Best first‐line therapy for patients with advanced non‐small cell lung cancer, performance status 2 without a targetable mutation or with an unknown mutation status
Abstract
This is a protocol for a Cochrane Review (Intervention). The objectives are as follows:
To identify the best first‐line therapy for advanced lung cancer in patients with performance status 2 without a targetable mutation or with an unknown mutation status.
Background
Description of the condition
Lung cancer is the most frequent cause of cancer‐related death worldwide, diagnosed in over 1.8 million patients annually (Ferlay 2015). Non‐small cell lung cancer (NSCLC) accounts for 75% of all cases. At the time of diagnosis, most patients (> 50%) already have advanced disease and can be treated only with palliative systemic therapies or best supportive care (Driessen 2017). Unfortunately, despite these therapies, survival rates remain poor, with a median survival of 8.8 months for patients with stage IV disease (Goldstraw 2016). Besides tumor stage, survival is determined by various patient‐ and tumor‐related factors (eg, smoking status, age, gender, performance score [PS], histologic characteristics), of which PS is the most important prognostic factor (Sculier 2008).
The two most commonly used performance scores are the Karnofsky Index of Performance Status (KPS) and the Eastern Cooperative Oncology Group Scale of Performance Status (ECOG PS). These scores correlate strongly, although the ECOG PS shows better predictive performance ‐ Buccheri 1996 ‐ and has been adopted by the World Health Organization (WHO) (WHO 1979). The ECOG PS is a five‐grade scale: 0 ‐ fully active, able to carry on all pre‐disease activities without restriction; 1 ‐ restricted in physically strenuous activity but ambulatory and able to carry out work of light or sedentary nature; 2 ‐ ambulatory and capable of all self‐care but unable to carry out any work activities, up and about more than 50% of waking hours; 3 ‐ capable of only limited self‐care, confined to bed or chair more than 50% of waking hours; 4 ‐ completely disabled, cannot carry on any self‐care, totally confined to bed or chair; and 5 ‐ dead.
Evidence is clear that patients with a known targetable mutation (eg, epidermal growth factor receptor [EGFR] mutation, anaplastic lymphoma kinase [ALK] mutation) should be treated with targeted therapy, regardless of PS (Geffen 2013;Hanna 2017;Novello 2016). Patients with PS of 0 or 1 are usually treated with systemic therapies such as platinum‐based doublet chemotherapy and/or checkpoint inhibitors, whereas patients with PS of 3 or 4 most often receive supportive care. However, treatment for patients with PS 2 without a targetable mutation remains unclear (Novello 2016). Historically, patients with a PS of 2 are frequently excluded from (important) clinical trials because of poorer outcomes and increased toxicity compared with patients with a PS of 0 or 1 (Borghaei 2015;Kogure 2018; Scagliotti 2008;Zinner 2016). As a consequence, trial populations often fail to represent the real‐world population of patients with lung cancer, as 20% to 30% of all new patients with advanced NSCLC present with PS 2 (Kawachi 2018; Lilenbaum 2008). Subsets of patients with PS 2 can be distinguished in clinical practice: those who were in poor health due to comorbidities and developed lung cancer; those whose PS is (in part) a result of their lung cancer; and those who fall into both groups. Most trials do not distinguish between these groups.
Description of the intervention
To identify the best first‐line treatment for patients with advanced NSCLC with PS of 2 and non‐targetable or unknown mutation status, we will include trials assessing chemotherapy (platinum doublet‐based regimens, single or combination cytotoxic agents), immunotherapy (anti‐programmed cell death protein 1 [PD‐1] or programmed death ligand [PD‐L1]/cytotoxic T lymphocyte‐associated antigen 4 [CTLA‐4]), vascular endothelial growth factor (VEGF) inhibitors, and best supportive care (BSC).
Regardless of PS, a variety of single cytotoxic agents and combination regimens have been evaluated for the treatment of NSCLC. In 1995, the Non‐Small Cell Lung Cancer Collaborative Group published a meta‐analysis showing the benefits of chemotherapy added to BSC for overall survival (NSCLC Collaborative Group 2000). In 2008, a subsequent add‐on meta‐analysis by the same group showed overall improvement in one‐year survival of 9% (from 20% to 29%), representing an absolute increase in median survival of 1.5 months (hazard ratio [HR] 0.77, 95% confidence interval [CI] 0.71 to 0.83). The most commonly studied groups of agents are vinca alkaloid or etoposide with or without platinum agents as single‐ or doublet‐agent regimens (NSCLC Collaborative Group 2010). Regimens using combinations of cytotoxic agents containing platinum agents show better results than are seen with single‐agent treatment and BSC (D'Addario 2005). Guidelines therefore recommend standard first‐line chemotherapy consisting of a platinum doublet regimen (Hanna 2017;Novello 2016). To date, the most commonly used agents are cisplatin or carboplatin plus docetaxel; gemcitabine; paclitaxel; vinorelbine; and pemetrexed. Adding bevacizumab to first‐line chemotherapy regimens showed additional absolute survival of 26 days (Lima 2011).
In recent years, immunotherapy has emerged as a novel treatment. Since 2015, three immune checkpoint inhibitors ‐ nivolumab and pembrolizumab (both PD‐1 inhibitors) and atezolizumab (PD‐L1 inhibitor) ‐ have been approved by the US Food and Drug Administration (FDA) for the treatment of advanced lung cancer and have become standard therapies in first‐line and/or second‐line settings for patients with advanced disease. Compared to current chemotherapy regimens, these immune checkpoint inhibitors lead to better progression‐free survival and one‐year survival along with greater quality of life (Borghaei 2015;Brahmer 2015;Reck 2018). Results of studies combining chemotherapy and immunotherapy have been published (Paz‐Ares 2018). Ipilimumab, a CTLA‐4 inhibitor, is still under investigation as an addition to current regimens of chemotherapy and/or immunotherapy.
How the intervention might work
Currently used cytotoxic agents can be divided into four groups.
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Alkylating agents (platinum agents [cisplatin and carboplatin]): these agents cause cross‐linking of DNA, thereby inhibiting DNA repair and/or synthesis.
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Antimetabolites (pyrimidine analogues [gemcitabine], folate antagonists [pemetrexed]): agents that interfere with DNA synthesis by disrupting processes essential to cell replication.
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Antimicrotubule agents (taxanes [docetaxel, paclitaxel] and vinca alkaloids [vinorelbine]): agents that block cell division by inhibiting formation or disassembly of microtubules.
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Topoisomerase inhibitors (ie, epipodophyllotoxins [etoposide]): agents that create DNA strand breaks and block DNA unwinding.
Bevacizumab is a monoclonal antibody that targets VEGF, thereby inhibiting angiogenesis. Immune checkpoint inhibitors (anti PD‐1/L1, CTLA‐4) affect the function of the immune system by stimulating or inhibiting regulatory feedback signaling of T cells, leading to a T cell response to tumor cells.
Why it is important to do this review
We identified a gap in the current overview literature about the best first‐line treatment for patients with advanced NSCLC with performance status 2 and non‐targetable or unknown mutation status. Guidelines from the American Society of Clinical Oncology (ASCO) or the European Society for Medical Oncology (ESMO) do not provide definitive answers (Hanna 2017; Novello 2016). We aim to address this knowledge gap, as this group of patients represents a significant proportion (20% to 30%) of the total population with newly diagnosed lung cancer.
Objectives
To identify the best first‐line therapy for advanced lung cancer in patients with performance status 2 without a targetable mutation or with an unknown mutation status.
Methods
Criteria for considering studies for this review
Types of studies
Randomized clinical trials reporting at least one subset analysis of patients with performance score 2, with or without blinding. Cross‐over studies will be excluded.
Types of participants
Patients aged 18 years and older who have not received previous therapy for pathological confirmed stage IIIB, IIIC, or IV NSCLC (Eighth Edition of TNM [tumor‐node‐metastasis] in Lung Cancer [Goldstraw 2016], or corresponding stages from previous editions) and with an ECOG PS of 2 or equivalent. Participants are considered for palliative systemic therapy only. We will include patients regardless of their histology (eg, squamous, non‐squamous). Patients with confirmed targetable and treated mutations (eg, EGFR, BRAF, ALK, MET, ROS1) will be excluded.
Types of interventions
We will include in this review all types of platinum doublet‐based regimens of chemotherapy and checkpoint‐inhibiting immunotherapy. Chemotherapy is defined as cytotoxic drugs, for example (but not limited to), cisplatin, carboplatin, paclitaxel, pemetrexed, gemcitabine, vinorelbine, irinotecan, or docetaxel. Checkpoint‐inhibiting immunotherapy is defined as drugs that target T cell suppressive pathways, for example, nivolumab, pembrolizumab (anti PD‐1), atezolizumab, durvalumab (anti PD‐L1), and ipilimumab (anti‐CTLA‐4). Other antitumor treatments such as bevacizumab (angiogenesis inhibitor) are allowed and will be categorized as subgroups.
We will investigate the following comparisons.
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Chemotherapy versus best supportive care.
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Chemotherapy versus chemotherapy.
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Chemotherapy versus immunotherapy.
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Chemotherapy plus immunotherapy versus chemotherapy or immunotherapy.
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Immunotherapy versus best supportive care.
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Immunotherapy versus immunotherapy.
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Interventions named above with the same intervention plus bevacizumab.
Types of outcome measures
Primary outcomes
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Overall survival (OS), defined as time from start of treatment until death by any cause
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Health‐related quality of life (HRQoL), measured via validated international scales
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Toxicity/adverse events (Common Terminology Criteria for Adverse Events [CTCAE] grade 3 to 5, and Patient Reported Outcomes [PRO]‐CTCAE if reported) (Kluetz 2016)
Secondary outcomes
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Tumor response rate, defined as the percentage of patients whose cancer shrinks or disappears after treatment based on the Response Evaluation Criteria in Solid Tumors (RECIST 1.1) (Eisenhauer 2009), or in cases of immunotherapy as reported via iRECIST criteria (Seymour 2017)
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Progression‐free survival (PFS), defined as time from randomization until disease progression
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Survival rates at specified time points (6 and 12 months), defined as time from start of treatment until death by any cause
Search methods for identification of studies
Electronic searches
We will conduct searches in the following electronic databases.
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Lung Cancer Group Trials Register.
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Cochrane Central Register of Controlled Trials (CENTRAL), in the Cochrane Library (Appendix 1).
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MEDLINE, accessed via PubMed (Appendix 2).
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Embase (Appendix 3).
We will apply no restriction on language of publication.
Search strategies will be designed by the Information Specialists of the Cochrane Lung Cancer Group.
We will search all databases using both controlled vocabulary (namely, medical subject headings [MeSH] in MEDLINE and Emtree in Embase) and a wide range of free‐text terms. We will perform the MEDLINE search using the Cochrane highly sensitive search strategy and the precision‐maximizing version (2008 version), as described in the Cochrane Handbook for Systematic Reviews of Interventions (Chapter 6.4.11.1, and detailed in Box 6.4.b) (Higgins 2011b).
Searching other resources
We will use the following additional resources to identify studies eligible for inclusion.
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Reference lists of included trials.
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Meeting abstracts of conferences of the American Society of Clinical Oncology (ASCO) from 2016 to date.
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Meeting abstracts of conferences of the European Society for Medical Oncology (ESMO) from 2016 to date.
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Meeting abstracts of conferences of the International Association for the Study of Lung Cancer (IASLC) from 2016 to date.
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Clinical trials registries (www.clinicaltrials.gov, www.clinicaltrialsregister.eu) from 2016 to date.
Data collection and analysis
Selection of studies
We will transfer all retrieved titles and abstracts to a reference manager database (Rayyan 2016). Two review authors (RG and WG) will independently select studies for review that meet inclusion criteria, based on title and abstract. We will exclude duplicates and will obtain the full text of potentially relevant references. Any disagreement will be discussed to achieve consensus. If this consensus is not achieved, a third review author (BV) will be consulted. Where appropriate, we will correspond with investigators to clarify study eligibility or to obtain raw data. If a study population combines multiple performance score groups (eg, PS 0 to 2), the whole group will be included. Where possible, we will recalculate Karnofsky and WHO performance scores as ECOG scores to enhance comparability. We will document reasons for exclusion.
Data extraction and management
Two review authors (RG and WG) will independently extract and document characteristics and outcome data from the included studies using an electronic data collection form. If we identify multiple published reports for an included study, we will collect data on separate data collection forms and will combine them after extraction. One review author (RG) will transfer data to the Cochrane Review Manager software (RevMan 2014), and a second review author (WG) will check the data. In cases of disagreement, a third review author will be consulted to reach consensus.
We will extract the following data.
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Author, year of publication, journal of origin, funding source.
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Methods (inclusion and exclusion criteria; type of analysis ‐ intention‐to‐treat [ITT] or per‐protocol [PP]; endpoints [with time points]; characteristics used to define subgroups).
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Participants (total number, baseline characteristics [if available: age, sex, smoking status, performance status, histology, mutation status, stage, country, ethnicity]).
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Intervention (agents used and control intervention).
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Outcomes (results on primary and secondary endpoints).
Assessment of risk of bias in included studies
We will assess the following types of bias using the Cochrane tool for assessing risk of bias.
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Selection bias (sequence generation, allocation concealment).
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Performance bias (blinding of participants and personnel).
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Detection bias (blinding of outcome assessment).
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Attrition bias (incomplete outcome assessment).
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Reporting bias (selective outcome reporting).
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Other sources of bias (as identified during analysis).
Measures of treatment effect
We will use the following measures of treatment effect.
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For time‐to‐event data, we will use hazard ratio (HR) and 95% confidence interval (CI), if possible. We will also present median survival and one‐year survival if applicable.
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For dichotomous outcomes, we will use odds ratio (OR) or risk ratio (RR) and 95% CI, if possible.
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For continuous outcomes, we will use (standardized) mean difference (MD), if possible.
Unit of analysis issues
We do not expect to include trials using a non‐standard design. For studies with more than one intervention arm, we will analyze these groups separately.
Dealing with missing data
If data are missing, we will try to contact the corresponding author of that study to obtain these results. If data are missing to such extent that the study cannot be included in the analysis, we will report this in the review.
Assessment of heterogeneity
We will assess the degree of heterogeneity using I² statistics and will consider a significance of heterogeneity test (X² test). An I² value > 30% or a low P value on the X² test (P < 0.1) will be considered to represent significant heterogeneity.
Assessment of reporting biases
We will use funnel plots to assess small study effects as publication bias if at least 10 studies are included in the analysis. We will visually inspect these plots and will consider publication bias as one of several possible explanations if we observe asymmetry, and we will conduct further exploration.
Data synthesis
If we identify a sufficient number of studies with a low degree of heterogeneity (I² ≤ 30% or high P value on the X² test), we will conduct a meta‐analysis using the fixed‐effect model. If heterogeneity is substantial (I² > 30% or low P value on the X² test), we will conduct a meta‐analysis using a random‐effects model. For dichotomous outcomes, we will pool (calculated) risk ratios for an event or property. For continuous outcomes, we will pool (calculated) mean differences if all studies report outcomes using the same scale; otherwise, we will use the standardized mean difference approach. For time‐to‐event data, we will pool hazard ratios.
If we are unable to conduct a meta‐analysis, we will summarize the results; we will display them using appropriate tables and images and will discuss them.
"Summary of findings" table
We intend to create a summary of findings table to report the following outcomes.
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Overall survival,
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Progression‐free survival.
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6/12‐Month survival.
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Tumor response rate.
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Health‐related quality of life.
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Toxicity/adverse events.
We will use GRADEpro software to prepare the summary of findings table (GradePRO 2015).
Subgroup analysis and investigation of heterogeneity
We consider the following factors as potential predictors of heterogeneity and will conduct a subgroup analysis to evaluate the effects of interventions in the following groups.
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Histology (squamous or non‐squamous).
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PD‐L1 status (tumor proportion score (TPS) < 1%, 1% to 49%, ≥ 50%).
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Patients aged < or ≥ 70 years.
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Combined performance status groups (eg, PS 0 to 2) versus performance status 2 only.
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Presence or absence of central nervous system metastasis.
Sensitivity analysis
If we identify issues suitable for sensitivity analysis, we will perform this analysis. If sufficient trials are included, we will exclude trials with potentially high risk of bias. If we perform a sensitivity analysis, we will report this by producing a summary table.
