scholarly journals Challenges for assessing replicability in preclinical cancer biology

eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Timothy M Errington ◽  
Alexandria Denis ◽  
Nicole Perfito ◽  
Elizabeth Iorns ◽  
Brian A Nosek

We conducted the Reproducibility Project: Cancer Biology to investigate the replicability of preclinical research in cancer biology. The initial aim of the project was to repeat 193 experiments from 53 high-impact papers, using an approach in which the experimental protocols and plans for data analysis had to be peer reviewed and accepted for publication before experimental work could begin. However, the various barriers and challenges we encountered while designing and conducting the experiments meant that we were only able to repeat 50 experiments from 23 papers. Here we report these barriers and challenges. First, many original papers failed to report key descriptive and inferential statistics: the data needed to compute effect sizes and conduct power analyses was publicly accessible for just 4 of 193 experiments. Moreover, despite contacting the authors of the original papers, we were unable to obtain these data for 68% of the experiments. Second, none of the 193 experiments were described in sufficient detail in the original paper to enable us to design protocols to repeat the experiments, so we had to seek clarifications from the original authors. While authors were extremely or very helpful for 41% of experiments, they were minimally helpful for 9% of experiments, and not at all helpful (or did not respond to us) for 32% of experiments. Third, once experimental work started, 67% of the peer-reviewed protocols required modifications to complete the research and just 41% of those modifications could be implemented. Cumulatively, these three factors limited the number of experiments that could be repeated. This experience draws attention to a basic and fundamental concern about replication – it is hard to assess whether reported findings are credible.

eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Timothy M Errington ◽  
Maya Mathur ◽  
Courtney K Soderberg ◽  
Alexandria Denis ◽  
Nicole Perfito ◽  
...  

Replicability is an important feature of scientific research, but aspects of contemporary research culture, such as an emphasis on novelty, can make replicability seem less important than it should be. The Reproducibility Project: Cancer Biology was set up to provide evidence about the replicability of preclinical research in cancer biology by repeating selected experiments from high-impact papers. A total of 50 experiments from 23 papers were repeated, generating data about the replicability of a total of 158 effects. Most of the original effects were positive effects (136), with the rest being null effects (22). A majority of the original effect sizes were reported as numerical values (117), with the rest being reported as representative images (41). We employed seven methods to assess replicability, and some of these methods were not suitable for all the effects in our sample. One method compared effect sizes: for positive effects, the median effect size in the replications was 85% smaller than the median effect size in the original experiments, and 92% of replication effect sizes were smaller than the original. The other methods were binary – the replication was either a success or a failure – and five of these methods could be used to assess both positive and null effects when effect sizes were reported as numerical values. For positive effects, 40% of replications (39/97) succeeded according to three or more of these five methods, and for null effects 80% of replications (12/15) were successful on this basis; combining positive and null effects, the success rate was 46% (51/112). A successful replication does not definitively confirm an original finding or its theoretical interpretation. Equally, a failure to replicate does not disconfirm a finding, but it does suggest that additional investigation is needed to establish its reliability.


eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Timothy M Errington ◽  
Alexandria Denis ◽  
Anne B Allison ◽  
Renee Araiza ◽  
Pedro Aza-Blanc ◽  
...  

As part of the Reproducibility Project: Cancer Biology, we published Registered Reports that described how we intended to replicate selected experiments from 29 high-impact preclinical cancer biology papers published between 2010 and 2012. Replication experiments were completed and Replication Studies reporting the results were submitted for 18 papers, of which 17 were accepted and published by eLife with the rejected paper posted as a preprint. Here, we report the status and outcomes obtained for the remaining 11 papers. Four papers initiated experimental work but were stopped without any experimental outcomes. Two papers resulted in incomplete outcomes due to unanticipated challenges when conducting the experiments. For the remaining five papers only some of the experiments were completed with the other experiments incomplete due to mundane technical or unanticipated methodological challenges. The experiments from these papers, along with the other experiments attempted as part of the Reproducibility Project: Cancer Biology, provides evidence about the challenges of repeating preclinical cancer biology experiments and the replicability of the completed experiments.


2018 ◽  
Vol 4 (2) ◽  
pp. 00140-2017 ◽  
Author(s):  
Pentti Nieminen ◽  
Tuula Toljamo ◽  
Hannu Vähänikkilä

Data analysis methods play an important role in respiratory research. We evaluated the application and complexity of data analytical methods in high-impact respiratory journals and compared the statistical reporting in these respiratory articles with reports published in other eminent medical journals.This study involved a total of 160 papers published in 2015 in the European Respiratory Journal, American Journal of Respiratory and Critical Care Medicine, Chest and Thorax, and 680 papers published between 2007–2015 in other medical journals including the Lancet and New England Journal of Medicine. We manually reviewed the articles to determine the way in which they reported the methods applied in data analysis.The statistical intensity in the respiratory journals was equal to that in eminent medical journals. Traditional ways of testing statistical significance were widely used in respiratory articles. Statistical procedures were not always described in sufficient detail, and the prominent respiratory journals did not display different profiles with respect to their statistical content.Readers of the prominent respiratory journals need to possess a substantial level of statistical expertise if they wish to critically evaluate the design, methodology, data analysis and interpretation of the findings published in these journals.


Author(s):  
Eka Fadilah

This survey aims to review statisical report procedures in the experimental studies appearing in ten SLA and Applied Linguistic journals from 2011 to 2017. We specify our study on how the authors report and interprete their power analyses, effect sizes, and confidence intervals. Results reveal that of 217 articles, the authors reported effect sizes (70%), apriori power and posthoc power consecutively (1.8% and 6.9%), and confidence intervals (18.4%). Additionally, it shows that the authors interprete those statistical terms counted 5.5%, 27.2%, and 6%, respectively. The call for statistical report reform recommended and endorsed by scholars, researchers, and editors is inevitably echoed to shed more light on the trustworthiness and practicality of the data presented.


2020 ◽  
Vol 23 (4) ◽  
pp. 76-89
Author(s):  
Narmin Rzayeva ◽  
Ilham Tagiyev ◽  
Azad Mammadov

This study deals with the issue of language choice from sociolinguistic perspectives. The problem of multilingualism and plurilingualism in sociolinguistics occupies a special field for the study and evokes the interest of most linguists. The goal of the research was to investigate language choice from sociolinguistic perspectives. This experimental work was carried out to verify the right choice of language (English, Russian, and Azerbaijani) and to identify its effectiveness, the data were processed and interpreted based on analysis. Special attention was paid to the multilingualism / plurilingualism issues and multilingualism in Azerbaijan separately. This paper presents the results of the quantitative method for sociolinguistic research in language. It was based on the interviews that were conducted among parents in order to learn their tendency to bring up their children in a multilingual society. Thus, parents were interviewed in different schools with Russian, Azerbaijani and English mediums of instruction; a school with Azerbaijani medium of instruction named as “Zangi” lyceum, a school with Russian medium named as “N_12”, a school with English medium called as “Baku-Oxford School”. This paper is an in-depth, multidimensional study of such choices in language. The results of the data analysis affirm a solid status of English as an international language in Azerbaijan and emphasize an undeniable position of the Azerbaijani language as well.


AERA Open ◽  
2018 ◽  
Vol 4 (3) ◽  
pp. 233285841879199 ◽  
Author(s):  
Joseph A. Taylor ◽  
Susan M. Kowalski ◽  
Joshua R. Polanin ◽  
Karen Askinas ◽  
Molly A. M. Stuhlsatz ◽  
...  

Author(s):  
Robert R. Richwine ◽  
G. Scott Stallard ◽  
G. Michael Curley

In recent years some power companies have instituted programs aimed at reducing or eliminating their power plants’ unreliability caused by abnormal events that occur infrequently but result in extended unplanned outages when they do occur, i.e. High Impact–Low Probability events (HILPs). HILPs include catastrophic events such as turbine water induction, boiler explosions, generator winding failures, etc. Many of these successful programs have relied on the detailed reliability data contained in the North American Electric Reliability Corporation’s (NERC) Generating Availability Data System (GADS) that contains data collected over the past 25 years from 5000+ generating units in North America. Using this data, these companies have been able to 1) benchmark their fleet’s unreliability due to HILPs against their North American peers, 2) prioritize their peer group’s susceptibility to various HILP modes and 3) use root cause data contained within the NERC-GADS data base to help identify and evaluate ways to proactively prevent, detect and/or mitigate the consequences of HILP events. This paper will describe the methods used in these successful programs in sufficient detail to enable others to adopt the techniques for application at their own generating plants.


2020 ◽  
Author(s):  
Nathan Honeycutt ◽  
Lee Jussim ◽  
Akeela Careem ◽  
Neil Anthony Lewis

In a seminal study investigating gender bias in academic science, Moss-Racusin et al. (2012) found bias against female lab manager applicants with respect to competence, hireability, mentoring, and salary conferral. This topic will be revisited through four studies--two direct replications, one extension, and a meta-analysis. The present set of studies, all using the same methods and materials as the original, will sample from a larger and broader pool of faculty, collectively representing the breadth of STEM disciplines at R1 universities across the United States. The proposed studies will have high power to detect smaller effect sizes than in the original. Furthermore, a priori criteria have been explicitly articulated for what will be accepted as hypothesis confirmation and replication, and for evidence of gender bias. The pre-registered data analysis plans will provide a strong test assessing the replicability of Moss-Racusin et al. (2012)’s finding that STEM faculty were biased against women who applied for a lab manager position.


2017 ◽  
Author(s):  
Vincent L. Cannataro ◽  
Stephen G. Gaffney ◽  
Jeffrey P. Townsend

ABSTRACTA major goal of cancer biology is determination of the relative importance of the genomic alterations that confer selective advantage to cancer cells. Tumor sequence surveys have frequently ranked the importance of substitutions to cancer growth by P value or a false-discovery conversion thereof. However, P values are thresholds for belief, not metrics of effect. Their frequent misuse as metrics of effect has often been vociferously decried. Here, we estimate the effect sizes of all recurrent single nucleotide variants in 23 cancer types, quantifying relative importance within and between driver genes. Some of the variants with the highest effect size, such as EGFR L858R in lung adenocarcinoma and BRAF V600E in primary skin cutaneous melanoma, have yielded remarkable therapeutic responses. Quantification of cancer effect sizes has immediate importance to the prioritization of clinical decision-making by tumor boards, selection and design of clinical trials, pharmacological targeting, and basic research prioritization.


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