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Cochrane Database of Systematic Reviews Protocol - Intervention

Pancreatic enzyme replacement therapy for steatorrhoea in pancreatic cancer

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Abstract

This is a protocol for a Cochrane Review (Intervention). The objectives are as follows:

To evaluate the efficacy of PERT for the treatment of steatorrhoea in people with pancreatic cancer by accessing whether it:

  1. reduces the severity and duration of common symptoms, including fatty (greasy or oily appearance and residue), foul‐smelling, pale‐coloured, and heavy stools (bulky and difficult‐to‐flush), which are usually associated with weight loss and nutritional deficiencies as a result of fat malabsorption and the concomitant malabsorption of amino acids and vitamins, and abdominal pain or cramps (Cheifetz 2011; Kasper 2015);

  2. is an acceptable treatment, as assessed by the number of side effects/adverse events, study dropout rates, and participant satisfaction levels;

  3. has an impact on chemotherapy adherence;

  4. has an impact on postoperative outcomes.

Background

Description of the condition

The presence of malignant cells in the pancreas, which can occur in tissues with either an exocrine or endocrine function, is called pancreatic cancer (PDQ 2015).

With about 278,684 cases every year, pancreatic cancer is the thirteenth most common cancer in the world. Nevertheless, it ranks eighth in men and ninth in women among the most common causes of death due to cancer (Kasper 2015).

Northern America and Western Europe had the highest incidence rates of pancreatic cancer in 2012, while Middle Africa and South‐Central Asia had the lowest. Incidence rates are higher in men than in women and increase with age (Ilic 2016).

Prognosis is poor, with a five‐year survival rate of less than 5% (Badger 2010). Between 15% and 20% of people with pancreatic cancer undergo successful resection and this increases the five‐year survival rate to 20% (Li 2004).

Pancreatic cancer usually progresses from precancerous lesions to invasive cancer as a result of the presence of oncogene and tumour‐suppressor gene mutations (Hidalgo 2010; Li 2004). The most common mutations affect the KRAS2 oncogene (Maitra 2008).

Smoking and obesity are known risk factors for pancreatic cancer. Diabetes mellitus and chronic pancreatitis also increase the risk. Other risk factors include a family history of pancreatic cancer and the presence of genetic syndromes, such as hereditary non‐polyposis colorectal cancer syndrome (HNPCC), Peutz‐Jeghers, BRCA2 gene mutation, and familial atypical multiple mole melanoma syndrome (FAMMM) (Maitra 2008).

More than two‐thirds of pancreatic cancers are located in the head of the pancreas (Freelove 2006). Such cancers are characterised by obstructive jaundice (Bruno 1998); weight loss and pain are usually also present. Pancreatic cancers arising in the body or tail of the pancreas usually present only with weight loss and pain (Freelove 2006).

Pancreatic cancers may cause pancreatic exocrine insufficiency (PEI), which is the inadequacy of pancreatic enzymes to digest food properly. This condition can occur as a result of the destruction of the normal pancreatic tissue, the restriction by the tumour of pancreatic secretion flow to the small intestine, or the consequences of pancreatic resection (Bartel 2015;Bruno 1998;Fieker 2011). In addition, people with pancreatic cancer lack the normal biphasic secretion pattern of pancreatic enzymes (Bartel 2015). It is notable that steatorrhoea does not usually occur until the secretion of lipase is less than 10% of normal (Löhr 2017).

PEI causes malabsorption and results in weight loss, malnutrition, and steatorrhoea (excess fat in the stool) (Vujasinovic 2017). The most accurate test for detecting steatorrhoea is the 72‐hour quantitative test. In this test, individuals consume 100 g of fat daily and the presence of at least 7 g of fat in the faeces is indicative of steatorrhoea; the presence of 15 g or more indicates severe steatorrhoea (Moss 2016; Struyvenberg 2017). The coefficient of fat absorption (CFA) (representing the percentage of fat absorbed) can be calculated from the results of the test (Dorsey 2010); a CFA below 93% is considered abnormal. This test is the only measure accepted by the US Food and Drug Administration and the European Medicines Agency for the monitoring of pancreatic enzyme replacement therapy (PERT) (Löhr 2017). The test requires the collection of the stool released over 72 hours, and is difficult, time‐consuming, and not well tolerated as a result of fat malabsorption‐related symptoms (MedlinePlus 2018; Moss 2016; Struyvenberg 2017). Other tests, which are considered less accurate, include the Sudan stain spot stool test and the steatocrit test. However, these tests are more practical than the 72‐hour quantitative test as they require only one random stool sample (Moss 2016).

The symptoms of PEI result from either the presence of undigested food in the intestinal lumen (steatorrhoea, abdominal bloating, and symptoms of dyspepsia) or the loss of nutrients (weight loss and fat‐soluble vitamin deficiency) (Vujasinovic 2017). Fat‐soluble vitamin deficiency symptoms include impaired night vision and xerophthalmia due to vitamin A deficiency, bleeding due to vitamin K deficiency, peripheral neuropathy and ataxia due to vitamin E deficiency, and osteoporosis and muscle spasms due to vitamin D deficiency (Löhr 2017).

PEI can result in a reduction in quality of life and impaired cognitive function, which can have adverse effects on an individual's ability to work (Löhr 2017). Cancer cachexia, characterised by a loss of skeletal muscle mass (sarcopenia) with or without a loss of fat mass, is common in individuals with pancreatic cancer, and is seen in up to 80% of affected individuals at death (Fearon 2011; Ozola 2015). Cancer cachexia is driven by low food intake and abnormal metabolism, and is associated with increased morbidity and mortality (Fearon 2011; Lucia 2012). Poor nutritional status is also related to the failure of an individual to complete chemotherapy. Furthermore, malnutrition can increase the toxicity of chemo‐ and radiotherapy, and lead to poor postoperative outcomes. Early nutritional management improves quality of life and outcomes in affected individuals (Akahori 2016; Di Luzio 2010).

A diagnosis of pancreatic cancer can be suggested by an individual's history and the findings of a physical examination. Serum bilirubin and alkaline phosphatase levels are also useful when achieving a diagnosis. Cancer or carbohydrate antigen (CA) 19‐9, a tumour marker, can also help with diagnosis and can provide an indication of the individual's prognosis after treatment. Diagnosis is usually confirmed using imaging, with dual‐phase helical computed tomography being the most sensitive test (Freelove 2006).

Small tumours that are not metastasised can usually be resected surgically. Whipple’s procedure is a well‐known surgical procedure for managing pancreatic cancers. It involves resection of the head of the pancreas, the duodenum, the distal stomach, the distal common bile duct, and the gall bladder, following which, the distal stomach, the pancreatic duct, and the common hepatic duct are anastomosed to the jejunum (Bowles 2001).

Although surgery is the main treatment for pancreatic cancer, chemotherapy and radiotherapy may also be of use. PERT is a suggested modality for the treatment of PEI and the associated malabsorption (Freelove 2006).

See Appendix 1 for a glossary of terms.

Description of the intervention

PERT has been widely used in the management of people with PEI. PERT involves the administration of pancreatic enzyme supplements, the rationale being to compensate the individual for the loss of normal pancreatic secretions. PERT decreases fat malabsorption, thus alleviating steatorrhoea, as well as pain and other undesirable symptoms associated with pancreatic insufficiency (Ferrone 2007).

Pancreatic enzyme supplements contain lipase, amylase, and protease, which assist in digesting lipids, proteins, and carbohydrates, respectively. Protection of these enzymes from destruction by gastric acid is essential. Hence, the enzymes are usually mixed with different delivery agents to protect the enzymes from premature destruction before arriving at their site of action. The timing of PERT administration is also important, as it is necessary for active enzymes to be present in the duodenum when food reaches it (Fieker 2011). Studies have shown that the size of particles contained in an enzyme formulation can impact the time taken for it to reach the duodenum, with 1.4 mm being the standard size for maximum efficacy (Fieker 2011; Meyer 1988). Nonetheless, the timing, the exact region where the enzymes are released, and the amount of enzymes released have not been well studied in humans (Fieker 2011; Meyer 1997).

The dose also plays an important role in therapy. Determining the appropriate dose of PERT to be administered depends on the amount of lipase in the preparation and should be adjusted for the person’s body weight and any improvements in clinical signs and symptoms during therapy (Fieker 2011). Nevertheless, there are currently no standard guidelines for determining the need for dose adjustment of PERT (Fieker 2011; Fragoso 2016).

Results across multiple studies on different PERT preparations indicate that PERT is generally safe at the therapeutic doses implemented in those studies: pancreatin (80000 lipase units per main meal and 40000 lipase units per snack); pancrelipase (6403.2 ±2671.4 units/kg/day); pancrelipase (72,000 lipase units per meal and 36,000 per snack) (Thorat 2012; Trapnell 2011; Whitcomb 2010).

How the intervention might work

The goal of PERT is to mimic normal pancreatic exocrine functions (Keller 2005). This may reduce the morbidity and mortality related to the malnutrition and the weight loss caused by maldigestion (Struyvenberg 2017). Some studies have shown PERT to improve fat absorption, maldigestion‐related symptoms and quality of life in individuals with PEI (British Guideline 2005; Damerla 2008; NCCN 2015).

Why it is important to do this review

Steatorrhoea is the leading symptom of PEI in people with pancreatic cancer. According to the results of some randomised controlled trials (RCTs), PERT has shown benefits in this population by reducing the fat in stools, and improving weight loss, digestion, and the absorption of protein and fat (Bruno 1998). Fat‐soluble nutrient deficiencies and digestive symptoms can affect people's adherence with chemotherapy and their quality of life (Armstrong 2002; Keim 2009). Administration of PERT in patients with PEI showed to be effective in reducing fat‐soluble‐nutrients deficiency by decreasing steatorrhea (Nakajima 2012). Guidelines strongly support the use of PERT in people with pancreatic cancer in order to maintain weight and increase quality of life (British Guideline 2005; Smith 2016). However, there are no robust, specific guidelines that reflect the impact of PERT on the morbidity, mortality, and quality of life of individuals with pancreatic cancer (postsurgical or inoperable) and steatorrhoea (Fieker 2011; Pezzilli 2013; Safdi 2006). This systematic review aims to assess the efficacy of PERT in managing steatorrhoea and its related problems in people with pancreatic cancer who experience major cancer‐ and cancer treatment‐related changes in the physiology and anatomy (and consequently pharmacology) of their gastrointestinal tract (Hirono 2015; Yuasa 2012).

Adherence to chemotherapy is vital; this is especially true in individuals with pancreatic cancer, as chemotherapy can be initiated at any stage of the disease (ACS 2016). The “outcomes of adherence may include decrease in health care costs; decrease disease exacerbations, crisis or relapse, increase in patient quality and preservation of life” (Wells 2015). Chemotherapy‐related adverse effects were one of the most prevalent causes of non‐adherence in several studies (Spoelstra 2011). These adverse events and other digestive symptoms affecting adherence may be reduced using PERT. Hence, the assessment of this and possibly other aspects of PERT use could contribute to an improvement in adherence to chemotherapy and, consequently, to an improvement in people's quality of life and outcomes.

The management of individuals with pancreatic cancer is highly costly due to the need for multiple therapies to control the tumour, extend survival, and palliate symptoms (Bardou 2013). It is therefore important to evaluate the cost of PERT as a therapy for steatorrhoea and malabsorption after the consideration of its benefits/harms.

Objectives

To evaluate the efficacy of PERT for the treatment of steatorrhoea in people with pancreatic cancer by accessing whether it:

  1. reduces the severity and duration of common symptoms, including fatty (greasy or oily appearance and residue), foul‐smelling, pale‐coloured, and heavy stools (bulky and difficult‐to‐flush), which are usually associated with weight loss and nutritional deficiencies as a result of fat malabsorption and the concomitant malabsorption of amino acids and vitamins, and abdominal pain or cramps (Cheifetz 2011; Kasper 2015);

  2. is an acceptable treatment, as assessed by the number of side effects/adverse events, study dropout rates, and participant satisfaction levels;

  3. has an impact on chemotherapy adherence;

  4. has an impact on postoperative outcomes.

Methods

Criteria for considering studies for this review

Types of studies

We will include all RCTs or quasi‐RCTs (“a trial in which randomisation is attempted but subject to potential manipulation, such as allocating participants by day of the week, date or birth, or sequence of entry into trial”) (CCCRG 2016).

We will include studies reported as full text, those published in abstract form only, and unpublished data, with no restrictions on blinding, publication status, or language.

Types of participants

We will include people with pancreatic cancer, diagnosed using any validated criteria, irrespective of gender, age, or ethnicity.

We will use the following inclusion criteria:

  1. clinical presentation (medical history, physical examination, and information from imaging, chemical, histological, and cellular studies) compatible with pancreatic cancer;

  2. steatorrhoea (see Background for definition).

We will include studies conducted in any healthcare setting.

We will exclude studies involving combined populations (i.e. people with pancreatic cancer along with those with chronic pancreatitis, cystic fibrosis, or any other people suffering from other diseases causing PEI) if they do not report results for individuals with pancreatic cancer separately.

Types of interventions

We will include the following types of study.

  1. Studies comparing PERT (single‐ or multi‐enzyme preparations, various coating methods (e.g. enteric or non‐enteric coatings) different pharmacological forms) versus placebo or no treatment.

  2. Studies comparing PERT versus fat restriction.

We will include studies investigating opiate usage as a cointervention provided that this is not a part of the randomised treatment, keeping in mind that it may hide the effects of exocrine insufficiency, which could complicate the detection and treatment of malabsorption (Imrie 2010); however, when opiates are used in one or more of the groups and not in others (treatment or control groups) we will exclude the study.

As mentioned above, we will include studies comparing PERT with fat restriction, which is a treatment for steatorrhoea. We will include trials that do not compare PERT with fat restriction, but which include the use of fat restriction in all groups; however, when fat restriction is used in one or more of the groups and not in others (treatment or control groups), we will exclude the study.

Types of outcome measures

Primary outcomes

Steatorrhoea: measured by any reduction in fat excretion; improvement in fat absorption; improvement in stool consistency or steatorrhoea severity, duration, and frequency, using any subjective reports (e.g. number of people reporting improvement in steatorrhoea), validated scales, clinical findings and/or laboratory parameters.

We will report the timing of outcome assessments, and conduct meta‐analyses using data from four time intervals: one month and less, one month to six months, six months to one year, and more than one year. We will use no more than one time point (the closest to the end of the interval) for each interval from each study for any particular outcome.

Secondary outcomes

  1. Malabsorption: measured by comparing the CFA and the coefficient of nitrogen absorption (CNA), or any other suitable chemical tests

  2. Reductions in symptoms, such as abdominal bloating, wind, and distension, reported by the participant; and abdominal pain measured by participants' or caregivers' reports, or any scales used for that purpose

  3. Weight change: measured by changes in body mass index or weight (in kilograms or pounds). We will pay attention to relative weight change

  4. Improvements in fat‐soluble vitamin deficiency‐related diseases (e.g. osteomalacia or any other related diseases), provided that these diseases occurred after the diagnosis of pancreatic cancer

  5. Quality of life: measured using the performance status or any validated scales used for that purpose

  6. Participant acceptability of therapy: measured by the number of side effects/adverse events, study dropout rates, and participant satisfaction levels

  7. Postoperative outcomes: mean or median survival, mortality rates, complication rates, length of stay, readmission rates, participant satisfaction, functional health status, and other measures of health‐related quality of life measured by any validated scales used for that purpose

  8. Chemotherapy adherence: preferably measured using the medication possession ratio (MPR), which is calculated as the number of days a participant was covered by their chemotherapy regimen, defined according to National Comprehensive Cancer Network (NCCN) guidelines, divided by the number of days elapsed from the first to the last infusion of that regimen (Seal 2016), or by any validated scales used for that purpose

  9. Adverse effects: all adverse events reported, irrespective of the severity of these events

  10. Economics outcomes: changes in the average cost of care per participant, measured by the change in need for artificial nutrition due to malabsorption or steatorrhoea (serums, vitamins, etc.), as well as changes in hospitalisation duration and costs due to malnutrition or malnutrition‐related causes, or both.

We will not regard the reporting of the outcomes listed here as an inclusion criterion for the review.

For the reduction of accompanying symptoms, we will report the timing of outcome assessments and will conduct meta‐analyses using data from four time intervals: six months and less, six months to one year, one year to three years, and more than three years. We will use no more than one time point (the closest to the end of the interval) for each interval from each study for any particular outcome.

For malabsorption, weight, and fat‐soluble vitamin deficiency‐related diseases, we will report the timing of outcome assessments and conduct meta‐analyses using data from four time intervals: one month and less, one month to six months, six months to one year, and more than one year. We will use no more than one time point (the closest to the end of the interval) for each interval from each study for any particular outcome.

Search methods for identification of studies

Electronic searches

We will conduct a literature search to identify all published and unpublished RCTs. We will construct the search strategies by using a combination of subject headings and text words relating to pancreatic cancer, steatorrhoea, and PERT. A preliminary search testing suggests that only a very small number of studies has been published that mention terms related to pancreatic cancer, steatorrhoea, and PERT (< 50 hits in MEDLINE). As we want to review all identified references including reviews, we will not apply a RCT filter on this search combination. To further increase the literature search sensitivity, we will also search any RCT that used terms related to pancreatic cancer and PERT in the abstract even if these studies do not mention terms relating to steatorrhoea in the abstract. We will apply the standard Cochrane search strategy filter for identifying RCTs to this supplemental search because a large of number of hits are found (> 1000 in MEDLINE). Hence, the final search strategy will combine terms related to: (pancreatic cancer AND steatorrhoea AND pancreatic enzyme therapy) OR (pancreatic cancer AND pancreatic enzyme therapy AND RCT filter). Will will not use an RCT filter for the search in the Cochrane Library (pancreatic cancer AND pancreatic enzyme therapy). We will apply no language restrictions. We will translate non‐English language papers and fully assess them for potential inclusion in the review, as necessary.

We will search the following electronic databases for identifying potential studies:

  • Cochrane Central Register of Controlled Trials (CENTRAL) (Appendix 2);

  • MEDLINE (1966 to present) (Appendix 3);

  • Embase (1988 to present) (Appendix 4); and

  • CINAHL (Cumulative Index to Nursing and Allied Health Literature; 1982 to present) (Appendix 5).

We will also conduct a search of ClinicalTrials.gov and the World Health Organization International Clinical Trials Registry Platform (www.who.int/ictrp/en/).

Searching other resources

We will handsearch the published abstracts from the conference proceedings published in Digestive Disease Week and United European Gastroenterology Week from 2011 to 2018. We will handsearch the references cited in studies found by the above search to identify further relevant studies. We will check the reference lists of all primary studies and review articles for additional references.  We will contact authors of identified studies and ask them to identify other published and unpublished studies. We will also contact manufacturers and experts in the field.

We will search for errata or retractions for any eligible studies and for studies that are not indexed by MEDLINE in PubMed (www.ncbi.nlm.nih.gov/pubmed) prior to publication of the review and report the date this was done within the review.

Data collection and analysis

Selection of studies

Four review authors (YHN, YA, YAD, and FA) will independently screen the titles and abstracts of all the potential studies we identify as a result of the search and code them as 'retrieve' (eligible or potentially eligible/unclear) or 'do not retrieve'. We will retrieve the full‐text study reports/publications and four review authors (YHN, YA, YAD, and FA) will independently screen the full text and identify studies for inclusion, and identify and record reasons for exclusion of any ineligible studies. We will resolve any disagreement through discussion or, if required, we will consult another review author (NAH). We will identify and exclude duplicates and collate multiple reports of the same study so that each study rather than each report is the unit of interest in the review. We will record the selection process in sufficient detail to complete a PRISMA flow diagram and a 'Characteristics of excluded studies' table.

Data extraction and management

We will use a standard data collection form for study characteristics and outcome data, adapted from the Cochrane Upper Gastrointestinal and Pancreatic Diseases website (Resources for Authors), which we will pilot on at least one study in the review. Four review authors (YHN, YA, YAD, and HAS) will extract study characteristics from included studies. We will extract the following study characteristics.

  1. Methods: study design, total duration study and run in, number of study centres and location, study setting, withdrawals, and date of study.

  2. Participants: number, age range, mean age, gender, severity of condition, diagnostic criteria, inclusion criteria, and exclusion criteria.

  3. Interventions: intervention (routes of delivery (e.g. oral or intravenous delivery), doses (e.g. amount or intensity of each treatment, frequency of delivery), timing (e.g. before, during, or after a meal), pharmacological form, length of treatment, comparisons, concomitant medications (antacids, etc.), excluded medications (when opiates are used in one or more of the groups and not in others (treatment or control groups)), excluded treatment (when fat restriction is used in one or more of the groups and not in others (treatment or control groups)).

  4. Outcomes: primary and secondary prespecified and collected outcomes at different time points.

  5. Notes: funding source of the study and potential conflicts of interest of the study authors.

Four review authors (YHN, YAD, YA, FA) will independently extract outcome data from included studies. We will note in a 'Characteristics of included studies' table whether outcome data were reported in an unusable way. We will resolve disagreements by consensus or by involving another review author (NAH). One review author (YA) will copy across the data from the data collection form into Review Manager 5 (RevMan 5) (RevMan 2014). Each review author (YHN, YAD, YA, FA) will double check that the data are entered correctly by comparing the study reports with the data presented in the systematic review. A review author (NAH) will spot‐check study characteristics for accuracy against the study report.

Assessment of risk of bias in included studies

Four review authors (YHN, YA, YAD, and HAS) will independently assess the risk of bias for each study using the criteria outlined in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011). Any disagreement will be resolved by discussion or by involving a fifth review author (NAH). For individually randomised studies we will assess the risk of bias according to the following domains.

Random sequence generation

  • Low risk of bias if there was a random component in the sequence generation process, such as referring to a random number table or using a computer random number generator

  • High risk of bias if selection was based on participant numbers, birth dates, visit dates, or alternative allocation. We will exclude studies in which selection was based on participant or clinical preferences, or used a mechanism that cannot be described as random. We will also exclude studies that do not state whether the treatment was randomly allocated

  • Unclear risk of bias if there was insufficient information about the sequence generation process to permit a judgement of ‘low risk’ or ‘high risk’

Allocation concealment

  • Low risk of bias if participants and investigators enrolling participants could not foresee assignment because one of the following was used to conceal allocation or an equivalent method

    1. Central allocation (including telephone, web‐based and pharmacy‐controlled randomisation)

    2. Sequentially numbered drug containers of identical appearance

    3. Sequentially numbered, opaque, sealed envelopes

  • High risk of bias if participants or investigators enrolling participants could possibly foresee assignments and thus introduce selection bias, such as allocation based on:

    1. use of an open random allocation schedule (e.g. a list of random numbers)

    2. use of assignment envelopes without appropriate safeguards (e.g. if envelopes were unsealed or non‐opaque or not sequentially numbered)

    3. alternation or rotation

    4. date of birth

  • Unclear risk of bias if there was insufficient information to permit a judgement of ‘low risk’ or ‘high risk’

Blinding of participants and personnel

  • Low risk of bias if blinding of participants and key study personnel was ensured, and it was unlikely that the blinding could have been broken

  • High risk of bias if blinding of key study participants and personnel was attempted, but it was likely that the blinding could have been broken, and the outcome was likely to be influenced by lack of blinding; or if there was no blinding of key study participants and personnel

  • Unclear risk of bias if there was insufficient information to permit a judgement of ‘low risk’ or ‘high risk’; or the study did not address this outcome

Blinding of outcome assessment

  • Low risk of bias if blinding of outcome assessment was ensured, and it was unlikely that the blinding could have been broken

  • High risk of bias if blinding of outcome assessment was attempted, but it was likely that the blinding could have been broken, and the outcome measurement was likely to be influenced by lack of blinding; or if there was no blinding of outcome assessment

  • Unclear risk of bias if there was insufficient information to permit a judgement of ‘low risk’ or ‘high risk’; or if the study did not address this outcome

Incomplete outcome data

  • Low risk of bias if there were no missing outcome data, reasons for missing outcome data were unlikely to relate to the true outcome, missing outcome data were balanced in numbers across intervention groups with similar reasons for missing data across the groups, the proportion of missing outcomes compared with the observed event risk was not enough to have a clinically relevant impact on the intervention effect estimate, and missing data were imputed using appropriate methods

  • High risk of bias if reasons for missing outcome data were likely to be related to the true outcome with either an imbalance in numbers or reasons for missing data across intervention groups, the proportion of missing outcomes compared with observed event risk was enough to induce clinically relevant bias in the intervention effect estimate, and the potentially inappropriate application of simple imputation

  • Unclear risk of bias if there was insufficient reporting of attrition and exclusions to permit a judgement of ‘low risk’ or ‘high risk’ (e.g. number randomised not stated, no reasons for missing data provided)

Selective outcome reporting

  • Low risk of bias if the published reports included all expected outcomes, including those that were prespecified

  • High risk of bias if not all of the study’s prespecified primary outcomes were reported; if one or more primary outcome was reported using measurements, analysis methods, or subsets of the data that were not prespecified; one or more reported primary outcomes were not prespecified; one or more outcomes of interest were reported incompletely; or the study report failed to include results for a key outcome that would be expected to have been reported for such a study

  • Unclear risk of bias if there was insufficient information to permit a judgement of 'low risk' or 'high risk'

Other bias

  • Low risk of bias if the study appears to be free of other sources of bias

  • High risk of bias if there was at least one important risk of bias (e.g. the study had a potential source of bias related to the specific study design used, or has been claimed to have been fraudulent, or had some other problem)

For cluster randomised trials we will assess the risk of bias according to the following domains (Higgins 2011).

  • Recruitment bias.

  • Baseline imbalance.

  • Loss of clusters.

  • Incorrect analysis.

  • Comparability with individually randomised trials.

For cross‐over trials we will assess the risk of bias according to the following domains (Higgins 2011).

  • Whether the cross‐over design was suitable.

  • Whether there was a carry‐over effect.

  • Whether only first period data are available.

  • Incorrect analysis.

  • Comparability of results with those from parallel‐group trials.

We will grade the risk of each potential source of bias as high, low, or unclear and provide a quote from the study report together with a justification for our judgement in a 'Risk of bias' table. We will summarise the 'Risk of bias' judgements across different studies for each of the domains listed. We will consider blinding separately for different key outcomes where necessary (e.g. for an unblinded outcome assessment, the risk of bias for all‐cause mortality may be very different than for a participant‐reported pain scale). Where information on risk of bias relates to unpublished data or to correspondence with trialists, we will note this in the 'Risk of bias' table.

When considering treatment effects, we will take into account the risk of bias in the studies that contribute to that outcome.

Assessment of bias in conducting the systematic review

We will conduct the review according to this published protocol and report any deviations from it in the 'Differences between protocol and review' section of the systematic review.

Measures of treatment effect

We will analyse dichotomous variables (e.g. improvement in steatorrhoea, reductions in symptoms and improvements in fat‐soluble vitamin deficiency‐related diseases) using risk ratios with 95% confidence intervals. For continuous variables (e.g. measuring weight change, malabsorption, abdominal pain and costs) we will calculate mean differences with 95% confidence intervals. We will use standardised mean differences with 95% confidence intervals for quality of life or any other continuous variable if studies used different scales. We will ensure that higher scores for continuous outcomes have the same meaning for each particular outcome, explain the direction to the reader, and report where the directions were reversed, if this was necessary. For count outcomes, such as the number of adverse events, we will calculate the rate ratios with 95% confidence intervals.

We will undertake meta‐analyses only where this is meaningful (i.e. if the treatments, participants, and the underlying clinical question are sufficiently similar for pooling to make sense).

A common way that trialists indicate the presence of skewed data is the reporting of medians and interquartile ranges. When we encounter this we will note that the data are skewed and consider the implications of this.

Unit of analysis issues

The unit of analysis will be the individual participant with pancreatic cancer suffering from steatorrhoea.

We will consider special issues in the analysis of studies with non‐standard designs as follows.

Cluster‐randomised studies

If cluster‐randomised trials are identified, we will obtain the effect estimate adjusted for the clustering effect. If this is not available, we will perform a sensitivity analysis by excluding the study from the meta‐analysis, as the variance of the effect estimate unadjusted for the cluster effect is less than the actual variance, giving inappropriately more weight to the cluster‐RCT in the meta‐analysis.

Multiple intervention groups and multiple trial arms

If any RCT has multiple intervention groups, we will analyse all possible pairs of treatments in different meta‐analyses. Where multiple trial arms are reported in a single study, we will include only the relevant arms. If two comparisons must be entered into the same meta‐analysis, we will halve the control group across the analysis to avoid double‐counting.

Cross‐over randomised trials

With regards to cross‐over randomised trials, we will incorporate cross‐over trials in a meta‐analysis by analysing all measurements as if the study was a parallel‐group trial only if it can be demonstrated that the results approximate those from a paired analysis.

Dealing with missing data

We will contact investigators or study sponsors in order to verify key study characteristics and obtain missing numerical outcome data where possible (e.g. when a study is published in abstract form only).

For dichotomous variables we will perform an intention‐to‐treat analysis whenever possible, which will include all participants randomised to a study irrespective of what happened subsequently (Higgins 2011; Lewis 1993; Newell 1992). This will involve imputing outcomes for the missing participants and we will assume that all missing participants did not experience the desired outcome (reduction in steatorrhoea and related symptoms). If this is not possible, we will conduct a per‐protocol analysis (an analysis of the results of only those participants who completed the study and who complied with (or received some of) their allocated intervention (in this review, PERT)) (Higgins 2011); we will, however, assess the impact of the worst‐ and best‐case scenarios on the results in the sensitivity analysis. For continuous outcomes, we will perform an available‐case analysis. If we are unable to obtain the necessary information from the investigators or study sponsors, we will impute the mean from the median (i.e. consider the median as the mean) and the standard deviation from the standard error, interquartile range, or P values, according to guidance in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011); we will, however, assess the impact of including such studies using a sensitivity analysis. If we are unable to calculate the standard deviation from the standard error, interquartile range, or P values, we will impute the standard deviation as the highest standard deviation in the remaining studies included in the outcome, being fully aware that this method of imputation will decrease the weight of a study in a meta‐analysis of mean differences and will shift the effect estimate towards no effect for standardised mean differences. We will assess the impact of including such studies using a sensitivity analysis.

Assessment of heterogeneity

We will test heterogeneity using:

  1. the Chi² test, with significance set at P < 0.1;

  2. the I² statistic (Higgins 2003), which can be interpreted as the percentage of variation observed between the studies that is attributable to between‐study differences rather than sampling error (chance) (Higgins 2011); we will consider an I² statistic greater than 50% as indicative of high‐level heterogeneity. We will recognise that there is uncertainty in the I² statistic when there are few studies in a meta‐analysis;

  3. Tau², which represents an estimate of the between‐study variance in a random‐effects meta‐analysis (Higgins 2011). If Tau² is similar to the treatment effect we will conclude that the heterogeneity is very high.

If we find high levels of heterogeneity (I² > 50%, or Tau² is similar to the treatment effect) for our primary outcomes, we will explore possible sources of heterogeneity using the sensitivity and subgroup analyses described below.

Assessment of reporting biases

We will attempt to contact study authors asking them to provide missing outcome data. Where this is not possible, and the missing data are thought to introduce serious bias, we will explore the impact of including such studies in the overall assessment of results using a sensitivity analysis

If we are able to pool more than 10 studies, we will create and examine a funnel plot to explore possible publication biases.

We will consider reporting biases (publication, time lag, duplicate publication, location, citation, language, and outcome reporting) at all points of both the data analysis and the interpretation. If sufficient numbers of RCTs are found in a particular field, attempts will be made to analyse the studies for publication bias using funnel plots, bearing in mind that publication bias does not necessarily cause asymmetry (Egger 1997; Macaskill 2001). We will consider a P value of less than 0.05 statistically significant for reporting bias.

Data synthesis

We will perform the analysis using RevMan 2014. We will use both a fixed‐effect model and a random‐effects model for the analysis. For subgroup analyses, if the studies are found to be homogeneous (in terms of age, diagnostic subtype, intervention type, intervention duration) we will use a fixed‐effect model; if they are found to be heterogeneous we will perform a random‐effects model. In case of discrepancies between the two models, we will report both results.

  • We will summarize dichotomous (binary) variables (e.g. proportion of participants who develop side effects) using risk ratios.

  • We will summarize continuous data using the mean difference when studies use the same scale. We will use the standardised mean difference to measure the difference between groups in studies that use different scales

  • We will summarize ordinal outcomes data and scales as dichotomous data for short scales and continuous data for long scales

  • When studies have a multifactorial design comparing multiple intervention groups, we will extract data and assign them to the relevant intervention group. We will treat each intervention group independently within our analysis

'Summary of findings' table

We will create a 'Summary of findings' table for each of the following comparisons: 1. PERT (single‐ or multi‐enzyme preparations, enteric‐coated or non‐enteric coated, different pharmacological forms) versus placebo or no treatment; and 2. PERT versus fat restriction. We will include the outcomes: steatorrhoea, malabsorption, reduction of accompanying symptoms, weight change, chemotherapy adherence, quality of life, and adverse effects. We will use the five GRADE considerations (study limitations, consistency of effect, imprecision, indirectness, and publication bias) to assess the quality of the body of evidence as it relates to the studies that contribute data to the meta‐analyses for the prespecified outcomes (GRADE 2013). We will use the methods and recommendations described in Section 8.5 and Chapter 12 of the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011) and by using GRADEpro software (GRADEproGDT). We will justify all decisions to down‐ or upgrade the quality of studies using footnotes and make comments to aid readers' understanding of the review where necessary. We will consider whether there is any additional outcome information that we were unable to incorporated into the meta‐analyses, note this in the comments and state whether it supports or contradicts the information from the meta‐analyses.

Subgroup analysis and investigation of heterogeneity

We plan to carry out the following subgroup analyses.

  • PERT in participants with unresectable or resectable cancers prior to the Whipple procedure as one group versus participants after the Whipple procedure as another group. This is because the procedure is greatly invasive and its malabsorption consequences could be a result of many factors other than the loss of pancreatic enzymes.

  • Coadministration of antacids and various PERT preparations versus various PERT preparations alone, to allow for the change in pH level in the stomach associated with antacids that could affect PERT efficacy (Vecht 2006).

  • Different administration schedules (before, with, or after meals), to allow for their effect on the therapeutic efficacy of PERT, considering that the change in the timing of the arrival of PERT with chymus in the duodenum could affect PERT efficacy (Dominguez‐Munoz 2005).

  • Doses of 25,000 or lower lipase units per main meal versus doses of more than 25,000 lipase units per main meal (Struyvenberg 2017).

We will use steatorrhoea as the outcome in subgroup analyses.

We will use the formal statistical test for heterogeneity across subgroups based on the random‐effects model to test for subgroup interactions (Borenstein 2008) and we will use caution in the interpretation of subgroup analyses, as advised in Section 9.6 of the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011). We will compare the magnitude of the effects between the subgroups by assessing the overlap of the confidence intervals of the summary estimate (non‐overlap of the confidence intervals indicates statistical significance).

Sensitivity analysis

We will perform sensitivity analyses defined a priori to assess the robustness of our conclusions. These will involve:

  • excluding studies at unclear or high risk of bias (one or more of the 'Risk of bias' domains classified as unclear or high, including: methods used for randomisation, allocation to interventions, blinding or missing data);

  • excluding those at unclear or high risk of bias for sequence generation (e.g. quasi‐RCTs);

  • making different hypotheses on any imputed data (e.g. excluding studies in which either means or standard deviations, or both are imputed);

  • excluding cluster RCTs in which the adjusted effect estimates are not reported;

  • excluding studies published in abstract form only;

  • excluding studies of low statistical power;

  • excluding unpublished studies;

  • excluding studies funded by industry;

  • comparing summary statistics (risk ratios versus odds ratios) by calculating a risk ratio for the desired outcome (no steatorrhoea and malabsorption after PERT therapy); if the risk ratio is close to one, we will compare this with the odds ratio to analyse sensitivity;

  • comparing meta‐analysis modelling (fixed‐effect versus random‐effects);

  • evaluating the influence of missing data on the results (intention‐to‐treat analysis versus per‐protocol analysis);

  • performing a best‐case, worst‐case type analysis in which all missing participants in one arm are assumed to have had the outcome of interest and all missing participants in the other arm are assumed to have not had the outcome, and vice‐versa.

We will report the results from the sensitivity analyses in a summary table and produce a summary table detailing decisions made during the process of conducting the review and the potential impact of these decisions on the findings. We will address significant decisions in the 'Discussion' section of the review.

Reaching conclusions

We will base our conclusions for this review only on findings from the quantitative or narrative synthesis of included studies. We will avoid making recommendations for practice and our implications for research will give the reader a clear sense of where the focus of any future research in the area should be and what the remaining uncertainties are.