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Taxane‐based chemohormonal therapy for metastatic hormone‐sensitive prostate cancer

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Abstract

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

To assess the effects of immediate taxane‐based chemohormonal therapy for newly diagnosed metastatic hormone‐sensitive prostate cancer.

Background

Description of the condition

Prostate cancer is the most frequently diagnosed cancer amongst men in high‐income countries and causes over 300,000 deaths worldwide (Torre 2015). In the US, prostate cancer accounts for one in five new diagnoses of all cancers and is the second leading cause of cancer death amongst men (Siegel 2016). Most prostate cancers tend to be localized at the time of diagnosis and are managed with active monitoring/surveillance, radical surgery or radiation therapy (Hamdy 2016). However, a subgroup of men experience local or distant disease recurrence after local therapy. The eight‐year risk of metastases following radical prostatectomy is 3% and following external beam radiation therapy is 7% (Zelefsky 2010). Approximately 16% of men present with regional or distant‐stage disease at the time of initial diagnosis (Siegel 2016). Therefore, the burden of advanced prostate cancer is considerable.

Since Huggins and colleagues elucidated the androgen‐dependent nature of prostate cancer, androgen deprivation therapy has underpinned the management of locally advanced and metastatic hormone‐sensitive prostate cancer (Huggins 1941). Although androgen deprivation therapy demonstrates antitumour activity with marked reduction of the prostate‐specific antigen (PSA) in the majority of men, it is not curative. Most men eventually experience progression of their cancer despite ongoing hormone treatment, which is a lethal disease state referred to as castration‐resistant prostate cancer. This progression occurs after a mean of 11 months on androgen deprivation therapy (James 2015). The mechanisms involved in the progression of disease are not entirely understood and currently thought to be a multifactorial process that facilitates androgen receptor activity through amplification, mutations, splice variants and aberrant activation (Tilki 2016). Once in this resistant state, men face a poor prognosis with a pooled median survival of 14 months (Kirby 2011). Additionally, castration‐resistant disease is associated with considerable morbidity and a negative impact on quality of life. It has been reported that 45% of men were burdened by bone pain at the time of diagnosis with this lethal disease state (Inoue 2009). At a mean follow‐up of 18 months, 80% of men experienced bone pain. Moreover, increased incidence of major skeletal events, such as vertebral collapse, fractures and spinal cord compression, is evident with disease progression (Berruti 2005).

The landscape of advanced prostate cancer treatment has undergone considerable transformation since the early 2000s prior to which no treatment had been shown to confer a survival benefit. Early randomized trials that examined the role of chemohormonal therapy using chemotherapeutic agents such as epirubicin (Pummer 1997), estramustine (Janknegt 1997), cyclophosphamide (Murphy 1983), or a combination of ketoconazole plus doxorubicin alternating with vinblastine plus estramustine demonstrated no improvement in survival (Millikan 2008). However, there was a landmark discovery in 2004 when two studies reported prolonged overall survival in men with metastatic castration‐resistant cancer administered docetaxel (Petrylak 2004; Tannock 2004). Since the US Food and Drug Administration approval for the use of docetaxel in metastatic disease, a number of other agents have entered the market such as abiraterone acetate (de Bono 2011; Ryan 2015), enzalutamide (Beer 2014; Scher 2012), carbazitaxel (de Bono 2010), and sipuleucel‐T (Kantoff 2010). The seminal findings with docetaxel laid the foundation to revisit the concept of upfront chemohormonal therapy utilizing these newer agents to improve the efficacy of androgen deprivation therapy and thus potentially delay progression of androgen‐dependent disease to its lethal castration‐resistant form. The newer drugs have all focused on men with castration‐resistant prostate cancer; however, this has changed with the introduction of docetaxel earlier in the disease stage concomitantly with the time of systemic androgen ablation.

Description of the intervention

Docetaxel is a second‐generation taxane chemotherapeutic agent that is derived from 10‐deacetylbaccatin III obtained from European yew tree needles (Taxus baccata) (Engels 2005). It is currently approved for use in a range of advanced cancers including metastatic castration‐resistant prostate cancer. In this latter setting, docetaxel is administered as a 75 mg per square meter of body surface intravenous infusion every 21 days. This is prescribed in combination with oral prednisolone 5 mg twice daily.

At standard doses, docetaxel has been reported to have linear pharmacokinetics with a mean half‐life of 11 hours. In plasma, over 90% of the drug is bound to α1‐acid glycoprotein, albumin and lipoproteins. The concentration of α1‐acid glycoprotein has been demonstrated to have the most impact on both clearance and the amount of unbound, pharmacologically active substance. The drug is primarily metabolized through hepatic CYP3A pathways with metabolites eliminated in the feces and urine (Loos 2003). Therefore, medications that induce CYP3A activity, such as antiepileptic drugs, decrease the efficacy of docetaxel. In contrast, drugs that inhibit hepatic enzymes decrease clearance.

Adverse effects of the intervention

Phase I trials demonstrated that the dose‐limiting toxicity of docetaxel was neutropenia (Taguchi 1994). Just under one‐third (32%) of the group receiving docetaxel every three weeks in the TAX 327 study reported grade 3 or 4 neutropenia (Tannock 2004). Other severe complications experienced include anemia, thrombocytopenia and fatigue. One in 10 men had impaired left ventricular function following treatment. Furthermore, over one‐half of the group reported fatigue (53%) and alopecia (65%). There was no significant trend to decreased adverse events with weekly docetaxel therapy compared to dosing every three weeks. Meanwhile, Petrylak and colleagues found that men administered docetaxel plus estramustine displayed higher incidences of febrile neutropenia, cardiovascular events, nausea and vomiting, metabolic disturbances and neurologic events compared to men who received mitoxantrone plus prednisone (Petrylak 2004). However, there was no significant difference of grade 3 or greater neutropenia between the groups. It is important to note the adverse event outcomes reported in these trials may not be truly representative of routine clinical practice. It was observed that men with metastatic castration‐resistant prostate cancer who received docetaxel while enrolled in a clinical trial, including TAX 327 (Tannock 2004), were younger, had a better performance status and experienced less toxicity from their treatment than men managed out of a trial protocol (Templeton 2013).

How the intervention might work

Taxanes bind to tubulin on microtubules and result in increased polymerization and thus interferes with mitosis. Microtubules are protein polymers which are an integral component of the cytoskeleton and have several functions including cell signaling, translocation of cellular cargo and cell division. They are essential for nearly all steps of mitosis as they are involved in the attachment of chromosomes to the spindle, congression and synchronous separation during anaphase and telophase. It has been shown that even a single chromosome unable to attach to a spindle is sufficient to induce cell cycle arrest and the cell subsequently undergoes apoptosis (Jordan 1996).

Publications have proposed that taxanes also interact with the androgen receptor in neoplastic prostate cells (Darshan 2011, Gan 2009). Using tissue microarrays, it has been demonstrated that treatment with docetaxel results in significant decrease of ligand‐induced androgen receptor nuclear translocation (Zhu 2010). This subsequently results in a reduction of androgen receptor transcriptional activity measured by PSA messenger ribonucleic acid (mRNA) expression. These two mechanisms of decreased androgen receptor activity and cell cycle arrest are hypothesized to slow the growth and progression of metastatic prostate cancer.

Delaying the development of castration‐resistant prostate cancer has important implications. Aside from the survival advantage, men are able to maximize their quality of life by delaying the morbidity associated with castration‐resistant disease and the need for further treatment which have potential adverse events. Moreover, administration of chemotherapy during the early stages of metastatic prostate cancer, rather than after progression to a castration‐resistant state, has its own benefits. The higher disease burden and subsequent overall decline in functional status that is experienced with the development of castration‐resistant prostate cancer will exclude a sizable proportion of men from even receiving chemotherapy at this late stage. Furthermore, the typically superior health status of men during the early stages of metastatic prostate cancer diagnosis enhances their capacity to withstand the toxicities of chemotherapy.

Why it is important to do this review

Immediate chemotherapy is beginning to be widely used to treat men with newly diagnosed metastatic prostate cancer, representing a paradigm shift in the management of these men. This is reflected in current clinical practice guidelines such as those of the National Cancer Center Network (Mohler 2017), European Society of Medical Oncology (Parker 2015), and European Association of Urology (Cornford 2017), with major implications for clinical care pathways and resource utilization. Guidelines differ in their recommendations as to whether all men with metastatic prostate cancer should receive upfront chemotherapy, or only men with higher volume disease.

Several systematic reviews exist that have sought to critically appraise the entire body of trial evidence addressing this question. Tucchi and colleagues attempted to answer this question, but neither assessed the benefit of upfront chemotherapy on disease‐specific survival or used a GRADE approach to evaluate the evidence (Tucci 2016). Similar shortcomings are evident in the other two systematic reviews on the topic (Botrel 2016; Vale 2016). Therefore, this Cochrane Review will aim to critically evaluate the evidence in a prescribed manner and focus on outcomes that are important to men with metastatic hormone‐sensitive prostate cancer using the most methodologically rigorous approach.

Objectives

To assess the effects of immediate taxane‐based chemohormonal therapy for newly diagnosed metastatic hormone‐sensitive prostate cancer.

Methods

Criteria for considering studies for this review

Types of studies

We will include randomized or quasi‐randomized trials regardless of their publication status or language of publication. We will exclude cluster and cross‐over randomized studies.

Types of participants

We will include studies that enrolled men with a confirmed histological diagnosis of adenocarcinoma of the prostate and radiologic evidence of metastases as determined by cross‐sectional imaging (computer tomography (CT), magnetic resonance imaging (MRI), positron emission tomography (PET)) with or without bone scans. This will include both men who have and have not undergone local therapy. Only men receiving taxane‐based chemotherapy for their prostate cancer will be included. Men will be required to have commenced chemotherapy within 120 days of beginning androgen deprivation therapy to be considered as receiving upfront combination therapy. Men who had previously received adjuvant or neoadjuvant androgen deprivation therapy will be permitted in the study if the development of metastases occurred at least 12 months following cessation of hormone therapy. Men receiving concurrent osteoprotective therapy (e.g. bisphosphonates) will also be eligible.

We will exclude men with advanced prostate cancer who received chemotherapy without known metastases and who received prior chemotherapy of any agent for their prostate cancer.

Types of interventions

We will consider the following interventions.

Concomitant interventions will have to be the same in the experimental and comparator groups to establish fair comparisons.

Experimental interventions

  • Taxane‐based chemotherapy in combination with androgen deprivation therapy (using methods outlined under 'Comparator intervention' below).

Comparator interventions

  • Androgen deprivation therapy only (using luteinizing hormone‐releasing hormone agonist or antagonist; combination of antiandrogen plus luteinizing hormone‐releasing hormone agonist (maximum androgen blockade) or bilateral orchiectomy).

Types of outcome measures

We will not use the measurement of the outcomes assessed in this review as an eligibility criterion.

Primary outcomes

  • Time‐to‐death due to any cause.

  • Serious adverse events.

Secondary outcomes

  • Time‐to‐death due to prostate cancer.

  • Time‐to‐progression.

  • Discontinuation due to adverse events.

  • All adverse events.

  • Quality of life.

Method and timing of outcome measurement

  • Time‐to‐death due to any cause will be the time from randomization until death from any cause.

  • Serious adverse events will be grade 3 to 5 adverse events according to the Common Toxicity Criteria (CTCAE) v3.0 occurring at any time during treatment; such as sudden death, neutropenia, febrile neutropenia, fatigue, gastrointestinal disorders (including diarrhea, constipation and vomiting), stomatitis, neuropathy, thromboembolism, thrombocytopenia or renal impairment.

  • Time‐to‐death due to prostate cancer will be the time from randomization until death from prostate cancer.

  • Time‐to‐progression will be the time from randomization until clinical, biochemical or radiographic progression.

  • Discontinuation due to adverse events will be the number of participants ceasing treatment due to an adverse event caused by the treatment.

  • All adverse event will include all grades of adverse events measured by CTCAE v3.0.

  • Overall quality of life as measured by validated instruments such as the 12‐item Short Form (SF‐12), 36‐item Short Form (SF‐36) or Functional Assessment of Cancer Therapy (FACT) questionnaire.

If we are unable to retrieve the necessary information to analyze time‐to‐event outcomes, we will assess the number of events per total for dichotomized outcomes at one, three and five years after commencing chemohormonal therapy.

Search methods for identification of studies

We will perform a comprehensive search with no restrictions on the language of publication or publication status. We plan to rerun searches within three months prior to anticipated publication of the review.

Electronic searches

We will search the following sources from inception of each database.

  • The Cochrane Library:

    • Cochrane Database of Systematic Reviews (CDSR);

    • Cochrane Central Register of Controlled Trials (CENTRAL);

    • Database of Abstracts of Reviews of Effects (DARE);

    • Health Technology Assessment Database (HTA).

  • MEDLINE (PubMed).

  • Embase (Ovid).

We will also search the following.

If we detect additional relevant key words during any of the electronic or other searches, we will modify the electronic search strategies to incorporate these terms and document the changes.

Searching other resources

We will try to identify other potentially eligible trials or ancillary publications by searching the reference lists of retrieved included trials, reviews, meta‐analyses and health technology assessment reports. We will also contact study authors of included trials to identify any further studies that we may have missed. We will contact drug/device manufacturers for ongoing or unpublished trials.

We will search abstract proceedings of relevant meetings (American Urological Association, European Urological Association, American Society of Clinical Oncology, European Society of Medical Oncology) from 2013 to 2017 for unpublished studies.

Data collection and analysis

Selection of studies

We will use reference management software (e.g. RefWorks, EndNote) to identify and remove potential duplicate records and then import these references into Covidence, a web‐based program for systematic review development. When more than one report of the same trial is available, we will include the most up‐to‐date publication in the analysis. In the event that a study has more than one publication, we will group publications so that each study, rather than each publication, is the unit of interest. Two review authors (NS, YP) will independently scan the abstract, title, or both, of remaining records retrieved, to determine which studies should be assessed further. Two review authors (NS, YP) will investigate all potentially relevant records as full text, map records to studies, and classify studies as included studies, excluded studies, studies awaiting classification or ongoing studies in accordance with the criteria for each provided in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011a). We will resolve any discrepancies through consensus or recourse to a third review author (PD). If resolution of a disagreement is not possible, we will designate the study as 'awaiting classification' and we will contact study authors for clarification. We will document reasons for exclusion of studies that may have reasonably been expected to be included in the review in a 'Characteristics of excluded studies' table. We will present an adapted PRISMA flow diagram showing the process of study selection (Liberati 2009).

Data extraction and management

We will develop a dedicated data abstraction form that we will pilot test ahead of time.

For studies that fulfil inclusion criteria, two review authors (NS, YP) will independently abstract the following information, which we will provide in the 'Characteristics of included studies' table.

  • Study design.

  • Study dates (if dates are not available then this will be reported as such).

  • Study settings and country.

  • Participant inclusion and exclusion criteria (including participant comorbidities, disease stage, pretreatment).

  • Participant details, baseline demographics (including participant age, disease stage).

  • Number of participants by study and by study arm.

  • Details of relevant experimental and comparator interventions (including dose, route, frequency and duration).

  • Definitions of relevant outcomes, and method and timing of outcome measurement as well as any relevant subgroups.

  • Study funding sources.

  • Declarations of interest by primary investigators.

We will extract outcomes data relevant to this Cochrane Review as needed for calculation of summary statistics and measures of variance. For dichotomous outcomes such as adverse events, we will attempt to obtain numbers of events and totals for population of a 2 × 2 table, as well as summary statistics with corresponding measures of variance. For continuous outcomes such as quality of life scores, we will attempt to obtain means and standard deviations or data necessary to calculate this information. For time‐to‐event outcomes, we will extract the hazard ratio (HR) from published data according to Parmar 1998 and Tierney 2007 with corresponding measures of variance or data necessary to calculate this information.

We will resolve any disagreements by discussion, or, if required, by consultation with a third review author (AL).

We will provide information, including trial identifier, about potentially relevant ongoing studies in a 'Characteristics of ongoing studies' table.

We will attempt to contact authors of included studies to obtain key missing data as needed.

Dealing with duplicate and companion publications

In the event of duplicate publications, companion documents or multiple reports of a primary study, we will maximize yield of information by mapping all publications to unique studies and collating all available data. We will use the most complete data‐set aggregated across all known publications. In case of doubt, we will give priority to the publication reporting the longest follow‐up associated with our primary or secondary outcomes.

Assessment of risk of bias in included studies

Two review authors (NS, YP) will assess the risk of bias of each included study independently. We will resolve disagreements by consensus, or by consultation with a third review author (PD).

We will assess risk of bias using Cochrane's 'Risk of bias' assessment tool (Higgins 2011b). We will assess the following domains.

  • Random sequence generation (selection bias).

  • Allocation concealment (selection bias).

  • Blinding of participants and personnel (performance bias).

  • Blinding of outcome assessment (detection bias).

  • Incomplete outcome data (attrition bias).

  • Selective reporting (reporting bias).

  • Other sources of bias.

We will judge risk of bias domains as 'low risk,' 'high risk' or 'unclear risk' and will evaluate individual bias items as described in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011b). We will present a 'Risk of bias' summary figure to illustrate these findings.

For performance bias (blinding of participants and personnel) and detection bias (blinding of outcome assessment), we will evaluate the risk of bias separately for each outcome, and we will group outcomes according to whether measured subjectively or objectively when reporting our findings in the 'Risk of bias' tables. For performance bias, we will judge all outcomes to be similarly susceptible and rate them in one group.

We will define the following endpoints as subjective outcomes.

  • Disease‐specific survival.

  • Progression‐free survival.

  • Major adverse events.

  • Mild adverse events.

  • Quality of life.

We will define the following endpoint as an objective outcome.

  • Overall survival.

We will assess attrition bias (incomplete outcome data) on an outcome‐specific basis, and will present the judgment for each outcome separately when reporting our findings in the 'Risk of bias' tables. If appropriate, we will create groups of outcomes with similar reporting characteristics (e.g. major adverse events and mild adverse events) to facilitate both the risk of bias ratings and presentation.

We will further summarize the risk of bias across domains for each outcome in each included study, as well as across studies and domains for each outcome, in accordance with the approach for summary assessments of the risk of bias presented in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011b).

Measures of treatment effect

We will express dichotomous data as risk ratios (RRs) with 95% confidence intervals (CIs). We will express continuous data as mean differences (MDs) with 95% CIs unless different studies use different measures to assess the same outcome, in which case we will express data as standardized mean differences with 95% CIs. We will express time‐to‐event data as HRs with 95% CIs. We will analyse the data using RevMan 5 software (RevMan 2014).

Unit of analysis issues

The unit of analysis will be the individual participant. Should we identify trials with more than two intervention groups for inclusion in the review, we will handle these in accordance with guidance provided in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011c). We will exclude cross‐over trials and cluster‐randomized trials.

Dealing with missing data

We will obtain missing data from study authors, if feasible, and will perform intention‐to‐treat (ITT) analyses if data are available; we will otherwise perform available‐case analyses. We will investigate attrition rates (e.g. dropouts, losses to follow‐up and withdrawals), and will critically appraise issues of missing data. We will not impute missing data.

Assessment of heterogeneity

In the event of excessive heterogeneity unexplained by subgroup analyses, we will not report outcome results as the pooled effect estimate in a meta‐analysis but will provide a narrative description of the results of each study.

We will identify heterogeneity (inconsistency) through visual inspection of the forest plots to assess the amount of overlap of CIs, and the I2 statistic, which quantifies inconsistency across studies to assess the impact of heterogeneity on the meta‐analysis (Higgins 2002; Higgins 2003); we will interpret the I2 statistic as follows (Deeks 2011):

  • 0% to 40%: may not be important;

  • 30% to 60%: may indicate moderate heterogeneity;

  • 50% to 90%: may indicate substantial heterogeneity;

  • 75% to 100%: considerable heterogeneity.

When we find heterogeneity, we will attempt to determine possible reasons for it by examining individual study and subgroup characteristics.

Assessment of reporting biases

We will attempt to obtain study protocols to assess for selective outcome reporting.

If we include 10 studies or more investigating a particular outcome, we will use funnel plots to assess small‐study effects. Several explanations can be offered for the asymmetry of a funnel plot, including true heterogeneity of effect with respect to trial size, poor methodologic design (and hence bias of small trials) and publication bias. Therefore, we will interpret results carefully.

Data synthesis

Unless there is good evidence for homogeneous effects across studies, we will summarize data using a random‐effects model. We will interpret random‐effects meta‐analyses with due consideration of the whole distribution of effects. In addition, we will perform statistical analyses according to the statistical guidelines contained in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011a). For dichotomous outcomes, we will use the Mantel‐Haenszel method; for continuous outcomes, we will use the inverse variance method; and for time‐to‐event outcomes, we will use the generic inverse variance method. We will use Review Manager 5 software to perform analyses (RevMan 2014).

Subgroup analysis and investigation of heterogeneity

We expect the following characteristics to introduce clinical heterogeneity, and plan to carry out subgroup analyses with investigation of interactions.

  • Volume of metastases: high volume defined according to expert consensus (Gillessen 2015) as visceral, four or more bone metastases including one beyond the pelvis and vertebral column, or both versus low volume.

  • Type of metastases: nodal metastases only versus visceral, bone, nodal metastases, or a combination of these.

We will use the test for subgroup differences in Review Manager 5 to compare subgroup analyses if there is at least one study with the data available for our pre‐defined subgroups (RevMan 2014). Furthermore, unless the trial(s) are stratified for the subgroups we will downgrade for quality of evidence.

Sensitivity analysis

We plan to perform sensitivity analyses to explore the influence of the following factors (when applicable) on effect sizes.

  • Restricting the analysis by taking into account risk of bias, by excluding studies at 'high risk' or 'unclear risk.'

'Summary of findings' table

We will present a 'Summary of findings' table reporting the following outcomes listed according to priority.

  • Time‐to‐death due to any cause.

  • Serious adverse events.

  • Time‐to‐death due to prostate cancer.

  • Time‐to‐progression.

  • Discontinuation due to adverse events.

  • All adverse events.

  • Quality of life.

We will present the overall quality of the evidence for each outcome according to the GRADE approach, which takes into account five criteria relating to internal validity (risk of bias, inconsistency, imprecision, publication bias), and external validity (such as directness of results) (Guyatt 2008). For each comparison, two review authors (NS, YP) will independently rate the quality of evidence for each outcome as 'high,' 'moderate,' 'low' or 'very low' using GRADEpro GDT. We will resolve any discrepancies by consensus, or, if needed, by arbitration by a third review author (PD). For each comparison, we will present a summary of the evidence for the main outcomes in a 'Summary of findings' table, which provides key information about the best estimate of the magnitude of the effect in relative terms and absolute differences for each relevant comparison of alternative management strategies; numbers of participants and studies addressing each important outcome; and the rating of the overall confidence in effect estimates for each outcome (Guyatt 2011; Schünemann 2011). If meta‐analysis is not possible, we will present results in a narrative 'Summary of findings' table.