB and Nras) can be either farnesylated or geranylgeranylated. Recent short-interfering (si) RNA studies indicate that RhoC is the most important isoform in stimulating invasion of certain cancers; RhoA has also been implicated in epithelial-to-mesenchymal transition, an important event in cancer progression (Demierre 2005). The ability of statins to inhibit the formation of these proteins could be important to the pleiotropic effects of these drugs. The most relevant studies to date, however, indicate that GGPP prenylation (geranylgeranylation) of other proteins, including the Rho proteins, is the crucial step in the apoptotic, angiogenic and inflammatory effects of statins, as well as in other important cellular effects of statins (Demierre 2005; Graaf 2004; Poynter 2005; Sleijfer 2005).

HMG-CoA reductase-independent pathway

Lovastatin directly binds to the L (lovastatin) site in the I (inserted) domain of the integrin lymphocyte function-associated antigen-1 (LFA1), which is expressed on the surface of various leucocytes (Weitz-Schmidt 2001). Intercellular-adhesion molecule 1 (ICAM-1) acts as a ligand for LFA-1, binding of ICAM-1 to LFA-1 will initiate the more cellular recruitment of T-cells towards the target site, which can be a inflammatory site and this allows for further downstream process which may employ pro-inflammatory mediators or cytokines and activate various cell signalling/interaction processes which can facilitate for metastasis/ progression of cancer cells under the name of more cellular recruitment/infiltrations (Kelly 1992). The binding of lovastatin to the LFA1 I-domain induces a conformational change in LFA1 and inhibits the interaction of LFA1 with ICAM1 through an allosteric mechanism. Therefore, lovastatin inhibits the function of LFA1 by stabilising the receptor in an inactive conformation. Simvastatin also inhibit LFA1 by binding to the L-site. Blocking the LFA1–ICAM1 interaction could contribute to the effects of statins on cell and suppress the inflammatory response adhesion, invasion and inflammation (Weitz-Schmidt 2001).

Statins reportedly also target the protein degradation machinery, specifically the proteasome (Rao 1999). Inhibition of the proteasome could account for the effects of statins on the cyclin-dependent kinase inhibitors (CDKIs) p21 (also known as CDKN1A) and p27 (also known as CDKN1B), although other mechanisms have been reported (Demierre 2005; Poynter 2005; Sleijfer 2005).

Other putative mechanisms of statins include statin-induced chromatin condensation and DNA laddering, and the activation of caspases in association with statin-induced apoptosis has also been documented (Cafforio 2005). Statins can inhibit cellular proliferation through the induction of G1/S arrest and/or G2/M arrest in numerous cell lines (Keyomarsi 1991). It seems that the effects of statins on proliferation and apoptosis are independent of each other, although both can occur in the same cell line at different concentrations. Statins seem to induce apoptosis and inhibit proliferation to a greater degree in malignant than in non-malignant cells, possibly because of the increased expression of HMG-CoA reductase and a greater requirement for mevalonate-derived isoprenoids in tumour as opposed to normal cells (Demierre 2005; Poynter 2005).

Why it is important to do this review

The evidence regarding the effect of statins on CRC risk has been rather contradictory. Some epidemiological studies - both cohort (Flick 2009; Friis 2005; Jacobs 2006; Setoguchi 2007; Singh 2009) and case-control studies (Blais 2000; Coogan 2007; Coogan 2007a; Farwell 2008; Graaf 2004a; Haukka 2010; Hoffmeister 2007; Kaye 2004; Poynter 2005; Vinogradova 2007; Yang 2008) - have been conducted to estimate this association, but the exact role of the chemopreventive activity of statins in CRC remains to be elucidated. Some randomised clinical trials on statin use in coronary heart disease (ALLHAT 2002; Colhoun 2004; LIPID Study 2002; Nakamura 2006; Ridker 2008; Sacks 1996; Shepherd 1995; Shepherd 2002; Strandberg 2004) have reported a non-significant decrease in the incidence of CRC among statin users compared with non-users, but most of the results were ambiguous because the studies were inadequately powered to assess this outcome.
Therefore, we will undertake a systematic review of the literature to collect and compile data on the association between the use of statins and the risk of CRC in randomised controlled trials.

Objectives

The primary objectives are to assess the effect of statins on the incidence of colorectal adenomatous polyps and on the incidence of CRC compared with placebo. A secondary objective is to evaluate the incidence of adverse effects resulting from this intervention.

Methods

Criteria for considering studies for this review

Types of studies

We will include randomised controlled trials investigating the effect of statins in preventing colorectal adenomas and carcinomas. Statins considered for inclusion in this systematic review are atorvastatin, cerivastatin, fluvastatin, lovastatin, pravastatin, simvastatin and rosuvastatin.

Types of participants

Participants from the general population with a history of adenomatous polyps but not colorectal cancer will be included in this review. Data from individuals with familial adenomatous polyposis (FAP) will be excluded. Study participants will have undergone at least one documented procedure that directly visualised the colon and rectum at baseline and at least two years after the baseline investigation. Studies that do not use appropriate procedures (i.e. polypectomy) to ensure that the colon or rectum is free of polyps at baseline will be excluded. Studies that include participants with new or recurrent adenomas will be included.

Types of interventions

Studies in which participants in the treatment group receive statins at any dose versus a comparison group receiving placebo or no treatment will be considered for inclusion.

Types of outcome measures

Studies will have to report at least one of the primary outcomes for it to be included. Adenomatous polyp and CRC outcomes will have to be confirmed pathologically.

Primary outcomes
  1. Number of participants with:

    1. at least one adenomatous polyp;

    2. at least one adenomatous polyp that is 1 cm or greater in size.

  2. Number of participants with a new diagnosis of CRC.

Secondary outcomes

Type, frequency and severity of adverse effects.

Search methods for identification of studies

For multiple publications from the same study population, only data from the most recent report will be included. No language restrictions will be applied.

Electronic searches

We will conduct a comprehensive literature search to identify all published and unpublished randomised controlled trials with no language restrictions. We will search the following electronic databases to identify potential studies:

  1. Cochrane Central Register of Controlled Trials (CENTRAL) (The Cochrane Library) (1980 to present);

  2. MEDLINE (1980 to present);

  3. EMBASE (1980 to present);

  4. CINAHL (1980 to present);

  5. ISI Web of knowledge (1980 to present).

The reference lists of studies and review articles identified by the literature search will be reviewed for additional studies.

The search strategies for CENTRAL, MEDLINE and EMBASE are presented in Appendix 1.

Searching other resources

Clinical trials will be identified by scanning the reference lists in relevant papers. We will search the following online clinical trials databases: Clinical Trials of the American Cancer Society (http://www.cancer.gov), the metaRegister of Controlled Trials (http://www.controlled-trials.com) and the German Cancer Study Register (http://www.studien.de), and conference abstracts to identify unpublished material. We will search The Grey Literature Report and OpenGrey databases for grey literature. Relevant professional and research organisations will be contacted to identify any additional published or unpublished research of relevance.

Data collection and analysis

Selection of studies

Two reviewers (KG and KU) will independently review the titles and abstracts of references retrieved from the searches and select potentially relevant studies. The full text of provisionally included studies will be assessed by KG and KU together to determine whether the study meets the inclusion criteria. Any differences in opinion will be resolved by discussion until consensus is reached. If agreement cannot be reached, a third author (DB) will be consulted.

PRISMA flow diagram
We will create a flow chart showing the process of study selection, as suggested by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement, in order to illustrate the results of our various searches and the process of screening and selecting studies for inclusion in the review.

Data extraction and management

Two reviewers (DB and KU) will independently extract data from selected trials using a paper data extraction form (Appendix 2). Any discrepancies will be resolved by discussion until consensus is reached and the corresponding author of the study will be contacted for clarification. Any remaining differences will be resolved with the help of an independent expert gastroenterologist or statistician. Justification for excluding studies from the review will also be documented. Data will be entered into Review Manager (RevMan) 5.2 software and checked for accuracy.

Assessment of risk of bias in included studies

The risk of bias of the included studies will be evaluated independently by two reviewers (KG and KU). Studies will be assessed for selection bias, performance bias, attrition bias and detection bias, as follows.

Selection bias

Allocation concealment:

  1. low risk: use of a randomisation method that does not allow the investigator or participant to know or influence the allocation of treatment before eligible participants enter the study;

  2. unclear: the studies states that randomisation is used but provides no information on the method used;

  3. high risk: use of alternate medical record numbers or unsealed envelopes as randomisation method; hence, there is information in the study to indicate that investigators or participants could have influenced the allocation of treatment.

Performance bias

  1. Masking of study personnel: low/unclear/high risk.

  2. Masking of participants: low/unclear/high risk.

Study personnel and participants will be considered not masked if the intervention group can be identified in >20% of participants because of treatment-emergent adverse events.

Detection bias

Masking of outcome assessors: low/unclear/high risk.

Attrition bias

Intention-to-treat (ITT) analysis performed:

    1. low risk: all participants have been analysed according to the treatment group to which they were randomised, regardless of whether or not they received the allocated intervention;

    2. high risk: some participants (<5%, 5% to 10%, 10% to 20%, >20%) have not been analysed according to the treatment group to which they were randomised because they either did not receive the study intervention or dropped out/withdrew from the study, or because of a protocol violation;

    3. unclear: it cannot be determined whether participants were analysed according to the ITT principle, even after contact with the original study authors

Clarification from the author will be sought if the published data provides inadequate information for the review. Discrepancies will be resolved by consensus. Following quality assessment of the studies, potential risks of bias will be allocated, as follows, as described in the Cochrane Handbook for Systematic Reviews of Interventions.

  1. Low risk of bias: plausible bias is unlikely because all criteria are met and do not seriously alter the results.

  2. Moderate risk of bias: plausible bias is present as one or more criteria are not met, thus raising doubt about the results.

  3. High risk of bias: plausible bias is present, two or more criteria are not met, thus weakening confidence about the results, randomisation procedure, concealment of allocation, blind assessment of outcomes and losses to follow up.

Measures of treatment effect

Dichotomous data will be presented as risk ratios (RR) or incidence rate ratios (IRR), and 95% confidence intervals (CI) for each study. We will combine data from all the studies (separately for adenomatous polyp and CRC outcomes), irrespective their follow-up periods. We plan a subgroup analysis according to the duration of statin use. Effect estimates will be expressed separately for adenomatous polyp and CRC outcomes. An RR or IRR greater than 1.0 will be taken to indicate that statins may increase the incidence of CRC. We will analyse the data using RevMan 5.2, according to the recommendations of the Cochrane Handbook for Systematic Reviews of Interventions.

Unit of analysis issues

Studies with non-standard designs, such as cross-over trials and cluster-randomized trials will not be included in the review.

Dealing with missing data

Data that have been measured but not reported will be sought from study authors. If there is a discrepancy between the numbers of participants randomised and those analysed in each treatment group, the percentage lost to follow up in each group will be calculated and reported. For dichotomous data, if dropouts exceed 30% in any study and the missing dropouts will be assumed to have survived and free of neoplasms (best-case scenario).

Assessment of heterogeneity

Heterogeneity will be explored among study results using a multistep process including:

  1. forest plots: visual examination for the presence or absence of overlap in the CI. Lack of overlap of the CI will indicate heterogeneity;

  2. I2 measurement: this will be used to assess the amount of variability arising due to heterogeneity;

  3. Chi2 test for heterogeneity: data will be considered heterogeneous if the P value is < 0.10.

If we detect substantial heterogeneity (I2 > 50%, P value < 0.10) (Higgins 2002), we will look for possible explanations for this by conducting subgroup analyses. If we cannot find an explanation for the heterogeneity, we will consider the following options: provide a narrative overview and not aggregate the studies at all, or use a random-effects model with appropriate cautious interpretation.

Assessment of reporting biases

If 10 or more trials contribute data to a meta-analysis, a funnel plot will be used to assess the risk of reporting bias and such findings will be presented in a table. If, on visual assessment, a funnel plot is found to be asymmetrical, we will carry out exploratory analyses to investigate any suggestion of visual asymmetry in the funnel plots.

Data synthesis

The analyses will be performed using RevMan 5.2. The results will be shown using the approach recommended in the Cochrane Handbook for Systematic Reviews of Interventions. All randomised participants included will be analysed using the ITT principle. Heterogeneity will be assessed among trials using the I2 measurement. The results will be combined in meta-analysis if the interventions are the same or sufficiently similar. The data will be analysed using random-effects model. Subgroup analyses will be performed to assess the impact of possible sources of heterogeneity, when appropriate. The authors of included studies will be contacted to supply missing data. Funnel plots will be drawn if sufficient studies are included.

Subgroup analysis and investigation of heterogeneity

As trials are conducted by different groups of investigators at different periods of time, they may be heterogeneous in nature.

If there is substantial heterogeneity among the studies included with regard to the primary outcomes, reasons for the heterogeneity will be explored using subgroup analyses. Subgroup analyses will be based on:

  1. type of statin used: hydrophilic or lipophilic agents; naturally or synthetically derived agents;

  2. dose and duration of statin usage;

  3. age group of participants: less than and greater than 50 years;

  4. incidence or recurrence of adenomatous polyps;

  5. personal history of inflammatory bowel disease or type 2 diabetes mellitus;

  6. race and ethnic background (African-Americans have the highest incidence of CRC among all racial groups).

We plan to use multivariable meta-regression to assess whether treatment effect and heterogeneity are associated with the factors mentioned above. Meta-regression analysis will also be attempted to elucidate the dose-response relationship.

Sensitivity analysis

If sufficient data are available, analyses will be repeated:

  1. excluding unpublished studies (if there are any);

  2. excluding trials at high or unclear risk of bias;

  3. excluding any outlying results.

  4. performing fixed effects model

  5. Worst case scenario

Summary of Findings tables

The quality of the evidence will be rated using GRADE methods (http://www.gradeworkinggroup.org/) for the following outcomes:

  1. Number of participants with at least one adenomatous polyp;

  2. Number of participants with at least one adenomatous polyp that is 1 cm or greater in size.

  3. Number of participants with a new diagnosis of CRC.

  4. Adverse effects

Evidence will start at high quality for RCTs and will be downgraded to moderate, low or very low quality evidence based on consideration of the impact of risk of bias, imprecision, inconsistency, indirectness and publication bias. The quality of the evidence will be presented in a Summary of Findings table for each comparison.

Acknowledgements

We thank Ms Barbateskovic for developing the search strategies for this review.

Appendices

Appendix 1. Search strategy of electronic databases

Database Searched period Search strategy
CENTRALUp to 2013

#1 MeSH descriptor: [Hydroxymethylglutaryl-CoA Reductase Inhibitors] explode all trees

#2 MeSH descriptor: [Anticholesteremic Agents] explode all trees

#3 statin* or Hydroxymethylglutaryl* or HMG CoA* or HMG-CoA* or Hydroxymethylglutaryl-CoA Reductase Inhibitor* or 3-hydroxy-3-methylglutar* or cholesterol:ti,ab,kw

#4 Atorvastatin* or Altocor* or Altoprev* or Baycol* or Cerivastatin* or Compactin* or Crestor* or Dalvastatin* or Fluvastatin* or Fluindostatin* or Lovastatin* or Lipitor* or Lescol* or Lipostat* or Livalo* or Lipex* or Mevacor* or Mevinolin* or Mevastatin* or Monacolin* or Meglutol* or Pravastatin* or Pravachol* or Pitavastatin* or Pitava* or Rivastatin* or Rosuvastatin* or Selektine* or Simvastatin* or Torvast* or Zocor*:ti,ab,kw

#5 (#1 or #2 or #3 or #4)

#6 MeSH descriptor: [Colorectal Neoplasms] explode all trees

#7 ((colorect* or colon* or rect* or anal* or anus* or intestin* or bowel*) near/3 (carcinom* or neoplas* or adenocarcinom* or cancer* or tumor* or tumour* or sarcom* or polyp* or adenom*)):ti,ab,kw

#8 (#6 or #7)

#9 (#5 and #8)

MEDLINE (Ovid)Up to 2013

1. exp Hydroxymethylglutaryl-CoA Reductase Inhibitors/

2. exp Anticholesteremic Agents/

3. (statin* or Hydroxymethylglutaryl* or HMG CoA* or HMG-CoA* or Hydroxymethylglutaryl-CoA Reductase Inhibitor* or 3-hydroxy-3-methylglutar* or cholesterol).mp.

4. (Atorvastatin* or Altocor* or Altoprev* or Baycol* or Cerivastatin* or Compactin* or Crestor* or Dalvastatin* or Fluvastatin* or Fluindostatin* or Lovastatin* or Lipitor* or Lescol* or Lipostat* or Livalo* or Lipex* or Mevacor* or Mevinolin* or Mevastatin* or Monacolin* or Meglutol* or Pravastatin* or Pravachol* or Pitavastatin* or Pitava* or Rivastatin* or Rosuvastatin* or Selektine* or Simvastatin* or Torvast* or Zocor*).mp.

5. 1 or 2 or 3 or 4

6. exp Colorectal Neoplasms/

7. ((colorect* or colon* or rect* or anal* or anus* or intestin* or bowel*) adj3 (carcinom* or neoplas* or adenocarcinom* or cancer* or tumor* or tumour* or sarcom* or polyp* or adenom*)).mp.

8. 6 or 7

9. 5 and 8

10.randomized controlled trial.pt.

11.controlled clinical trial.pt.

12.randomized.ab.

13.placebo.ab.

14.clinical trial.sh.

15.randomly.ab.

16.trial.ti.

17.10 or 11 or 12 or 13 or 14 or 15 or 16

18.humans.sh.

19. 17 and 18

20. 19 and 9

EMBASE

(Ovid)

Up to 2013

1. exp hydroxymethylglutaryl coenzyme A reductase inhibitor/

2. exp hypocholesterolemic agent/

3. (statin* or Hydroxymethylglutaryl* or HMG CoA* or HMG-CoA* or Hydroxymethylglutaryl-CoA Reductase Inhibitor* or 3-hydroxy-3-methylglutar* or cholesterol).mp.

4. (Atorvastatin* or Altocor* or Altoprev* or Baycol* or Cerivastatin* or Compactin* or Crestor* or Dalvastatin* or Fluvastatin* or Fluindostatin* or Lovastatin* or Lipitor* or Lescol* or Lipostat* or Livalo* or Lipex* or Mevacor* or Mevinolin* or Mevastatin* or Monacolin* or Meglutol* or Pravastatin* or Pravachol* or Pitavastatin* or Pitava* or Rivastatin* or Rosuvastatin* or Selektine* or Simvastatin* or Torvast* or Zocor*).mp.

5. 1 or 2 or 3 or 4

6. *colon tumor/

7. *rectum tumor/

8. ((colorect* or colon* or rect* or anal* or anus* or intestin* or bowel*) and (carcinom* or neoplas* or adenocarcinom* or cancer* or tumor* or tumour* or sarcom* or polyp* or adenom*)).m_titl.

9. 6 or 7 or 8

10. 5 and 9

11. CROSSOVER PROCEDURE.sh.

12. DOUBLE-BLIND PROCEDURE.sh.

13. SINGLE-BLIND PROCEDURE.sh.

14. (crossover* or cross over*).ti,ab.

15. placebo*.ti,ab.

16. (doubl* adj blind*).ti,ab.

17. allocat*.ti,ab.

18. trial.ti.

19. RANDOMIZED CONTROLLED TRIAL.sh.

20. random*.ti,ab.

21. 11 or 12 or 13 or 14 or 15 or 16 or 17 or 18 or 19 or 20

22. (exp animal/ or exp invertebrate/ or animal.hw. or nonhuman/) not (exp human/ or human cell/ or (human or humans or man or men or wom?n).ti.)

23. 21 not 22

Appendix 2. Data collection form

General information: Extracted Data
Title 
First author 
Author affiliation 
Author degree 
Institution 
Corresponding author contact address 
Source of this article 
Verification of study eligibility 
Methods: 
Study design 
Unit of allocation 
Unit of analysis 
Power calculation 
Method of randomization 
Allocation concealment 
Blinding 
Population: 
Recruitment of patients 
Place 
Enrolment dates 
Inclusion criteria 
Exclusion criteria 
Age 
Sex 
Ethnicity 
Work status 
Diagnosis of disease 
Outcome measures 
Total number of patients recruited 
Number of patients who met inclusion criteria 
Total number of patients randomized 
Total number of patients followed up 
Dropout rate (%) 
Interventions: 
Intervention 
Control group (s) 
Outcomes: 
Who carried out the measurement? 

What was measured at baseline?

How was it measured?

Is the tool validated?

(as stated in the article)

 

What was measured immediately after the intervention?

How was it measured?

Is the tool validated (as stated in the article)?

 

When was the first follow-up?

What was measured at the first follow-up?

How was it measured? Is the tool validated

(as stated in the article)?

 
Analysis: 
Statistical technique used 
Intention-to-treat analysis? 
Does the technique adjust for confounding? 
Number (or %) of followed up from each group 
Results Results

Contributions of authors

The protocol was written by Kapil Gudala with contributions from all co-authors.

Declarations of interest

None known.

Ancillary