How to Read: Global cancer statistics, 2012 [Reading Guide]
Lindsey A. Torre, F. Bray, R. Siegel, J. Ferlay, J. Lortet-Tieulent, A. Jemal · 2015 · Ca
Three-Pass Reading Method
The three-pass reading method is a systematic approach designed to efficiently extract maximum understanding from research papers. The first pass (5-10 minutes) gives you a high-level overview by skimming the title, abstract, introduction, and conclusion. The second pass (up to 1 hour) involves careful reading of the paper with emphasis on methodology and key technical details. The third pass (1-5 hours) focuses on deep understanding, critical analysis, and connecting ideas to related work.
This structured approach helps you determine a paper's relevance quickly, then dive deeper only when needed, making your research workflow more efficient and effective.
This guide will help you efficiently read "Global cancer statistics, 2012" by Torre et al., published in Ca in 2015, using a three-pass approach.
First pass (5–10 min)
The goal of the first pass is to get a high-level overview of the paper's main contributions, the problem it addresses, and its overall scope.
-
What to skim:
- Title: "Global cancer statistics, 2012" immediately tells you this is a descriptive epidemiological paper focusing on worldwide cancer burden for a specific year.
- Abstract: Read this carefully. It summarizes the key findings: 14.1 million new cases and 8.2 million deaths in 2012, the shift of burden to less developed countries, leading cancer types by region and sex, and the role of risk factors and prevention.
- Introduction (first and last paragraphs): The first paragraph sets the context of cancer as a global burden. The last paragraph outlines the paper's objective: to provide a comprehensive overview of the global cancer burden in 2012 using GLOBOCAN estimates.
- Conclusion: Read the final paragraph of the "Discussion" section (which serves as the conclusion). It reiterates the major findings and emphasizes the potential for prevention.
-
What to notice:
- Contributions: The paper provides comprehensive estimates of cancer incidence and mortality worldwide for 2012, broken down by region, sex, and specific cancer types. It highlights disparities between more and less developed countries and identifies key risk factors.
- Problem: Cancer constitutes an enormous and increasing burden globally, with a significant shift towards less developed countries, where resources for prevention and treatment are often limited.
- Setting: This is a global epidemiological study, using data compiled by GLOBOCAN 2012, focusing on descriptive statistics rather than experimental results.
Second pass (up to 1 hour)
Using SpatialRead in the Second Pass
- Use the Screenshot tool to capture figures, tables, diagrams, and formulae from the PDF and use AI for simple explanations.
- Ask: "Explain Figure X at a high level", "Compare Table 2 vs 3", or "What does the y-axis represent here?"
- Download SpatialRead →
In the second pass, you'll delve deeper into the core findings and methodologies, focusing on key sections and figures that present the main data.
-
What sections/figures to focus on:
- "Methods" section: Skim this section to understand the data sources (GLOBOCAN 2012) and the general approach to estimation. Note that incidence and mortality estimates are based on national cancer registries and statistical modeling where data is sparse.
- "Results" section: This is the heart of the paper. Focus on the initial paragraphs of each subsection and the accompanying figures and tables.
- Global Burden: Read the first few paragraphs.
- Figure 1: Examine the pie charts showing the distribution of new cancer cases and deaths by more and less developed regions. This visually confirms the shift in burden.
- Table 1: Review the estimated number of new cancer cases and deaths worldwide and by region (more/less developed) for both sexes combined and separately. This provides the raw numbers behind Figure 1.
- Leading Cancers:
- Figure 2: Study the bar charts illustrating the ten leading cancer types by incidence and mortality, globally and by sex. This quickly shows which cancers are most prevalent and deadly.
- Table 2: Examine the estimated number of new cancer cases and deaths for the 10 leading cancer types, globally and by region. This table provides the detailed numbers for the trends shown in Figure 2.
- Regional Patterns:
- Figure 3: Analyze the bar charts comparing age-standardized incidence and mortality rates by region and sex. This highlights the disparities in rates between different regions.
- Figure 4: Focus on the leading cancer types in more developed regions.
- Figure 5: Focus on the leading cancer types in less developed regions. Compare these two figures to understand the distinct cancer profiles in different economic settings.
- Global Burden: Read the first few paragraphs.
- "Discussion" section: Read the initial paragraphs that summarize the main findings and highlight the most important observations.
-
Key terms/questions to note:
- Terms: Incidence, mortality, age-standardized rates, more developed regions, less developed regions, GLOBOCAN, specific cancer types (e.g., lung, breast, colorectal, prostate, liver, stomach, cervical).
- Questions: What are the overall global trends? How do cancer patterns differ between more and less developed countries? Which cancers are most significant in each region and sex? What are the major risk factors identified?
Third pass (1–5 hours)
Using SpatialRead in the Third Pass
- Highlight complex keywords, dense paragraphs, equations, or proofs and ask for a plain-English explanation that preserves notation.
- Use AI to explain the concepts in a way that is easy to understand.
- Ask for alternative phrasings or analogies to confirm understanding without changing technical meaning.
- Connect concepts with each other using AI to build a comprehensive understanding of the paper.
- Download SpatialRead →
The third pass involves a deep, critical reading of the entire paper, scrutinizing the methods, results, limitations, and implications.
-
Deep reading guidance:
- "Methods" section: Read this section thoroughly. Understand the specific data sources for each country, the statistical methods used for estimation (especially for countries with incomplete data), and any assumptions made. This is crucial for evaluating the reliability of the statistics.
- "Results" section: Go through every paragraph and cross-reference the text with all figures and tables. Pay close attention to the nuances of regional and sex-specific differences. Understand the magnitude of the burden for each cancer type and how it compares across regions. Note the discussion of specific risk factors associated with the leading cancers.
- "Discussion" section: Read this section critically. Evaluate the authors' interpretation of their findings. Understand the explanations provided for observed disparities (e.g., differences in risk factor prevalence, screening practices, access to treatment). Pay close attention to the "Limitations" subsection, which discusses potential biases and uncertainties in the estimates due to data quality and estimation methods. Finally, consider the implications for cancer control and prevention strategies outlined in the concluding paragraphs.
- References: Briefly scan the references to identify key sources for further reading on specific topics or methodologies.
-
Replication pointers:
- This paper presents descriptive statistics derived from the GLOBOCAN 2012 database, rather than an experimental study. Therefore, "replication" would involve verifying the reported statistics.
- To do this, you would need to access the raw GLOBOCAN 2012 data (if publicly available) and apply the same estimation methodologies described in the "Methods" section. This would allow you to confirm the calculations and assess the robustness of the estimates.
- Focus on understanding the specific algorithms and assumptions used to generate incidence and mortality rates, particularly for countries with limited or no cancer registry data. This will help you critically evaluate the validity and generalizability of the findings.