Vaccines for the prevention of infections in adults with solid tumors

Objectives

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

To assess the benefits and harms of vaccines for the prevention of infections in adults with solid tumors.

Background

Description of the condition

According to the National Cancer Institute, a solid tumor is defined as an abnormal mass of tissue that usually does not contain cysts or liquid areas (either benign or malignant (NCI Dictionary of Cancer Terms). Cancer is a leading cause of death in most countries (Sung 2021). In 2020, cancer caused almost 10 million deaths globally, according to the World Health Organization (WHO 2022). In the United States, there will be an estimated 1,918,030 new cancer cases and 609,360 cancer deaths in the year 2022. Breast, prostate, lung, and colon cancers are the most common types of cancer (Siegel 2022). 

Infections are one of the most frequent complications seen in people with cancer, and occur as a result of the underlying condition, or as a consequence of immunosuppressive therapies. People with haematological malignancies usually have higher levels of immunosuppression than those with solid tumors, because neoplastic processes affect the host immune system, and treatments usually cause prolonged neutropenia (Rolston 2017). Thus, the incidence of infections is lower in people with solid tumors compared to those with haematological malignancies (Marin 2014; Schelenz 2013). Nevertheless, next to person‐related factors, such as age, gender, comorbidities, and malnutrition, other common risk factors for infection in people with solid tumors include tumor obstruction (e.g. in people with lung, hepatobiliary, pancreatic, intestinal cancers), oncologic surgery, disruption of anatomic barriers (e.g. skin and mucosal surfaces), and invasive procedures. Common infection sites are respiratory and urinary tract, bloodstream and skin (Rolston 2017). Bacterial infections are the most common type of infections in people with cancer, followed by viral and fungal infections (Cancer 2019).

As anti‐infective therapies, such as antibiotics, antifungals, and antivirals, often interfere with anticancer agents, this can lead to reduced anticancer therapy efficacy and increased toxicity (Zhang 2021). In many cases, this leads to postponement of anticancer therapies to treat an infection, or vice versa, and anti‐infectives are not administered until completion of anticancer therapy (Zorina 2015). Some infections (e.g. influenza, pneumococcal, and meningococcal disease) can be prevented with vaccination, and therefore, preventive strategies to avoid infection, such as vaccinations are required.

Description of the intervention

Vaccines can be broadly classified according to the pathogens used for vaccine development. Conventional vaccines include live‐attenuated pathogens (e.g. measles, rubella, mumps), inactivated pathogens (e.g. polio, first influenza vaccines), and conjugate vaccines (e.g. influenza, human papillomavirus, hepatitis B). Novel vaccine technologies are based on genome‐sequence information, and include nucleic acid vaccines and vector‐based vaccines (Gebre 2021; Rüthrich 2022).

Live‐attenuated vaccines contain weakened or attenuated pathogens, mimicking a natural infection. In healthy individuals, these vaccines trigger a strong cellular and humoral immune response without causing the disease itself (Rüthrich 2022). In people with immunocompromised systems, these vaccines are contraindicated, because of the risk of severe disease (Rieger 2018; Sarmiento 2016). In contrast, inactivated and conjugate vaccines are less immunogenic, but the strength of the immune response varies, and booster vaccinations might be necessary to elicit a sufficient immune response (Rieger 2018; Tsigrelis 2016).

How the intervention might work

Currently, there is no gold standard to prevent vaccine‐preventable infections in people with cancer. While people with haematological disorders elicit lower immune responses to most vaccines compared to healthy individuals, people with solid tumors elicit either adequate or lower immune responses when compared to healthy individuals (Becerril‐Gaitan 2022; Nordøy 2002). However, vaccination may prevent and decrease the severity of infections, avoid hospitalisations, and reduce infection‐related mortality (Mikulska 2019). Recommendations in current national and international guidelines are vague or inconsistent. According to the European Conference on Infections in Leukaemia guideline for people with cancer after stem cell transplantation, limited evidence indicates that re‐vaccination should be considered (Cordonnier 2019). People with haematological malignancies who are not candidates for stem cell transplantation should be vaccinated against influenza and pneumococcus infection. No clear recommendations are given for other vaccinations for this population (Mikulska 2019). The guideline by the Infectious Diseases Working Party of the German Society for Hematology and Medical Oncology provides recommendations based on expert panel discussion, without giving details on the selection process of included literature, bias assessment, or analysis of identified studies (Rieger 2018). 

According to the Canadian Immunization Guide, people with haematological disorders and solid tumors should be vaccinated with inactivated vaccines, according to the routine vaccination schedule, but at least two weeks prior to the start of immunosuppressive therapy, or when immunosuppressive therapy is at the lowest level, except when the risk of an impending infection with a pathogen is high (Government of Canada 2022). Vaccination with pneumococcal conjugate vaccine and polysaccharide vaccine is recommended because of an increased risk to invasive pneumococcal disease. People with haematological disorders should also be vaccinated with a single dose of haemophilus influenzae type b (HiB) vaccine, regardless of prior vaccination. People with severe neutropenia (neutrophil counts < 500/µL) should not be vaccinated, in order to avoid acute febrile episodes (Australian Government 2020). Live‐attenuated vaccines are contraindicated in both populations (Government of Canada 2022). Vaccination of people with cancer is not covered in the German evidence‐based guidelines on supportive care, and is rarely and inconsistently recommended in disease specific guidelines.

Why it is important to do this review

The research question on how to prevent vaccine‐preventable infections in people with cancer is very relevant, and has been prioritised by the German Society for Hematology and Medical Oncology (DGHO). In 2019, the DGHO conducted a roadmap for research on cancer and diseases of the blood, summarising the current essential research questions (DGHO 2019). Prevention of infections in people with cancer is one of the essential research fields identified in this process. According to the DGHO, vaccines offer the best option for tolerability and costs for prevention in the field of pharmacological prophylaxis. They also highlighted the practice of not vaccinating people with cancer, and the lack of evidence to support the assumption that this population had a reduced vaccination response. And lastly, in the introduction of antineoplastic therapies, there is no recommendation to investigate their influence on vaccination response.

There is an existing Cochrane Review, Influenza vaccines in immunocompromised adults with cancer, which was last updated in 2018 (Bitterman 2018). The review focused solely on influenza vaccines and included adults with all types of cancer (solid and haematological malignancies, and post‐autologous or allogeneic haematopoietic stem cell transplantation). In addition to randomised controlled trials (RCT) and cohort studies, they also included retrospective study designs, such as case‐control studies. In this review, we will exclude evidence from retrospective studies, because they are often at high risk of bias.

This review will focus on individuals with solid tumors. It is part of a series of two other reviews focusing on people with haematological malignancies and cellular therapies (including autologous and allogeneic haematopoietic stem cell transplantation and chimeric antigen receptor T‐cell).

Objectives

To assess the benefits and harms of vaccines for the prevention of infections in adults with solid tumors.

Methods

Criteria for considering studies for this review

Types of studies

We plan to include randomised controlled trials (RCT). When RCT data are available, we will use the common methods recommended by the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2022a). We will include non‐standard RCT designs, such as cross‐over studies and cluster‐randomised studies, using methods recommended in Chapter 23 of the Cochrane Handbook (Higgins 2022b). In cross‐over studies, we will only consider results from the first period before cross‐over to avoid carry‐over effects. 

If at least one RCT per vaccine for each infectious disease is not available, we will include prospectively registered, controlled non‐randomised studies of interventions (NRSIs) for this disease, including quasi‐RCTs, using methods proposed in the Cochrane Handbook (Reeves 2022). 

We will only consider studies with a minimum sample size of 20 participants per arm. We will exclude non‐comparative study designs (e.g. case series) and retrospective studies, because they are often of low methodological quality and more prone to bias (e.g. through selective inclusion of participants, a lack of records in patient charts (Norris 2005)). We will include formats such as full‐text publications, preprints, abstract publications, results published in study registries and information provided by the principal investigators.

There will be no limit with respect to the length of follow‐up.

Types of participants

We will consider studies including adult participants (i.e. ≥ 18 years of age) with any diagnosis of a solid tumor cancer (e.g. breast, colon, bladder, prostate, or lung), diagnosed with any stage, including people with relapsed or metastatic disease. Studies including people with cancer and other entities will only be included if the study authors provide subgroup data for participants with solid tumors.

We will include studies on people receiving antineoplastic treatment or no treatment, but exclude individuals receiving cellular therapies (e.g. autologous and allogeneic haematopoietic stem cell transplantation and chimeric antigen receptor T‐cell), as they will be addressed in another review.

Types of interventions

We will include the following vaccines against infectious diseases.

• Inactivated and conjugate vaccines

  • Streptococcus pneumonia

  • Haemophilus influenzae type b (Hib)

  • Neisseria meningitidis 

  • Pertussis 

  • Hepatitis B

  • Tetanus

  • Polio

  • Diphtheria

  • Influenza

  • Herpes zoster

• Novel vaccine technologies

  • COVID‐19*

• Combination vaccines that include at least one eligible vaccine

*We will include COVID‐19 vaccines currently authorised by the European Medicines Agencies, or authorised in at least ten countries worldwide by the time of the search (according to McGill COVID19 Vaccine Tracker Team (McGill 2021) available from covid19.trackvaccines.org/). As of 1 June 2022, those are: 

• BNT162b2 (Comirnaty; Biontech Pfizer) 

• mRNA1273 (Spikevax; Moderna) 

• AZD12222 (Vaxzevria; AstraZeneca) 

• Ad26.COV2.S (COVID‐19 Vaccine Janssen)

• Sputnik V (Gamaleya) 

• Sputnik Light (Gamaleya) 

• BBIBP‐CorV (Sinopharm; Beijing CNBG)

• CoronaVac (Sinovac) 

• BBV152 (Covaxin)

• Ad5‐nCoV (Convidecia)

• NVX‐CoV2373 (Nuvaxovid; Novavax)

We will exclude live‐attenuated vaccines because these are contraindicated in people with immunocompromised systems.

We will conduct separate analyses for vaccines for each infectious disease.

As a comparator, we will consider placebo or no vaccine. 

Types of outcome measures

To avoid selective reporting bias, we will include studies regardless of the reported outcome data.

The outcomes of interest were prioritised by clinical experts, people with cancer, and their representatives.

Critical outcome

• Incidence of the infection concerned (using methods as defined in the study)

Important outcomes

• All‐cause mortality (at longest follow‐up available)

• Quality of life (QoL), if measured using reliable and valid instruments, such as the European Organization for the Research and Treatment of Cancer Quality of Life Questionnaire (EORT‐QLQ C30), Functional Assessment of Cancer Therapy‐General (FACT‐G) or Quality of Life Scale (QOLS); at a time point most commonly reported in the studies; if the reported time points differ significantly, we will choose the longest follow‐up available

• Number of participants with any grade adverse events (AE) at longest follow‐up available

• Number of participants with serious adverse events (SAE) at longest follow‐up available

• Number of participants with AE of special interest, such as local events at the injection site (e.g. tenderness or soreness, erythema, arm stiffness), systemic events (e.g. myalgia, fever, headache, fatigue, rash), at the longest follow‐up available

Hierarchy of outcome measures

If the same outcome domain is measured in multiple ways within one study or across multiple studies (e.g. QoL measured on two different scales), we will prioritise the outcome measure most commonly reported across studies.

Timing of outcome measures

We will consider outcome data for all published time points after full vaccination (i.e. for most vaccines two weeks after the last planned shot). If sufficient data are available, we will group the measurement time points into short‐term (up to 12 weeks after full vaccination), medium‐term (from 12 weeks to 6 months after full vaccination) and long‐term (more than 6 months after full vaccination) observations.  

Search methods for identification of studies

Electronic searches

Search strategies for electronic databases will be adapted from those suggested in the Cochrane Handbook (Lefebvre 2022). In this emerging field, we expect that at least the abstract will be in English. If the full‐text articles are published in other languages, we will use Cochrane TaskExchange to identify people within Cochrane to translate these studies (taskexchange.cochrane.org/).

We will search the following databases:

• Cochrane Central Register of Controlled Trials (CENTRAL) in the Cochrane Library (latest issue);

• MEDLINE Ovid (1946 to current; Appendix 1);

• Embase Ovid (1974 to current);

• Web of Science Emerging Sources Citation Index (ESCI; 2017 to current); and 

• LILACS (Latin American and Caribbean Health Science Information database). 

We will search ClinicalTrials.gov (clinicaltrials.gov/) and the WHO International Clinical Trials Registry Platform (ICTRP) search portal (www.apps.who.int/trialsearch/).

For COVID‐19 vaccines, we will search these specific sources:

• Cochrane COVID‐19 Study Register for ongoing trials, not yet published trials, (covid-19.cochrane.org; inception to current; Appendix 2), that includes:

  • PubMed, updated weekly;

  • Embase.com, updated weekly;

  • ClinicalTrials.com, updated daily;

  • WHO ICTRP, updated weekly; and

  • CENTRAL, updated monthly.

• WHO COVID‐19 global literature on coronavirus disease (search.bvsalud.org/global-literature-on-novel-coronavirus-2019-ncov/).

Searching other resources

We will hand search references of all included studies, and relevant review articles identified in the searches, and contact experts in the field in order to retrieve information on unpublished studies.

Data collection and analysis

Selection of studies

Two review authors (CH, AB, or NK) will independently screen the results of the search strategies for eligibility by reading the abstracts, using Covidence software (Covidence). We will obtain the full‐text publications of any abstracts that both review authors find eligible, and those on they disagree or rate as uncertain, for further discussion. Two review authors (CH, AB, or NK) will assess the full‐text articles of selected studies. If the two review authors are unable to reach a consensus, we will consult a third review author (NS) to reach a final decision.

We will document the study selection process in a flow chart, as recommended in the PRISMA statement, and will show the total number of retrieved references and the numbers of included and excluded studies (Moher 2009). We will list all articles that we exclude after full‐text assessment and their reasons for exclusion in a characteristics of excluded studies table.

Data extraction and management

Two review authors (CH, AB, or NK) will extract data independently and in duplicate, using a customised and piloted data extraction form developed in Microsoft Excel. We will solve disagreements by discussion. Should no agreement be reached, we will involve a third review author (NS). If multiple records of one study report on the same characteristics or outcome data, we will choose the data with the longest follow‐up time. If required, we will contact the authors of specific studies for supplementary information (Boutron 2022).

We will collate multiple reports of each study so that the study, and not the report, is the unit of analysis.

We will extract the following information if reported.

• General information: author, title, source, publication date, publication type, country, language, ethics approval (yes/no), and location of ethics committee, duplicate publications

• Study characteristics: trial design, setting and dates, source of participants, inclusion and exclusion criteria, length of follow‐up

• Participant characteristics: age, sex, ethnicity, number of participants recruited/allocated/evaluated, type of malignancy, stage of malignancy, details of anti‐cancer treatment (e.g. type of treatment, treatment status), additional diagnoses, previous known infection, recovery from infection, or previous vaccination (i.e. childhood) 

• Intervention: type of vaccine and vaccination schedule, timing, duration of follow‐up;

  • For vaccines requiring multiple doses for full vaccination: time interval between shots, heterologous/homogenous vaccination

  • For booster vaccinations: time interval since full vaccination, type of booster vaccine

• Control intervention: placebo or no vaccine 

• Outcomes as specified under Types of outcome measures

Assessment of risk of bias in included studies

For risk of bias assessments, we will use tools tailored to the study design. Two authors will independently assess the risk of bias of included studies on an outcome level. In case of discrepancies amongst their judgements and inability to reach consensus, we will consult a third review author to reach a final decision.

Randomised‐controlled studies

For RCTs, we will use the RoB 2 tool to analyse the risk of bias per study outcome listed for inclusion in the summary of findings table (Sterne 2019). Of interest for this review is the effect of the assignment to the intervention (the intention‐to‐treat (ITT) effect).

We will assess the following types of bias (Higgins 2022c).

• Bias arising from the randomisation process

• Bias due to deviations from the intended interventions

• Bias due to missing outcome data

• Bias in measurement of the outcome

• Bias in selection of the reported result

For cluster‐randomised trials, we will add a domain to assess bias arising from the timing of identification and recruitment of participants in relation to timing of randomisation (Eldridge 2021; Higgins 2022b).

To address these types of bias, we will use the signalling questions recommended in RoB 2, and make a judgement using the following options.

• Yes: if there is firm evidence that the question is fulfilled in the study

• Probably yes: a judgement has been made that the question is fulfilled in the study 

• No: if there is firm evidence that the question is unfilled in the study 

• Probably no: a judgement has been made that the question is unfilled in the study 

• No information: if the study report does not provide sufficient information to allow any judgement

We will use the algorithms proposed by RoB 2 to assign each domain one of the following levels of bias.

• Low risk of bias

• Some concerns

• High risk of bias

Subsequently, we will derive an overall risk of bias rating for each prespecified outcome in each study in accordance with the following suggestions.

• Low risk of bias: we judge the trial to be at low risk of bias for all domains for this result

• Some concerns: we judge the trial to raise some concerns in at least one domain for this result, but not to be at high risk of bias for any domain

• High risk of bias: we judge the trial to be at high risk of bias in at least one domain for the result, or we judge the trial to have some concerns for multiple domains in a way that substantially lowers confidence in the results

We will use the RoB 2 Excel tool to implement RoB 2 (available from riskofbias.info) and will store and present our detailed RoB 2 assessments as supplementary online material.

Non‐randomised controlled studies

For NRSIs, we will use the Risk of Bias in Non‐randomised Studies ‐ of Interventions (ROBINS‐I) tool (Sterne 2016). The quality assessment strongly depends upon information on the design, conduct, and analysis of the study.

We will assess the following domains of bias. 

• Bias due to confounding 

• Bias in selection of participants into the study 

• Bias in classification of interventions 

• Bias due to deviations from intended interventions 

• Bias due to missing data 

• Bias in measurement of outcomes 

• Bias in selection of the reported result

For every criterion, we will make a judgement using one of five response options. 

• Yes 

• Probably yes

• Probably no

• No

• No information

The levels for domain risk of bias judgements are: 

• Low risk of bias;

• Moderate risk of bias;

• Serious risk of bias;

• Critical risk of bias;

• No information.

Subsequently, we will derive an overall risk of bias rating for each prespecified outcome in each study, in accordance with the following suggestions (Sterne 2016).

• Low risk of bias: we judge the trial to be at low risk of bias for all domains for this result

• Moderate risk of bias: we judge the trial to be at low or moderate risk of bias for all domains

• Serious risk of bias: we judge the trial to be at serious risk of bias in at least one domain, but not at critical risk of bias in any domain

• Critical risk of bias: we judge the trial to be at critical risk of bias in at least one domain

• No information: there is no clear indication that the study is at serious or critical risk of bias, and there is a lack of information in one or more key domains of bias

We will use robvis, an online risk of bias visualisation tool for NRSI, to create 'traffic light' plots of domain‐level judgements for each individual result (McGuiness 2021).

Measures of treatment effect

For continuous outcomes, we will record the mean, standard deviation, and total number of participants in both treatment and control groups. Where continuous outcomes use the same scale, we will undertake analyses using the mean difference (MD) with 95% confidence intervals (CIs). For continuous outcomes measured with different scales, we will undertake analyses using the standardised mean difference (SMD).

For dichotomous outcomes, we will record the number of events and the total number of participants in both treatment and control groups. We will report the pooled risk ratio (RR) with a 95% CI (Deeks 2022). For non‐RCTs, we will preferentially extract and use adjusted RRs with 95% CI.

For cluster‐randomised trials, we will extract and report direct estimates of the effect measure (e.g. RR with a 95% CI) from an analysis that accounts for the clustered design. We will obtain statistical advice to ensure the analysis is appropriate. If appropriate analyses are not available, we will make every effort to approximate the analysis (Higgins 2022b).

Unit of analysis issues

The aim of this review is to summarise trials that analyse data at the level of the individual.  For dichotomous outcomes (e.g. adverse events), we will use participants as the unit of analysis, rather than events (e.g. the number of participants with adverse events rather than the number of events per participant (Higgins 2022b)). If a study reports rate ratios, we will analyse the rate ratios on the basis of events rather than participants (Higgins 2022d).

We will also include cluster‐randomised trials, and we will use the methods recommended in Chapter 23 of the Cochrane Handbook (Higgins 2022b). When study authors used an analysis that accounted for clustering, such as multilevel or generalised models, we will directly incorporate the effect estimate using inverse‐variance meta‐analysis. If authors did not account for clustering, we will estimate the effective sample size or inflated standard error from the non‐accounted effect estimate, the number of clusters, and the intraclass correlation coefficient for inclusion in the meta‐analysis (Higgins 2022b). From cross‐over trials, we will only consider results from the first period before cross‐over.

Studies with multiple treatment groups

For studies with multiple treatment groups of the same intervention (i.e. dose), we will evaluate if study arms are sufficiently homogeneous to be combined. When it is not feasible to pool arms, we will compare each arm with the common comparator separately. For pair‐wise meta‐analysis, we will split the ‘shared’ group into two or more groups with smaller sample sizes, and include two or more (reasonably independent) comparisons. For this purpose, for dichotomous outcomes, we will divide both the number of events and the total number of participants; for continuous outcomes, we will divide the total number of participants and leave the means and SDs unchanged (Higgins 2022d).

Dealing with missing data

When possible, we will extract effect estimates or data to calculate effect estimates for all allocated participants (intention‐to‐treat principle). If individuals allocated to treatment are missing from the analysis, their possible effect on the analysis will be considered in our RoB assessment.

If outcome data are reported only partly, and recalculation of effect estimates and their corresponding measure of spread is not possible, information on complete outcomes is missing, or any further information is required (i.e. on relevant study characteristics or information necessary to judge the risk of bias), we will contact the primary study authors for this information.

Assessment of heterogeneity

We will assess heterogeneity of treatment effects between studies using a Chi² test with a significance level at P < 0.1. We will use the I² statistic to quantify possible heterogeneity (I² statistic between 30% and 60% may signify moderate heterogeneity, I² statistic between 50% and 90% may signify substantial heterogeneity, and I² > 75% may signify considerable heterogeneity (Deeks 2022)). If heterogeneity is considerable (I² > 75%), we will explore potential causes through sensitivity and subgroup analyses. If we cannot find a reason for heterogeneity, we will not perform a meta‐analysis, but will comment on results from all studies and present these in tables.

Assessment of reporting biases

We will search study registries to identify completed studies that have not been published elsewhere, to minimise or determine publication bias. We intend to explore potential publication bias by generating a funnel plot and statistically testing this, by conducting a linear regression test for meta‐analyses involving at least 10 trials (Page 2022). We will consider P < 0.1 as significant for this test.

Data synthesis

We will conduct separate meta‐analyses for vaccines for different infectious diseases. We will not combine data from RCTs and non‐randomised controlled studies. 

If the clinical and methodological characteristics of individual studies are sufficiently homogeneous, we will pool the data in meta‐analysis according to the recommendations of the Cochrane Handbook, using Review Manager Web (RevMan Web (Deeks 2022; RevMan Web 2023)). One review author (CH or AB) will enter the data into the software, and a second (NK) will check the data for accuracy. We will use the random‐effects model for all analyses, both RCTs and NRSI, because we anticipate that true effects will be related, but not the same for all included studies. 

For binary outcomes originating from RCTs, we will base the estimation of the between‐study variance using the Mantel‐Haenszel method. We will use the inverse variance method for continuous outcomes, outcomes that include data from cluster‐RCTs, or outcomes where hazard ratios (HR) are available. If heterogeneity is found to be above 75%, we will explore this with subgroup analyses. If we cannot find a cause for the heterogeneity, we will not present the pooled estimate of the meta‐analysis, but comment on the results narratively.

We will meta‐analyse NRSI data based on Chapter 24 in the Cochrane Handbook when studies are considered sufficiently homogeneous, report sufficient data, and are rated as low or moderate risk of bias, following the same approach as described for meta‐analysis of RCT (Reeves 2022).

If we cannot perform a meta‐analysis, we will present the results in forest plots without a combined effect estimate in RevMan Web, according to vaccines for each infectious disease and subgroups (e.g. age, biological sex of participants, type of malignancy) and comment on them narratively. 

Subgroup analysis and investigation of heterogeneity

To explore heterogeneity, we will perform subgroup analyses for our critical outcome, incidence of the infection concerned, based on the following characteristics.

• Different types of vaccine for the same disease

• Alternative dosing regimens or schedules

• Age of participants (e.g. 18 to 75 years versus ≥ 75 years)

• Biologic sex of participants (male versus female)

• Type of malignancy

• Stage of malignant disease (e.g. active versus in remission; treatment‐naïve versus first‐line treatment versus relapsed or refractory)

• Type of treatment (e.g. B cell‐depleting therapies, targeted or novel antineoplastic agents), chemotherapy

• Treatment status (before therapy, during therapy, during maintenance therapy, and after therapy)

• Vaccination schedule (duration between vaccinations, heterologous versus homologous, time interval to booster shot)

• Duration of follow‐up (e.g. shorter versus longer follow‐up) 

Due to differences in vaccine responses, we expect a higher incidence of infection in the elderly, males, B cell‐depleting therapies, during and before treatment, homologous vaccinations, and in studies with longer follow‐up periods. Similarly, different vaccine types and dosing regimens or schedules could contribute to heterogeneity.

We will use the tests for interaction in RevMan Web to test for differences between subgroup results.

Sensitivity analysis

We will undertake sensitivity analyses for the outcome, incidence of the infection concerned, for the following criteria.

• Risk of bias assessment components (RCT with a low risk of bias or some concerns versus those with a high risk of bias; non‐randomised studies with a low risk of bias versus those with a moderate risk of bias; non‐randomised studies with a serious or critical risk of bias will not be included in any analysis)

• Comparison of peer‐reviewed articles with non‐peer reviewed data sources (e.g. preprints, abstracts, data extracted from trial registries)

We will use the tests for interaction to test for differences between sensitivity analyses.

Summary of findings and assessment of the certainty of the evidence

Summary of findings table

We will create separate summary of findings tables for vaccines for each infectious disease, for the comparison placebo or no vaccine using GRADEpro GDT software (GRADEpro GDT; Schünemann 2022).

We will include these outcomes, prioritised by clinical experts, people with cancer, and their representatives.

• Incidence of the infection concerned (using methods as defined in the respective study)

• All‐cause mortality (at longest follow‐up available)

• Quality of life (QoL), if measured at a time point most commonly reported in the studies; if the reported time points differ significantly, we will choose the longest follow‐up available

• Number of participants with any grade adverse events at longest follow‐up available

• Number of participants with serious adverse events at longest follow‐up available

• Number of participants with adverse events of special interest, such as local events at the injection site (e.g. tenderness or soreness, erythema, arm stiffness), or systemic events (e.g. myalgia, fever, headache, fatigue, rash), at the longest follow‐up available

Assessment of the certainty of the evidence

We will use the GRADE approach to assess the certainty of the evidence for the outcomes listed in the previous section. The GRADE approach uses five domains (risk of bias, consistency of effect, imprecision, indirectness, and publication bias) to assess the certainty of the body of evidence for each prioritised outcome. Two authors (CH, NK, or AB) will independently assess the certainty for each outcome. Disagreements will be resolved by a third author (NS).

In case we have serious or very serious concerns in any of the above domains, we plan to downgrade our certainty of the evidence as follows: 

• Study limitations: moderate (‐1) or serious (‐2) risk of bias; in addition, for non‐randomised studies (‐3) for critical risk of bias;

• Inconsistency: serious (‐1) or very serious (‐2) inconsistency;

• Indirectness: serious (‐1) or very serious (‐2) uncertainty about directness;

• Imprecision: serious (‐1) or very serious (‐2) imprecise or sparse data;

• Publication bias: serious (‐1) or very serious (‐2) probability of reporting bias.

The GRADE system used the following criteria for assigning grades of evidence.

• High certainty: we are very confident that the true effect lies close to that of the estimate of the effect

• Moderate certainty: we are moderately confident in the effect estimate; the true effect is likely to be close to the estimate of effect, but there is a possibility that it is substantially different

• Low certainty: our confidence in the effect estimate is limited; the true effect may be substantially different from the estimate of the effect

• Very low certainty: we have very little confidence in the effect estimate; the true effect is likely to be substantially different from the estimate of effect

We will follow the current GRADE guidance for these assessments in their entirety (Schünemann 2022). 

According to GRADE guidance 18, we will start our initial rating for non‐randomised studies with high certainty (as for RCTs), as we will use the ROBINS‐I tool to assess risk of bias (Schünemann 2019). We will use the overall risk of bias judgement to inform our decision on downgrading for risk of bias.

We will phrase the findings and certainty of the evidence as suggested in the guidance on informative statements (Santesso 2020).

Notes

Parts of the review's methods section is adopted from the template of Cochrane Haematology and protocol by Hirsch 2022. 

Appendices

Appendix 1. Preliminary MEDLINE Ovid search strategy

# Searches

1 exp NEOPLASMS BY HISTOLOGIC TYPE/

2 exp NEOPLASMS BY SITE/

3 Antineoplastic Agents/

4 (anticancer* or antitumor* or antitumour* or anti‐cancer* or anti‐tumor* or anti‐tumour* or antineoplastic* or anticarcinogenic* or anti‐neoplastic* or anti‐carcinogenic* or chemotherap* or chemo‐therap* or onco*).tw,kf.

5 (neoplas* or tumo?r* or cancer* or malignan* or carcino* or sarcom* or melano* or metastas* or mesothelio* or mesotelio* or gliom* or glioblastom* or osteo?sarcom* or blastom* or neuroblastom* or adenocarcinoma* or myeloma*).tw,kf.

6 (lympho* adj2 (neoplasm* or malign* or tumor* or tumour* or sarcom*)).tw,kf.

7 (lympha* adj2 (neoplasm* or malign* or tumor* or tumour* or sarcom*)).tw,kf.

8 (lymphom* or (germinoblastic adj sarcom*) or germinoblastom* or germino‐blastom* or reticulolymphosarcom* or reticulo‐lympho‐sarcom* or reticulo‐lymphosarcom).tw,kf.

9 (non hodgkin* or nonhodgkin* or nhl).tw,kf.

10 (lymphosarcom* or lympho‐sarcom* or hodgkin* or (reticul* adj1 sarcom*) or reticulosarcom* or reticulo‐sarcom*).tw,kf.

11 (leuk?em* or histiocy* or granulom* or leucocyth?emia* or leuco‐cyth?emia* or (burkitt* adj1 (tumo?r* or lymphom*)) or brill‐symmer*).tw,kf.

12 (myelomatos?s or (plasma* adj3 neoplas*) or kahler* or plasm##ytom* or myelom? or sezary).tw,kf.

13 (ma#roglobulinemia or ma#roglobulinaemia or waldenstr* or immuno#ytoma*).tw,kf.

14 (dysmyelopoietic* or myelodysplas* or myeloplasti*).tw,kf.

15 ("B‐cell directed" or B‐cell deplet* or "B‐cell disruption" or "B‐cell directed therap*" or b‐cell targeted therap* or lymphocyte deplet* or lymphocytotoxic therap* or B lymphocyte deplet*).tw,kf.

16 myelodysplastic syndromes/

17 (((dysmyelopoietic* or myelodysplastic*) adj2 syndrom*) or myelodysplasia*).tw,kf.

18 or/1‐17

19 *vaccines/ or diphtheria‐tetanus vaccine/ or haemophilus vaccines/ or exp pertussis vaccine/ or toxoids/ or exp diphtheria toxoid/ or exp tetanus toxoid/ or exp vaccines, combined/ or exp vaccines, subunit/ or exp covid‐19 vaccines/ or exp herpesvirus vaccines/ or exp measles vaccine/ or exp mumps vaccine/ or exp papillomavirus vaccines/ or vaccines, inactivated/ or exp poliovirus vaccines/ or exp rubella vaccine/ or *viral hepatitis vaccines/ or hepatitis b vaccines/ or chickenpox vaccines/ or rotavirus vaccines/ or vaccines, conjugate/ or influenza vaccines/ or immunization, secondary/

20 ((diphtheri* or pertuss* or whoop* or bordetella or tetanus*) adj4 (toxoid* or vaccin* or immuni* or immune or booster* or revaccin*)).tw,kf,nm.

21 ((DTP* or DTwP* or DTaP* or DT2aP* or DT3aP* or DT5aP* or TDaP* or Td5aP* or DT3aP* or DTPa* or "di te per") adj4 (toxoid* or vaccin* or immuni* or booster* or revaccin*)).tw,kf,nm.

22 (acel imune* or acelimune* or adacel* or boostrix* or daptacel* or easysix* or hexyon* or hexacima* or hexaxim* or infanrix* or kinrix* or nimenrix* or pediacel* or pediarix* or pentacel* or quadracel* or Td Adsorbed* or tdvax* or tenivac* or tetravac* or tripedia* or repevax* or vaxelis*).tw,kf,nm.

23 (acellular adj5 vaccin*).tw,kf,nm.

24 ((haemophilus or hemophilus or HIB) adj5 (vaccin* or toixoid* or conjugate* or immuni* or immune or booster* or revaccin*)).tw,kf,nm.

25 (Hiberix* or Vaxem Hib or Menitorix or Hib‐MenCY‐TT vaccine or MenHibrix or ActHIB or COMVAX or Engerix‐B or Hib‐CRM197 or Hib‐TT or ActHIB or PedvaxHIB or Menjugate or Havrix or Quinvaxem or CombAct‐HIB or Zilbrix).tw,kf,nm.

26 ((hepatitis b or HBV or HepB*) adj5 (vaccin* or toxoid* or immuni* or immune or booster* or revaccin*)).tw,kf,nm.

27 ("engerix‐B" or "euvax‐B" or "elovac B" or "genevac B" or "heplisav‐B" or pentavac* or PreHevbrio* or recombivax* or "Shanvac B" or vaxelis*).tw,kf,nm.

28 ((measles* or rubeola* or rubeolla* or mumps* or rubella* or MMR) adj5 (vaccin* or immuni* or immune or conjugate* or inocula* or booster* or revaccin*)).tw,kf,nm.

29 (MMRV or "MMR+V" or "M‐M‐RvaxPro" or "M‐M‐R II" or tresivac or PHiD‐CV* or priorix or ProQuad or trimovax or "triviraten berna" or virivac or pluserix).tw,kf,nm.

30 (((neisseria adj mening*) or meningococ*) adj5 (vaccin* or toxoid* or immuni* or immune or conjugate* or inocula* or booster* or revaccin*)).tw,kf,nm.

31 (C‐CRM197* or menactra* or menomune* or menveo* or nimenrix* or mencevax* or menhibrix or MenAfriVac* or menquadfi*).tw,kf,nm.

32 (pneumococ* adj5 (vaccin* or toxoid* or immuni* or immune or conjugate* or inocula* or booster* or revaccin*)).tw,kf,nm.

33 (PCV7 or prevenar* or prevnar* or PCV10 or synflorix* or PCV13 or PCV15 or PncOMPC or PNCRM7 or vaxneuvance or PCV20 or apexxnar or pneumovax or PSV23 or PCV23 or "pnu imune vaccine" or CVP).tw,kf,nm.

34 (polio* adj5 (oral* or toxoid* or vaccin* or immun* or immune or inocula* or booster* or revaccin*)).tw,kf,nm.

35 (OPV* or mOPV* or bOPV* or tOPV* or IPV* or sabin).tw,kf,nm.

36 (ipol or poliovax or movax polio or imovax or imovac or ipovac or boostrix polio or tritanrix or poliorix).tw,kf,nm.

37 ((rota virus or rotavirus*) adj5 (vaccin* or toxoid* or immun* or immune or inocula* or booster* or revaccin*)).tw,kf,nm.

38 (rotarix or rotateq or rotavac or "rotavin‐M1" or "lanzhou lamb" or rotasiil).tw,kf,nm.

39 ((varicell* or chickenpox* or chicken pox*) adj5 (vaccin* or toxoid* or immuni* or immune or conjugate* or inocula* or booster* or revaccin*)).tw,kf,nm.

40 (poquad or varivax or varilrix or zostavax).tw,kf,nm.

41 ((papilloma virus* or papillomavirus* or HPV) adj5 (vaccin* or toxoid* or immuni* or immune or inocula* or booster* or revaccin*)).tw,kf,nm.

42 (gardasil* or cervarix* or GSK‐580299 or GSK580299).tw,kf,nm.

43 ((shingles or zoster* or varicellovir* or hhv3 or hhv3) adj5 (vaccin* or toxoid* or immuni* or immune or inocula* or booster* or revaccin*)).tw,kf,nm.

44 (varicellovir* or HZV or VZH or ZVin).tw,kf,nm.

45 ((flu or influenza or grippe or orthomyxovir* or myxovirus*) adj3 (vaccin* or toxoid* or conjugate* or immuni* or immune or booster* or revaccin*)).tw,kf,nm.

46 (flumist* or CAIV‐T vaccin* or LAIV vaccin* or fluzone* or fluarix* or fluinsure* or fluviral* or invivac* or influject* or flublok* or fluvirin* or vaxigrip* or imomax gripe* or istivac* or mutagrip* or flushield* or fluogen*).tw,kf,nm.

47 or/19‐46

48 Encephalitis, Tick‐Borne/

49 (((tickborne* or tick‐borne*) adj2 encephalitis*) or TBE or TBEv).tw,kf.

50 ((tick‐borne* or tickborne*) adj2 (meningoencephalitis* or meningo‐encephalitis*)).tw,kf.

51 (FSME or early summer meningoencephalitis or spring‐summer meningoencephalitis).tw,kf.

52 or/48‐51

53 (ticovac* or FSME IMMUN* or FSMEIMMUN* or encepur*).tw,kf.

54 Encephalitis, Japanese/

55 (japanese adj2 encephalitis*).tw,kf.

56 (ixiaro* or chimerivax* or JESPECT* or jevac* or jecevac* or je‐vax* or JEV IC51 or IMOjev* or je vaccine* or je‐cv vaccine*).tw,kf.

57 Cholera/ or exp Vibrio cholerae/

58 cholera*.tw,kf.

59 (shanchol* or cholvax* or euvichol* dukoral* or Bs‐WC or RBs‐WC or oravacs* or ORC‐vax* or BivWC* or Biv‐WC* or mORCVax* or mORC‐vax* or choleratoxin* or cholera‐toxin* or vaxchora* or vax‐chora* or hillchol* or BBV131*).tw,kf.

60 Rabies/

61 rabies*.tw,kf.

62 rabies vaccines/

63 (rabAvert* or rabipur* or rabivax* or speeda* or imovax* or rabix‐vc* or verorab* or ChAdOx2 RabG* or HDCV* or hyperRab* or abhayrab* or indirab*).tw,kf.

64 Typhoid Fever/

65 (thypoid* or (salmonell* and typhi*)).tw,kf.

66 Typhoid‐Paratyphoid Vaccines/

67 (Vi adj3 vaccine*).tw,kf.

68 (ty800* or Vi‐rEPA* or typhax* or Vi‐TCV* or TyphiBEV* or "Vi‐DT" or "Vi‐TT" or "Typhim Vi" or PQed TCV or "CVD 909" or iNTS‐TCV or iNTS‐GMMA or Vi‐CRM197 or EuTCV or Typbar‐TCV or Vi‐CRM or Vi‐CRM197 or Pectin‐rEPA or Typherix).tw,kf.

69 vaccines/

70 (vaccin* or toxoid* or immuniz* or immunis* or booster* or revaccin*).tw,kf,nm.

71 (52 or 54 or 55 or 57 or 58 or 60 or 61 or 64 or 65) and (69 or 70)

72 53 or 56 or 59 or 62 or 63 or 67 or 66 or 68

73 47 or 71 or 72

74 18 and 73

75 randomized controlled trial.pt.

76 controlled clinical trial.pt.

77 randomi?ed.ab.

78 placebo.ab.

79 drug therapy.fs.

80 randomly.ab.

81 trial.ab.

82 groups.ab.

83 or/75‐82

84 exp animals/ not humans/

85 83 not 84

86 clinical trial, phase III/

87 ("Phase 3" or "phase3" or "phase III" or P3 or "PIII").ti,ab,kw.

88 (86 or 87) not 84

89 85 or 88

90 74 and 89

Note: Lines 75‐85 RCT filter: Cochrane Highly Sensitive Search Strategy for identifying randomized trials in MEDLINE: sensitivity‐maximizing version (2008 revision); Ovid format. (Lefebvre 2022). We made the following minor revisions: we used “random?ed.ab. instead of “randomized.ab” to capture word variations such as randomised and randomized.
Lines 86‐88 Phase III filter (Cooper 2019). 

Appendix 2. Preliminary Cochrane COVID‐19 Study Register search strategy

Search I and search II will be run separately.

Search I:

cancer* or neoplas* or malignan* or tumor* or tumour* or sarcom* or lymphom* or leukem* or leukaem* or myelom* or germinoblastom* or reticulolymphosarcom* or reticulosarcom* or granulom* or carcino* or melano* or metastas* or mesothelio* or mesotelio* or gliom* or glioblastom* or osteosarcom* or blastom* or neuroblastom* or adenocarcinoma* or myeloma* or onco* or chemotherap* or "chemo‐therapy" or "anti‐cancer" or anticancer* or antitumor* or antitumour* or "anti‐tumor" or "anti‐tumour" or anticarcino* or "anti‐carcinogenic" or antineoplastic* or "anti‐neoplastic"

AND 

vaccin* 

AND 

COVID or COVID19 or "SARS‐CoV‐2" or "SARS‐CoV2" or SARSCoV2 or "SARSCoV‐2" or "SARS coronavirus 2" or "2019 nCoV" or "2019nCoV" or "2019‐novel CoV" or "nCov 2019" or "nCov 19" or "severe acute respiratory syndrome coronavirus 2" or "novel coronavirus disease" or "novel corona virus disease" or "corona virus disease 2019" or "coronavirus disease 2019" or "novel coronavirus pneumonia" or "novel corona virus pneumonia" or "severe acute respiratory syndrome coronavirus 2" 

study characteristics:

1. Study design: Parallel/crossover, unclear

2. Intervention assignment: randomised, unclear

 

Search II:

cancer* or neoplas* or malignan* or tumor* or tumour* or sarcom* or lymphom* or leukem* or leukaem* or myelom* or germinoblastom* or reticulolymphosarcom* or reticulosarcom* or granulom* or carcino* or onco* or chemotherap* or "chemo‐therapy" or "anti‐cancer" or anticancer* or antitumor* or antitumour* or "anti‐tumor" or "anti‐tumour" or antineoplastic*

AND

biontech* or pfizer* or corminaty* or comirnaty* or BNT162* or "BNT 162" or "BNT 162b2" or tozinameran* or moderna* or spikevax* or 1273* or elasomeran* or mrna1273* or "TAK‐919" or "CX‐024414" or CX024414* or astrazeneca* or "astra‐zeneca" or vaxzevria* or azd1222* or covishield* or AZD2816* or CHAdOx* or Janssen* or "JNJ‐78436735" or "JNJ78436735" or VAC31518* or "VAC‐31518" or "Johnson COVID‐19" or "Johnson COVID19" or Jcovden* or ad26* or Sputnik* or rAd26* or rAd5* or gamaleya* or "Gam‐COVID‐Vac" or "recombinant adenovirus type" or "adenovirus vector" or "combined vector" or BBIBP* or BIBP* or sinopharm* or sinovac* or PiCoVac* or CoronaVac* or "NVX‐CoV2373" or novavax* or covovax* or "Matrix‐M" or "Matrix‐M1" or nuvaxovid* or AD5* or Convidecia or Pakvac or covaxin* or BBV152* or "heterologous boost" or "heterologous booster" or "homologous boost" or "homologous booster" or "post‐boost" or "post‐booster" or "boost schedule" or "boost schedules" or "bost dose" or "booster dose" or "after boost" or "after booster" or "variant boost" or "variant booster" or "delayed boost" or "delayed booster" or bosted or revaccination*

study characteristics:

1. Study design: Parallel/crossover, unclear

2. Intervention assignment: randomised, unclear

Contributions of authors

AB: methodological expertise, conception and writing of the protocol

CH: methodological expertise, conception and writing of the protocol

NK: methodological expertise, conception and writing of the protocol

PJB: clinical expertise and advice

SM: clinical expertise and advice

IM: development of the search strategy

NS: methodological expertise and advice, and conception of the protocol

Sources of support

Internal sources

• University Hospital of Cologne, Germany

  Cochrane Haematology, Department I of Internal Medicine

External sources

• Federal Ministry of Education and Research, Germany

  Funding number: 01KG2104

Declarations of interest

AB: staff at Cochrane Haematology

CH: Managing Editor at Cochrane Haematology

NK: staff at Cochrane Haematology

PJB: none known

SM: Gilead Foundation (travel), Octapharma USA Inc (consultant)

IM: Information Specialist at Cochrane Haematology

NS: Co‐ordinating Editor of Cochrane Haematology

The authors AB, CH, NK, IM, and NS are affiliated with Cochrane Haematology, but are not otherwise involved with the editorial process.

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