DNP 820 TOPIC 5 DQ 1

DNP 820 TOPIC 5 DQ 1

DNP 820 TOPIC 5 DQ 1

Compare statistical and clinical significance. Explain why a project or practice outcome may not yield statistical significance but can still have clinical significance. When can a project’s outcomes be deemed “successful” by only using clinical significance as a measure? Provided examples from current research.

Measures of statistical significance quantify the probability of a study’s results being due to chance. Clinical significance, on the other hand, refers to the magnitude of the actual treatment effect (i.e., the difference between the intervention and control groups, also known as the “treatment effect size”), which will determine whether the results of the trial are likely to impact current medical practice (Ranganathan, P. et al., 2015). The “P” value, frequently used to measure statistical significance, is the probability that the study results are due to chance rather than an actual treatment effect. The conventional cut-off for the “P” value to be considered statistically significant is 0.05 (or 5%). A P < 0.05 implies that the possibility of the results in a study being due to chance is <5% (Ranganathan, P. et al., 2015).  In clinical practice, an impact’s “clinical significance” depends on its implications on existing practice-treatment effect size, which is one of the most critical factors driving treatment decisions. Sharma (2021) suggests that the clinical significance should reflect “the extent of change, whether the change makes a real difference to subject lives, how long the effects last, consumer acceptability, cost-effectiveness, and ease of implementation.” While there are established, traditionally accepted values for statistical significance testing, this is lacking for evaluating clinical significance (Sharma H., 2021). Often, it is the judgment of the clinician (and the patient) that decides whether a result is clinically significant or not.

According to Van Cutsem, E. et al. (2018), statistical significance heavily depends on the study’s sample size; with large sample sizes, even minor treatment effects (clinically inconsequential) can appear statistically significant; therefore, the reader must carefully interpret this “significance.” A study published in the Journal of Clinical Oncology compared overall survival in 569 patients with advanced pancreatic cancer who were randomized to receive erlotinib plus gemcitabine versus gemcitabine alone. Median survival was “significantly” prolonged in the erlotinib/gemcitabine arm (6.24 months vs. 5.91 months, P = 0.038). The P = 0.038 means that there is only a 3.8% chance that this observed difference between the groups occurred by chance (which is less than the traditional cut-off of 5%) and, therefore, statistically significant. In this example, the clinical relevance of this “positive” study is the “treatment effect” or difference in median survival between 6.24 and 5.91 months – a mere ten days, which most oncologists would agree is a clinically irrelevant “improvement” in outcomes, especially when considering the added toxicity and costs involved with the combination. In clinical research, statistically significant study results are often clinically meaningful. While statistical significance indicates the reliability of the study results, clinical significance reflects its impact on clinical practice.

Ranganathan, P., Pramesh, C. S., & Buyse, M. (2015). Common pitfalls in statistical analysis: Clinical versus statistical significance. Perspectives in clinical research6(3), 169–170. https://doi.org/10.4103/2229-3485.159943

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Sharma H. (2021). Statistical significance or clinical significance? A researcher’s dilemma for appropriate interpretation of research results. Saudi journal of anesthesia15(4), 431–434. https://doi.org/10.4103/sja.sja_158_21

Van Cutsem, E., Hidalgo, M., Canon, J. L., Macarulla, T., Bazin, I., Poddubskaya, E., … & Hammel, P. (2018). Phase I/II trial of pimasertib plus gemcitabine in patients with metastatic pancreatic cancer. International Journal of Cancer143(8), 2053-2064.

I agree with you that clinical significance and measures of statistical significance are different concept of healthcare statistics. However, both clinical significance and measure of statistical significance are important when handing statistical information in healthcare settings. Measures of statistical significance quantify the probability of a study’s outcomes because of chance (Griffiths & Needleman, 2019). Clinic significance is the magnitude of the actual treatment effect. The magnitude can be examined by identifying the difference between the intervention and control groups. Measures of statistical significance are general when addressing healthcare issue. The generalization may make measures of statistical significance unfit to handle clinical issues that requires specialty (Frank et al., 2021). Therefore, clinical significance becomes a right replacement for measures of statistical significance.  At the same time, the measures of statistical significance can replace clinical significance. The uniqueness of these two terms allow measures of statistical significant and clinical significance to complement one another in healthcare settings. Statistical significance illustrates the reliability of the study results, clinical significance reflects its impact on clinical practice.

References

Frank, O., Tam, C. M., & Rhee, J. (2021). Is it time to stop using statistical significance?. Australian Prescriber44(1), 16. doi: 10.18773/austprescr.2020.074

Griffiths, P., & Needleman, J. (2019). Statistical significance testing and p-values: Defending the indefensible? A discussion paper and position statement. International journal of nursing studies99, 103384. https://doi.org/10.1016/j.ijnurstu.2019.07.001

As we search for supportive literature that supports the DPI project it is important to understand statistical and clinical significance. Statistical significance quantifies the probability of a study’s results being due to chance (Sharm, 2021). In other words, statistical significance indicated reliability and describes the differences or relationship between two variables. This is measured with the p value and the p value can help the researcher know how credible the source is. On the other hand, clinical significance determines if the results of a study are meaningful and can be used to assess the effectiveness of a treatment modality (Armijo-Olivo, 2018). Clinical significance can be assessed on if the change makes a difference in patients’ everyday life.

A patient care outcome may not yield statistical significance but can still have clinical significance. For instance, clinical significance is often shown in pharmaceutical management. A provider may order a new medication that is shown to decrease the heart rate. The medication is new and has not been tested on a large population sample. However, the patients that are prescribed the medication have a decrease in heart rate and better patient outcome. This drug holds clinical significance as it positively impacted the patient but does not hold statistical significance because it is new.

References

Armijo-Olivo, S. (2018). The importance of determining the clinical significance of research results in physical therapy clinical research. Brazilian Journal of Physical Therapy22(3), 175-176. https://doi.org/10.1016/j.bjpt.2018.02.001

Sharma, H. (2021). Statistical significance or clinical significance? A researcher’s dilemma for appropriate interpretation of research results. Saudi Journal of Anaesthesia15(4), 431. https://doi.org/10.4103/sja.sja_158_21

RESPOND HERE

CHANDRA it is true that handling DPI projects requires adequate understanding of statistical and clinical significances. These two significances are applied in different stages of DPI project. Therefore, inadequate understanding may compromise the entire project. Statistical significance indicated reliability and describes the differences or relationship between two variables. On the other hand, clinical significance determines if the results of a study are meaningful and can be used to assess the effectiveness of a treatment modality (Panteghini et al., 2022). In the DPI projects, stakeholders interact with healthcare circumstances that either require them to use one of the significances or both depending with the healthcare issue.  P-value measures statistical significance. The researcher can ascertain the credibility of the source of information using P-value measurement (Rose-Nussbaumer, 2021). Clinical significance can be assessed on if the change makes a difference in patients’ everyday life. Clinical significance is tied to clinical decision-making process whereas statistical significance can be used beyond healthcare settings.

References

Panteghini, M., Tonni, G., & Mansournia, M. A. (2022). To move beyond statistical significance and consider clinical relevance. Clinical Oncology. DOI:https://doi.org/10.1016/j.clon.2022.02.003

Rose-Nussbaumer, J. (2021). Statistical Significance vs Clinical Significance—That Is the Question. JAMA ophthalmology139(11), 1235-1235. doi:10.1001/jamaophthalmol.2021.4139

Evidence of how things really are and how to improve the safety and quality of care provided to patients comes from relevant research. Reality to a researcher can either be objective or subjective (Smith, 2021); however, evidence to support a DPI project is quantitative with randomized controlled trial design. For this reason, searching the literature for evidence to support PICOT questions in a quality improvement project is very important in clinical practice. It is important to stress that statistical significance is not the same as clinical significance; however, the two can find usefulness in a DPI project. Following that the evidence required to support DPI project falls into quantitative methodology, with randomized control design, statistical and clinical significance become inevitable.

Clinical significance is the relevance of a particular treatment that does not necessarily take into consideration statistical significance. The relevance of statistical significance in nursing practice takes into consideration confidence intervals (Ranganathan, Pramesh, & Buyse, 2015). For this reason, the importance and relevance of a calculation and measure of statistical significance to mark out threat to validity of a quantitative study, such as the randomized controlled trial, cannot be overemphasized. Statistical significance allows researchers to rule out the fact that results are due to chance rather than differences in the population sampled. Testing a hypothesis using P-values is an example of where statistical significance found usefulness in research, while clinical significance could be used in a DPI quality improvement project. Clinical significance reinvigorates the results and findings of an existing practice-treatment effect. 

References

Ranganathan, P., Pramesh, C. S., & Buyse, M. (2015). Common pitfalls in statistical analysis: Clinical versus statistical significance. Perspectives in clinical research6(3), 169–170. https://doi.org/10.4103/2229-3485.159943

Smith, T. (2021). Qualitative and quantitative research. Salem Press Encyclopedia.

RESPOND HERE

JENEVIEVE I concur with you that relevant research is important in improving the safety and quality of services provided to patients. Research limit chances of using wrong information to make critical decisions. Inaccurate information paves way for poor decisions and choices (Fleischmann & Vaughan, 2019). Therefore, patients may be at risk of becoming victims of wrong decisions created from inaccurate information. Reality to a researcher can either be objective or subjective.  However, these researchers have the responsibility of finding the truth. Assumptions and predictions may not be right all the time. As a result, healthcare professionals are expected to use relevant studies to handle different healthcare issues. DPI projects rely on factual information (Walter et al., 2020). Thus, research is an important engagement in completing DPI projects. PICOT question directs researchers in their fact-finding procedures. Clinical and statistical significances are useful in handling healthcare concerns. Clinical significance is the relevance of a particular treatment that does not necessarily take into consideration statistical significance.

References

Fleischmann, M., & Vaughan, B. (2019). Commentary: Statistical significance and clinical significance-A call to consider patient reported outcome measures, effect size, confidence interval and minimal clinically important difference (MCID). Journal of Bodywork and Movement Therapies23(4), 690-694. https://doi.org/10.1016/j.jbmt.2019.02.009

Walter, S. D., Thabane, L., & Briel, M. (2020). The fragility of trial results involves more than statistical significance alone. Journal of clinical epidemiology124, 34-41. https://doi.org/10.1016/j.jclinepi.2020.02.011

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