Okay, so I am, I want to perform a study that is systematic review and meta-analysis on the topic of, it is on the topic of efficacy of cardioprotective therapies in preventing trastuzumab-related cardiotoxicity in HER2-positive breast cancer, a systematic review and meta-analysis, okay? So this I have to do in a group of three people. I have to take two people under me, so I'll be leading the team of three and we'll be proceeding with this paper, okay? Now, honestly speaking, I don't know anything about doing a meta-analysis. It's just I, I want to do, but I really don't know how to do it. So explain me please, each and every step, what I would require to do a meta-analysis secondly, please help me make a template or provide me a template of like containing title, type of study, and you know, then the search string and the databases I need to look upon for this paper and the total number of papers to be screened, like title screening, the abstracts and left and duplicates, etc., and inclusion exclusion criteria and the data extraction part, everything till the last end. And starting from the PRISMA as well. So guide me through it, please, please, please.

Reading Document
Medical Text Search

trastuzumab cardiotoxicity HER2 breast cancer cardioprotective therapies prevention

Medical Text Search

systematic review meta-analysis methodology PRISMA flow diagram steps

GradeResponse
GradeResponse
Now I have enough context. Let me give you a thorough, structured guide.

Complete Guide: Systematic Review & Meta-Analysis

Efficacy of Cardioprotective Therapies in Preventing Trastuzumab-Related Cardiotoxicity in HER2-Positive Breast Cancer


PART 1: WHAT IS A META-ANALYSIS? (Start Here)

Think of it as a study of studies. Instead of collecting patients yourself, you:
  1. Find all existing studies on your topic
  2. Pool their data mathematically
  3. Calculate one combined, more powerful answer
The logic: if one study has 50 patients and another has 60, pooling them gives you 110 patients worth of evidence — far more reliable.
Your topic in simple terms: Does giving heart-protective drugs (like beta-blockers, ACE inhibitors) prevent the heart damage that trastuzumab (Herceptin) causes in HER2+ breast cancer patients?

PART 2: STEP-BY-STEP WORKFLOW (From Zero to Published)

STEP 1 → Register your protocol (PROSPERO)
STEP 2 → Develop your PICO question
STEP 3 → Write search strings & search databases
STEP 4 → Import results → Remove duplicates
STEP 5 → Title & Abstract screening
STEP 6 → Full-text screening
STEP 7 → Data extraction
STEP 8 → Quality/Risk of Bias assessment
STEP 9 → Statistical meta-analysis
STEP 10 → Write PRISMA flow diagram
STEP 11 → Write & submit the paper

STEP 1 — REGISTER ON PROSPERO (Do This FIRST, Before Searching)

  • Website: prospero.york.ac.uk
  • Free registration, takes ~1–2 hours
  • You submit your protocol (what you plan to do) BEFORE doing it
  • This prevents publication bias and gives your study a registration number (e.g., CRD42024XXXXXXX)
  • Why it matters: Most journals now REQUIRE a PROSPERO number
What to fill in PROSPERO:
  • Title, team members, PICO, databases to be searched, inclusion/exclusion criteria, outcomes, statistical methods

STEP 2 — YOUR PICO FRAMEWORK

PICO is the skeleton of your entire study:
LetterStands ForYour Study
PPopulationAdult patients (≥18 yrs) with HER2-positive breast cancer receiving trastuzumab
IInterventionCardioprotective therapies (beta-blockers, ACE inhibitors, ARBs, statins, dexrazoxane)
CComparisonPlacebo / no cardioprotection / standard care
OOutcomeCardiotoxicity (decline in LVEF, heart failure, cardiac events, troponin rise)

STEP 3 — SEARCH STRINGS & DATABASES

Databases to Search (All Free or Institutional Access):

#DatabaseURLWhy
1PubMed/MEDLINEpubmed.ncbi.nlm.nih.govGold standard, most comprehensive
2Embaseembase.comStrong for pharmacology & European studies
3Cochrane Librarycochranelibrary.comBest for RCTs
4ClinicalTrials.govclinicaltrials.govUnpublished/ongoing trials (reduces bias)
5Scopusscopus.comBroad coverage
6Web of Sciencewebofscience.comCitation tracking
Tip for your team: Divide databases — Person A: PubMed + Cochrane, Person B: Embase + Scopus, You: Web of Science + ClinicalTrials.gov

Your PubMed Search String (Copy-Paste Ready):

("trastuzumab"[MeSH Terms] OR "trastuzumab"[tiab] OR "Herceptin"[tiab])
AND
("HER2"[tiab] OR "HER-2"[tiab] OR "ErbB2"[tiab] OR "HER2-positive"[tiab])
AND
("breast cancer"[MeSH Terms] OR "breast neoplasms"[MeSH Terms] OR "breast cancer"[tiab])
AND
("cardiotoxicity"[tiab] OR "cardioprotection"[tiab] OR "cardiac toxicity"[tiab]
OR "left ventricular dysfunction"[tiab] OR "LVEF decline"[tiab]
OR "heart failure"[MeSH Terms] OR "cardiomyopathy"[tiab])
AND
("beta-blocker"[tiab] OR "beta blocker"[tiab] OR "carvedilol"[tiab]
OR "metoprolol"[tiab] OR "ACE inhibitor"[tiab] OR "ACE-inhibitor"[tiab]
OR "angiotensin converting enzyme inhibitor"[tiab] OR "enalapril"[tiab]
OR "lisinopril"[tiab] OR "ARB"[tiab] OR "angiotensin receptor blocker"[tiab]
OR "candesartan"[tiab] OR "statin"[tiab] OR "dexrazoxane"[tiab]
OR "cardioprotective"[tiab] OR "cardioprotection"[tiab])

Embase Search String:

('trastuzumab'/exp OR trastuzumab:ti,ab)
AND ('HER2'/exp OR 'HER2 positive breast cancer'/exp OR her2:ti,ab)
AND ('breast cancer'/exp OR 'breast neoplasm'/exp)
AND ('cardiotoxicity'/exp OR cardiotoxicity:ti,ab OR 'cardiac toxicity':ti,ab)
AND ('cardioprotection'/exp OR 'beta blocker'/exp OR 'ACE inhibitor'/exp
OR carvedilol:ti,ab OR metoprolol:ti,ab OR enalapril:ti,ab
OR candesartan:ti,ab OR statin:ti,ab OR dexrazoxane:ti,ab)

STEP 4 — IMPORT & DEDUPLICATE

Tool to use: Rayyan (rayyan.ai — completely free)
  1. Export all search results as .ris or .nbib files from each database
  2. Import all files into Rayyan
  3. Rayyan auto-detects duplicates — you review and confirm
  4. Assign your two team members as reviewers in Rayyan
  5. Enable blinding (reviewers screen independently — they can't see each other's decisions)

PART 3: THE MASTER TEMPLATE


📋 PROTOCOL TEMPLATE — COMPLETE

═══════════════════════════════════════════════════════════════════
SYSTEMATIC REVIEW & META-ANALYSIS PROTOCOL
═══════════════════════════════════════════════════════════════════

TITLE:
Efficacy of Cardioprotective Therapies in Preventing
Trastuzumab-Related Cardiotoxicity in HER2-Positive Breast Cancer:
A Systematic Review and Meta-Analysis

TYPE OF STUDY: Systematic Review and Meta-Analysis

PROSPERO REGISTRATION NO.: [To be filled after registration]
Registration Date: [Date]

DATE OF PROTOCOL: [Date]
Last Updated: [Date]

───────────────────────────────────────────────────────────────────
TEAM MEMBERS
───────────────────────────────────────────────────────────────────
Lead Author (Principal Investigator): [Your Name]
  Role: Protocol development, search strategy, data extraction,
        statistical analysis, manuscript writing

Co-Author 2: [Name]
  Role: Independent title/abstract screening, full-text screening,
        data extraction, quality assessment

Co-Author 3: [Name]
  Role: Independent title/abstract screening, full-text screening,
        data extraction, quality assessment

Conflict Arbiter (for disagreements): [Your Name as Lead]

───────────────────────────────────────────────────────────────────
PICO FRAMEWORK
───────────────────────────────────────────────────────────────────
P (Population):
  - Adult patients (age ≥18 years)
  - Diagnosed with HER2-positive breast cancer
  - Receiving trastuzumab-based therapy (any line)

I (Intervention):
  - Cardioprotective pharmacological therapies including:
    · Beta-blockers (carvedilol, metoprolol, bisoprolol, nebivolol)
    · ACE Inhibitors (enalapril, lisinopril, ramipril)
    · Angiotensin Receptor Blockers/ARBs (candesartan, valsartan)
    · Statins (atorvastatin, rosuvastatin)
    · Dexrazoxane
    · Combination therapy

C (Comparator):
  - Placebo
  - No cardioprotective therapy
  - Standard care alone

O (Outcomes):
  PRIMARY:
    1. Incidence of cardiotoxicity defined as:
       - LVEF (Left Ventricular Ejection Fraction) decline ≥10%
         from baseline to <53% (ESMO criteria)
       - OR LVEF decline ≥5% to <55% with symptoms
    2. Rate of trastuzumab discontinuation due to cardiac reasons

  SECONDARY:
    1. Change in LVEF (%) from baseline — continuous outcome
    2. Incidence of clinical heart failure (HF)
    3. Troponin elevation (as marker of subclinical damage)
    4. NT-proBNP changes
    5. All-cause mortality
    6. Cardiac-related hospitalizations

───────────────────────────────────────────────────────────────────
SEARCH STRATEGY
───────────────────────────────────────────────────────────────────
Databases:
  1. PubMed/MEDLINE
  2. Embase
  3. Cochrane Central Register of Controlled Trials (CENTRAL)
  4. Scopus
  5. Web of Science
  6. ClinicalTrials.gov (grey literature)

Date Range: January 2000 – Present
  (Trastuzumab FDA approval was 1998; 2000 allows landmark trials)

Language: English (primary); include non-English with translation
           if resources allow

[Insert full search strings for each database above]

───────────────────────────────────────────────────────────────────
INCLUSION CRITERIA
───────────────────────────────────────────────────────────────────
✓ Randomized Controlled Trials (RCTs) — PRIMARY focus
✓ Prospective cohort studies (if RCT data insufficient)
✓ HER2-positive breast cancer patients
✓ Trastuzumab used as part of therapy (adjuvant or metastatic)
✓ At least one cardioprotective therapy used as intervention
✓ Cardiac outcome data reported (LVEF or clinical cardiac events)
✓ Minimum follow-up: 3 months
✓ Sample size: ≥20 patients per group

───────────────────────────────────────────────────────────────────
EXCLUSION CRITERIA
───────────────────────────────────────────────────────────────────
✗ Case reports, case series (<20 patients)
✗ Review articles, editorials, letters, commentaries
✗ Animal studies / in-vitro / preclinical studies
✗ Studies without a control/comparator group
✗ Studies not reporting any cardiac outcome
✗ Patients receiving pertuzumab or TDM-1 without trastuzumab
✗ Duplicate publications (keep the most complete dataset)
✗ Conference abstracts with insufficient data

───────────────────────────────────────────────────────────────────
SCREENING PROCESS (PRISMA-Based)
───────────────────────────────────────────────────────────────────

PHASE 1 — IDENTIFICATION
  Action: Run all search strings across all 6 databases
  Expected yield: 800–2000 records (varies widely)
  Tool: Export as .ris/.nbib files

PHASE 2 — DEDUPLICATION
  Action: Import all into Rayyan; remove duplicates
  Expected: Remove ~20–35% as duplicates
  Record: Total unique records after deduplication

PHASE 3 — TITLE & ABSTRACT SCREENING
  Who: ALL THREE team members screen INDEPENDENTLY (blinded)
  Tool: Rayyan (blinding mode ON)
  Decision: Include / Exclude / Maybe
  Conflict resolution: Discuss; if unresolved → third-party

  Screened by reading ONLY the title and abstract.
  Apply inclusion/exclusion criteria.
  When in doubt → INCLUDE (err on side of caution)

PHASE 4 — FULL-TEXT SCREENING
  Who: All three team members (independently, then compare)
  Action: Retrieve full PDFs and apply strict criteria
  Exclusion at this stage must be DOCUMENTED with reason

PHASE 5 — FINAL INCLUDED STUDIES
  These are the studies that enter data extraction

Kappa Agreement: Calculate Cohen's Kappa (κ) after each phase
  κ > 0.80 = excellent agreement ✓

───────────────────────────────────────────────────────────────────
EXPECTED PRISMA NUMBERS (Template — Fill In As You Go)
───────────────────────────────────────────────────────────────────

  Records identified via database searching:     ____
    PubMed:              ____
    Embase:              ____
    Cochrane:            ____
    Scopus:              ____
    Web of Science:      ____
    ClinicalTrials.gov:  ____

  Additional records from other sources
  (manual reference searching):                  ____

  TOTAL RECORDS IDENTIFIED:                      ____

  ↓
  Duplicates removed:                            ____

  RECORDS AFTER DEDUPLICATION:                   ____

  ↓
  Title & Abstract Screened:                     ____
  Excluded at T&A stage (with reason):           ____

  FULL-TEXTS ASSESSED FOR ELIGIBILITY:           ____
  Full-texts excluded (with reasons):            ____
    - Not HER2-positive:           ____
    - No cardioprotective therapy: ____
    - No cardiac outcome:          ____
    - Wrong study design:          ____
    - Insufficient data:           ____
    - Duplicate dataset:           ____

  STUDIES INCLUDED IN META-ANALYSIS:             ____

───────────────────────────────────────────────────────────────────
DATA EXTRACTION FORM (Per Study)
───────────────────────────────────────────────────────────────────
Extract independently by 2 reviewers; resolve discrepancies by
discussion or lead author decision.

STUDY IDENTIFICATION
  First Author:
  Year of Publication:
  Country:
  Funding Source:
  Trial Registration Number:
  Study Design (RCT/Cohort):
  Follow-up Duration (months):

POPULATION
  Total Sample Size (N):
  Intervention Group (n):
  Control Group (n):
  Mean Age (years):
  % Female:
  Stage of Breast Cancer:
  HER2 confirmation method (IHC/FISH):
  Prior anthracycline use (Yes/No/%):
  Baseline LVEF (%):

INTERVENTION
  Cardioprotective drug used:
  Dose:
  Duration of therapy:
  Started: Before trastuzumab / During / After
  Concurrent anthracycline use: Yes/No

CONTROL
  Placebo / No therapy / Other:

PRIMARY OUTCOMES
  Cardiotoxicity incidence:
    Intervention group: n/N (%)
    Control group: n/N (%)
    Relative Risk or Odds Ratio (if reported):
    p-value:
    95% CI:
  Trastuzumab discontinuation (cardiac):
    Intervention: n/N (%)
    Control: n/N (%)

SECONDARY OUTCOMES
  Mean LVEF at baseline — Intervention: ___  Control: ___
  Mean LVEF at follow-up — Intervention: ___  Control: ___
  Mean LVEF change (ΔEF) — Intervention: ___  Control: ___
  SD of LVEF change — Intervention: ___  Control: ___
  Heart failure events: n (%)
  Troponin elevation: n (%)
  Hospitalizations: n (%)

NOTES / SPECIAL CONSIDERATIONS:

───────────────────────────────────────────────────────────────────
RISK OF BIAS ASSESSMENT
───────────────────────────────────────────────────────────────────
For RCTs → Use: Cochrane RoB 2.0 Tool
For Cohort Studies → Use: Newcastle-Ottawa Scale (NOS)

RoB 2.0 Domains:
  D1. Randomization process
  D2. Deviations from intended interventions
  D3. Missing outcome data
  D4. Measurement of the outcome
  D5. Selection of reported result
  Overall: Low / Some concerns / High

Assessed by: 2 reviewers independently
Tool: RoB 2.0 Excel template (available from Cochrane)

───────────────────────────────────────────────────────────────────
STATISTICAL ANALYSIS PLAN
───────────────────────────────────────────────────────────────────
Software: RevMan 5.4 (free, from Cochrane) — RECOMMENDED FOR BEGINNERS
           OR: R (meta package) / STATA (metaan)

Effect Measures:
  - Dichotomous outcomes (cardiotoxicity incidence, HF events):
    → Risk Ratio (RR) with 95% CI
  - Continuous outcomes (LVEF change):
    → Mean Difference (MD) or Standardized MD with 95% CI

Heterogeneity:
  - Assessed using Cochran's Q test and I² statistic
  - I² interpretation:
      0–25%   = Low heterogeneity → Fixed-effects model
      26–50%  = Moderate → Random-effects model
      51–75%  = Substantial → Random-effects + subgroup analysis
      >75%    = Considerable → Report with caution; focus on subgroups

Model:
  → Random-effects model (DerSimonian-Laird) recommended as default
    given expected clinical heterogeneity

Subgroup Analyses:
  1. By drug class (beta-blocker vs ACE-I vs ARB vs statin)
  2. By concurrent anthracycline use (yes vs no)
  3. By baseline LVEF (preserved vs borderline)
  4. By cancer stage (early vs metastatic)
  5. By follow-up duration (<6 months vs ≥6 months)

Sensitivity Analysis:
  - Exclude high RoB studies → check if results change
  - Exclude small studies (n<50)
  - One study leave-out analysis

Publication Bias:
  - Funnel plot (requires ≥10 studies)
  - Egger's test / Begg's test

GRADE Assessment:
  Rate overall certainty of evidence as:
  High / Moderate / Low / Very Low
  Using: GRADEpro GDT (free online tool)

───────────────────────────────────────────────────────────────────
REPORTING
───────────────────────────────────────────────────────────────────
Follow: PRISMA 2020 Checklist (27 items)
         Available at: prisma-statement.org

Target Journals (Suggested):
  High Impact: JACC, European Heart Journal, JCO
  Mid-tier: Cardio-Oncology, Breast Cancer Research & Treatment,
            PLOS ONE, Frontiers in Oncology

───────────────────────────────────────────────────────────────────
TIMELINE (Suggested — 6 Month Plan)
───────────────────────────────────────────────────────────────────
Month 1: PROSPERO registration + Search execution + Deduplication
Month 2: Title/Abstract screening (all 3 members)
Month 3: Full-text screening + Retrieval of PDFs
Month 4: Data extraction + Risk of Bias assessment
Month 5: Statistical analysis + Figures (forest plots, funnel plots)
Month 6: Manuscript writing + Internal review + Journal submission

═══════════════════════════════════════════════════════════════════

PART 4: YOUR PRISMA FLOW DIAGRAM (Explained)

The PRISMA flow diagram is a box diagram that journals require. It looks like this:
┌─────────────────────────────────────────┐
│  IDENTIFICATION                          │
│  Records from databases (n = ____)       │
│  Records from other sources (n = ____)  │
└──────────────────┬──────────────────────┘
                   ↓
┌─────────────────────────────────────────┐
│  After duplicates removed (n = ____)    │
└──────────────────┬──────────────────────┘
                   ↓
┌─────────────────────────────────────────┐  ──→  Excluded (n = ____)
│  SCREENING                               │       Reasons:
│  Titles & Abstracts screened (n = ____) │       - Not relevant: ____
└──────────────────┬──────────────────────┘       - Wrong population: ____
                   ↓
┌─────────────────────────────────────────┐  ──→  Excluded with reasons
│  ELIGIBILITY                             │       (n = ____)
│  Full-texts assessed (n = ____)         │
└──────────────────┬──────────────────────┘
                   ↓
┌─────────────────────────────────────────┐
│  INCLUDED                                │
│  Studies in meta-analysis (n = ____)    │
└─────────────────────────────────────────┘
Draw it using: Microsoft Word SmartArt, Canva, or the free PRISMA Flow Diagram generator at prisma.thetacollaborative.ca

PART 5: TOOLS SUMMARY — ALL FREE

ToolPurposeLink
PROSPEROProtocol registrationprospero.york.ac.uk
RayyanScreening + deduplicationrayyan.ai
RevMan 5.4Meta-analysis + forest plotstraining.cochrane.org
RoB 2.0 ExcelRisk of bias for RCTsriskofbias.info
GRADEproEvidence certaintygradepro.org
PRISMA generatorFlow diagramprisma.thetacollaborative.ca
ZoteroReference managementzotero.org

PART 6: KEY BACKGROUND KNOWLEDGE FOR YOUR PAPER

  • Trastuzumab cardiotoxicity occurs in 3–7% of patients (up to 27% with concurrent anthracyclines). It manifests as Type II cardiotoxicity — typically reversible LVEF decline, unlike anthracycline-induced Type I (irreversible).
  • Landmark trials to know: MANTICORE trial (carvedilol/perindopril), CECCY trial (carvedilol), PRADA trial (candesartan + metoprolol)
  • Definition of cardiotoxicity varies between studies — this will be a key source of heterogeneity in your meta-analysis. Document which definition each study used.
  • Cardioprotective efficacy: Current evidence is mixed — ACE inhibitors and beta-blockers show modest benefit, particularly when anthracyclines are co-administered

QUICK START CHECKLIST FOR WEEK 1

  • Register on PROSPERO and submit protocol
  • Create shared folder (Google Drive/OneDrive) with all three team members
  • Create Rayyan account → invite both co-authors
  • Download RevMan 5.4
  • Run search strings on all databases → export .ris files
  • Import into Rayyan → remove duplicates
  • Begin title/abstract screening (independently, blinded)

You now have everything from PROSPERO to publication. Start with PROSPERO registration — that is non-negotiable and must happen before your first search. The most important rule during screening: both reviewers must screen independently, and all disagreements must be documented. Good luck with your team!

What do you think, do I have enough studies to, you know, do it, like, is it a good topic? Will I get a good amount of studies on this topic to screen upon and perform analysis or not?

Medical Text Search

cardioprotective therapy trastuzumab cardiotoxicity RCT clinical trials carvedilol ACE inhibitor candesartan

Medical Text Search

MANTICORE PRADA CECCY trial trastuzumab cardioprotection beta-blocker results

GradeResponse
GradeResponse
Here is an honest, direct assessment:

Yes — This is a Strong, Feasible Topic. Here's Why.


The Study Landscape (What Exists)

There are well-known, high-quality RCTs already published specifically on your exact topic. These are not obscure studies — they are landmark trials in cardio-oncology:
TrialDrug TestedYear
MANTICOREPerindopril vs Carvedilol vs Placebo2017
PRADACandesartan + Metoprolol2016
CECCYCarvedilol vs Placebo2018
OVERCOMEEnalapril + Carvedilol2013
SAFE-HEaRtBeta-blockers + ACE-I in borderline LVEF2018
ICOS-ONEEnalapril for troponin elevation2019
And beyond these landmark trials, there are dozens of smaller RCTs, prospective cohort studies, and observational studies from Europe, Asia, and the Americas. When you run your search strings, you can realistically expect to identify 600–1,500 records across all databases, narrowing down to roughly 20–45 eligible studies for final analysis — which is a very healthy number for a meta-analysis.

But Here is the Honest Reality Check

There are a few things you should be aware of before you start:
1. Prior Meta-Analyses Already Exist This topic has been meta-analyzed before — papers exist from 2018, 2020, 2022. This is actually not a dealbreaker, but you need to:
  • Frame your study as an updated meta-analysis (search up to 2024–2025)
  • Include newer trials that previous meta-analyses missed
  • Possibly narrow your focus slightly (e.g., "only RCTs" or "specific drug class" or "concurrent anthracycline use") to add novelty
2. Heterogeneity Will Be High Different studies define cardiotoxicity differently — some use LVEF <53%, others use a 10% drop, others use troponin. This will inflate your I² statistic. You handle this with subgroup analysis, which you already have planned.
3. The Debate Is Not Fully Settled Harrison's (p. 7244) explicitly notes: "it is not clear whether treatment enhances the spontaneous rate of improvement or whether it decreases progression." This actually works in your favor — an unsettled question is exactly what a meta-analysis should address.

How to Make Your Paper Stand Out

Since prior meta-analyses exist, here is how to position yours as genuinely novel:
StrategyHow
Update the evidenceSearch up to December 2024 — include all trials published after the last meta-analysis
Narrow to RCTs onlyMore rigorous, publishable in higher-tier journals
Subgroup by drug classBeta-blockers vs ACE-I vs ARBs separately — most prior reviews lump them together
Add GRADE assessmentMany older meta-analyses did not do this — adds significant value
Include trastuzumab discontinuation rateOften overlooked as an outcome

Bottom Line

Yes, do this topic. You will have enough studies. The field is active, the question is clinically important, and an updated, well-conducted meta-analysis with GRADE assessment will be publishable. The existence of prior meta-analyses means the foundation is solid — you are building on established ground, not starting from scratch in a barren field.
Your first task after reading this: go to PubMed right now and search "trastuzumab cardioprotection meta-analysis" — read the 2–3 most recent ones so you know exactly what has already been done and where your study fills the gap. That gap statement will be the backbone of your introduction.

Okay, so now give me a shortened version of version of this template, wherein I need to enter all the necessary information required and give it in a form that I can share with others as well.

write_file
Here is your complete, shareable protocol template. It is saved at /output/SR_MA_Protocol_Template.md — you can open it, copy it into a Word document or Google Doc, and share it directly with your two team members.

What the Template Contains (12 Sections):

#SectionWhat to Fill
1Study IdentificationTitle, PROSPERO number, date
2TeamYour names and roles
3PICOAlready filled — review and confirm
4OutcomesAlready defined — primary & secondary
5Search StrategyFill in date searched + record counts as you go
6Inclusion/Exclusion CriteriaAlready filled — add to if needed
7PRISMA Screening LogFill in numbers at each stage
8Data Extraction FormOne column per included study
9Risk of Bias SummaryFill after full-text inclusion
10Statistical Analysis PlanAlready decided — confirm with team
11TimelineFill in names and target dates
12Tools & ResourcesReady to use

How to Share It

  1. Copy the content into Google Docs → share the link with your two team members with edit access — everyone can fill it simultaneously
  2. Or paste into Microsoft Word → convert the tables to Word tables → share via email
  3. The Data Extraction Form (Section 8) — make a separate Google Sheet for this so all three of you can extract data in parallel without overwriting each other
The first thing all three of you should fill in together is Section 2 (your names/roles) and Section 11 (the timeline with actual dates). That sets accountability from day one.

The template isn’t opening

Reading Document
Reading Document
write_file
The template is now saved as a plain .txt file at /output/SR_MA_Protocol_Template.txt. Here is exactly how to open and share it:

Option 1 — Google Docs (Best for sharing with your team)

  1. Open Google Docs → File → New Document
  2. Copy everything from the text box below and paste it in
  3. Click Share → add your two team members' emails
  4. Everyone can edit simultaneously in real time

Option 2 — Microsoft Word

  1. Open Word → New blank document
  2. Paste the content in
  3. Save as .docx → share via WhatsApp, email, or Drive

Option 3 — WhatsApp / Email

  • Just copy the plain text directly and send it — it is readable as-is since it uses simple lines and spaces, no special formatting needed

The file is intentionally in plain text with no special characters so it opens perfectly in any application on any device — phone, laptop, tablet. Every blank line with underscores is a field your team fills in as the study progresses.

I am unable to open it

No problem at all. Here is the complete template directly on your screen — just copy everything below and paste it into Google Docs, Word, or even WhatsApp Notes:

================================================================
     SYSTEMATIC REVIEW & META-ANALYSIS — STUDY PROTOCOL
================================================================

SECTION 1 — STUDY IDENTIFICATION

Title       : Efficacy of Cardioprotective Therapies in
              Preventing Trastuzumab-Related Cardiotoxicity
              in HER2-Positive Breast Cancer:
              A Systematic Review and Meta-Analysis
Type        : Systematic Review and Meta-Analysis
PROSPERO No.: _______________________________
Reg. Date   : _______________________________
Version     : 1.0
Date        : _______________________________

================================================================
SECTION 2 — TEAM MEMBERS
================================================================

Lead / Principal Investigator
  Name : _______________________________
  Role : Protocol, search, analysis, writing

Co-Investigator 2
  Name : _______________________________
  Role : Independent screening, data extraction

Co-Investigator 3
  Name : _______________________________
  Role : Independent screening, data extraction

Conflict Arbiter: Lead Author

================================================================
SECTION 3 — PICO
================================================================

P — Population  : Adults (>=18 yrs), HER2-positive breast
                  cancer, receiving trastuzumab

I — Intervention: Cardioprotective therapy
                  (beta-blockers, ACE inhibitors, ARBs,
                  statins, dexrazoxane)

C — Comparator  : Placebo / No cardioprotective therapy /
                  Standard care

O — Outcomes    : Cardiotoxicity (LVEF decline, heart failure,
                  troponin rise, drug discontinuation)

================================================================
SECTION 4 — OUTCOMES
================================================================

PRIMARY
  1. Cardiotoxicity incidence
     (LVEF decline >=10% to <53% OR >=5% to <55% + symptoms)
  2. Trastuzumab discontinuation due to cardiac reasons

SECONDARY
  1. Mean change in LVEF (%) from baseline
  2. Incidence of clinical heart failure
  3. Troponin elevation
  4. NT-proBNP changes
  5. Cardiac-related hospitalizations
  6. All-cause mortality

================================================================
SECTION 5 — SEARCH STRATEGY
================================================================

Date Range : January 2000 – December 2024
Language   : English (primary)

DATABASE          DATE SEARCHED     RECORDS FOUND
PubMed            _____________     _____________
Embase            _____________     _____________
Cochrane CENTRAL  _____________     _____________
Scopus            _____________     _____________
Web of Science    _____________     _____________
ClinicalTrials    _____________     _____________
TOTAL                               _____________

PUBMED SEARCH STRING:

("trastuzumab"[MeSH Terms] OR "trastuzumab"[tiab]
OR "Herceptin"[tiab])
AND ("HER2"[tiab] OR "HER-2"[tiab]
OR "HER2-positive"[tiab])
AND ("breast cancer"[MeSH Terms]
OR "breast neoplasms"[MeSH Terms])
AND ("cardiotoxicity"[tiab] OR "cardiac toxicity"[tiab]
OR "LVEF decline"[tiab] OR "heart failure"[MeSH Terms]
OR "cardiomyopathy"[tiab])
AND ("beta-blocker"[tiab] OR "carvedilol"[tiab]
OR "metoprolol"[tiab] OR "ACE inhibitor"[tiab]
OR "enalapril"[tiab] OR "lisinopril"[tiab]
OR "candesartan"[tiab] OR "ARB"[tiab]
OR "statin"[tiab] OR "dexrazoxane"[tiab]
OR "cardioprotect*"[tiab])

================================================================
SECTION 6 — INCLUSION & EXCLUSION CRITERIA
================================================================

INCLUDE:
  1. RCTs (prospective cohorts if RCT data insufficient)
  2. HER2-positive breast cancer patients
  3. Trastuzumab as part of treatment
  4. At least one cardioprotective drug as intervention
  5. Cardiac outcome data reported (LVEF or cardiac events)
  6. Follow-up duration >= 3 months
  7. Sample size >= 20 patients per arm

EXCLUDE:
  1. Case reports / series (n <20)
  2. Reviews, editorials, letters, commentaries
  3. Animal / in-vitro / preclinical studies
  4. No comparator/control group
  5. No cardiac outcome reported
  6. Conference abstracts with no extractable data
  7. Duplicate publications (keep most complete dataset)

================================================================
SECTION 7 — PRISMA SCREENING LOG
================================================================

Screening Tool: Rayyan (rayyan.ai)

STAGE                                    COUNT
Total records (all databases)            _______
Duplicates removed                       _______
After deduplication                      _______
Excluded at title/abstract screening     _______
Full-texts assessed                      _______
Full-texts excluded — TOTAL              _______
  > Not HER2-positive                    _______
  > No cardioprotective therapy          _______
  > No cardiac outcome                   _______
  > Wrong study design                   _______
  > Insufficient data                    _______
  > Duplicate dataset                    _______
FINAL STUDIES INCLUDED                   _______

Cohen's Kappa after T&A screening : k = _______ (target >0.80)
Cohen's Kappa after full-text      : k = _______ (target >0.80)

================================================================
SECTION 8 — DATA EXTRACTION (One block per study)
================================================================

STUDY No.: ____
First Author                         : ____________________
Year                                 : ____________________
Country                              : ____________________
Study Design (RCT/Cohort)            : ____________________
Trial Registration No.               : ____________________
Funding Source                       : ____________________
Follow-up (months)                   : ____________________

POPULATION
  Total N                            : ____________________
  Intervention n                     : ____________________
  Control n                          : ____________________
  Mean Age (yrs)                     : ____________________
  % Female                           : ____________________
  Cancer Stage                       : ____________________
  HER2 Confirmation (IHC/FISH)       : ____________________
  Prior Anthracycline (Yes/No)       : ____________________
  Baseline LVEF (%)                  : ____________________

INTERVENTION
  Drug Used                          : ____________________
  Dose                               : ____________________
  Duration                           : ____________________
  Timing (before/during trastuzumab) : ____________________
  Concurrent Anthracycline (Yes/No)  : ____________________

CONTROL TYPE (placebo/none/other)    : ____________________

PRIMARY OUTCOMES
  Cardiotoxicity — Intervention      : ___/___  ( ____ %)
  Cardiotoxicity — Control           : ___/___  ( ____ %)
  RR / OR (95% CI)                   : ____________________
  p-value                            : ____________________
  Trastuzumab Stop — Intervention    : ___/___  ( ____ %)
  Trastuzumab Stop — Control         : ___/___  ( ____ %)

SECONDARY OUTCOMES
  LVEF Change — Intervention         : ______ % (SD: _____)
  LVEF Change — Control              : ______ % (SD: _____)
  HF Events — Intervention           : ______  ( ____ %)
  HF Events — Control                : ______  ( ____ %)
  Troponin Elevation                 : ____________________
  Hospitalizations                   : ____________________

Risk of Bias (RoB 2.0)               : Low / Some Concerns / High
Notes                                : ____________________

--- COPY ABOVE BLOCK FOR EACH ADDITIONAL STUDY ---

================================================================
SECTION 9 — RISK OF BIAS TABLE (Cochrane RoB 2.0)
================================================================
L = Low   H = High   ? = Some Concerns

STUDY      D1    D2    D3    D4    D5    OVERALL
________   ___   ___   ___   ___   ___   _______
________   ___   ___   ___   ___   ___   _______
________   ___   ___   ___   ___   ___   _______
________   ___   ___   ___   ___   ___   _______
________   ___   ___   ___   ___   ___   _______

D1=Randomization  D2=Deviations  D3=Missing Data
D4=Outcome Measurement  D5=Reported Results

================================================================
SECTION 10 — STATISTICAL ANALYSIS PLAN
================================================================

Software           : RevMan 5.4 (free — training.cochrane.org)
Dichotomous data   : Risk Ratio (RR) with 95% CI
Continuous data    : Mean Difference (MD) with 95% CI
Model              : Random-effects (DerSimonian-Laird)
Heterogeneity      : Cochran Q + I-squared (I2)
  I2 0-25%   = Low heterogeneity
  I2 26-50%  = Moderate
  I2 51-75%  = Substantial — do subgroup analysis
  I2 >75%    = Considerable — interpret with caution
Publication Bias   : Funnel plot + Egger's test (if >=10 studies)
Evidence Certainty : GRADE (gradepro.org)

SUBGROUP ANALYSES
  1. By drug class (beta-blocker/ACE-I/ARB/statin)
  2. By concurrent anthracycline use (yes/no)
  3. By baseline LVEF (preserved/borderline)
  4. By cancer stage (early/metastatic)
  5. By follow-up (<6 months / >=6 months)

SENSITIVITY ANALYSES
  1. Exclude high risk-of-bias studies
  2. Exclude studies with n <50 per arm
  3. Leave-one-out analysis

================================================================
SECTION 11 — TIMELINE
================================================================

MONTH   TASK                                      WHO
  1     PROSPERO + search + Rayyan import         All
  2     Title & abstract screening (blinded)      All
  3     Full-text screening + PDFs                All
  4     Data extraction + Risk of Bias            All
  5     Statistical analysis + forest plots       Lead
  6     Manuscript writing + submission           All

Target Submission Date : _______________________________
Target Journal         : _______________________________

================================================================
SECTION 12 — TOOLS
================================================================

PROSPERO        : prospero.york.ac.uk
Rayyan          : rayyan.ai
RevMan 5.4      : training.cochrane.org
RoB 2.0         : riskofbias.info
GRADEpro        : gradepro.org
PRISMA diagram  : prisma.thetacollaborative.ca
References      : zotero.org

================================================================
Protocol v1.0  |  Lead: _______________  |  Date: ___________
================================================================

To use this right now:

  1. Select all the text above from the first === line to the last one
  2. Copy it (Ctrl+C or long-press → Copy)
  3. Open Google Docs or Microsoft Word → paste it in
  4. Save and share the link with your team
That is all. No file download needed.

Okay, so give me a search string for PubMed and other web tools also, which is kind of very broad, so that I can get a lot of results. From the search string you gave me for PubMed, it is only revealing just one result over there. So give me that kind of a search string which reveals a lot of results, like a lot of papers, then I will have to screen, no? So I need around 200 to 300 papers initially to screen that.

The issue is your current search string is too specific — it requires ALL terms to match simultaneously. We need to loosen it significantly. Let me fix this.

PUBMED — Broad Search String

Go to pubmed.ncbi.nlm.nih.gov and paste this:
(trastuzumab OR Herceptin OR "anti-HER2") 
AND 
("breast cancer" OR "breast neoplasm" OR "breast carcinoma") 
AND 
(cardiotoxicity OR "cardiac toxicity" OR "cardio toxicity" 
OR "heart failure" OR cardiomyopathy OR "LVEF" 
OR "left ventricular" OR "ejection fraction" 
OR "cardiac dysfunction" OR "cardiac events")
This alone should give you 300–800+ results on PubMed. Do NOT add the drug names yet — that was the mistake before. You screen those papers manually.

IF YOU WANT EVEN MORE — Add This Variation:

(trastuzumab OR Herceptin) 
AND 
(cardiotoxicity OR cardioprotection OR "cardiac toxicity" 
OR "heart failure" OR "left ventricular dysfunction" 
OR "LVEF decline" OR cardiomyopathy OR "cardiac function")

OTHER DATABASES — Search Strings


COCHRANE LIBRARY

Website: cochranelibrary.com → go to Search
trastuzumab AND (cardiotoxicity OR "cardiac toxicity" 
OR "heart failure" OR "left ventricular")
Expected: 50–150 results (Cochrane is smaller but very high quality — mostly RCTs)

EMBASE

Website: embase.com (needs institutional login OR use through your college library)
'trastuzumab' AND ('cardiotoxicity' OR 'cardiac toxicity' 
OR 'heart failure' OR 'left ventricular dysfunction' 
OR 'cardiomyopathy') AND 'breast cancer'
Expected: 200–500 results

SCOPUS

Website: scopus.com
TITLE-ABS-KEY ( trastuzumab  AND  
( cardiotoxicity  OR  "cardiac toxicity"  
OR  "heart failure"  OR  "left ventricular"  
OR  "ejection fraction" )  
AND  "breast cancer" )
Expected: 150–400 results

WEB OF SCIENCE

Website: webofscience.com
TS = (trastuzumab AND ("breast cancer" OR "breast neoplasm") 
AND (cardiotoxicity OR "cardiac toxicity" OR "heart failure" 
OR "left ventricular" OR cardiomyopathy))
Expected: 150–350 results

CLINICALTRIALS.GOV

Website: clinicaltrials.gov → use the search bar (not an advanced string)
Search term 1: trastuzumab cardiotoxicity Search term 2: trastuzumab cardioprotection breast cancer
This gives you registered trials — important for finding unpublished or ongoing studies. Note down their NCT numbers.

GOOGLE SCHOLAR (Bonus — catches things others miss)

Website: scholar.google.com
trastuzumab cardiotoxicity "breast cancer" 
cardioprotection OR "beta blocker" OR "ACE inhibitor" 
OR carvedilol OR candesartan
Pick the first 3–4 pages of results only. Export using Zotero browser plugin.

Summary Table

DatabaseSearch String ComplexityExpected Results
PubMedBroad (3 concepts only)300–800
EmbaseBroad200–500
ScopusBroad150–400
Web of ScienceBroad150–350
CochraneNarrow (already small DB)50–150
ClinicalTrials.govKeyword only30–80
Google ScholarBroadUse first 3 pages
TOTAL~1000–2000

The Key Rule Here

Cast wide now, screen strictly later.
You want maximum results at the search stage. You will remove irrelevant papers during title/abstract screening in Rayyan. That is the whole point of the screening process — go from 1000+ down to 20–40 good studies. So do not worry if you get 1500 results — that is completely normal and expected for a meta-analysis.

What To Do Right Now — Step by Step

  1. Go to PubMed → paste the first broad string → click Search
  2. On results page → click Save → select All results → Format: PubMed → Download as .nbib file
  3. Repeat for each database → download as .ris or .csv
  4. Go to rayyan.ai → create new review → upload all files
  5. Rayyan auto-removes duplicates
  6. Start screening
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