Some Issues of Clinical Epidemiology - Assignment Example

Clinical Epidemiology (Q 1 Consider the natural history of this disease, and how screening fits within  this process Women aged 20 years and above have the highest risk of having breast cancer and regular screening is encouraged from this age. At age 40, the risk is highest and the frequency of screening is consequently higher (Tabar, 2011). Additionally, counselling is included during the screening to raise awareness among at-risk population on the importance of early diagnosis of breast cancer. Cancer is a malignant disease and spreads from tissue to tissue until it reaches the lymph nodes. If not detected and treated early, it can kill within a period of three years although this can extend to over thirty years. Breast cancer cells may be hormone-dependent while some can lie dormant in tissues for a very long time, as long as thirty years, after removal of the primary tumor (Lipkus et al, 2001). Some illnesses may act as catalysts in the progression of the disease in the body (Gail & Rimer, 1998). Consequently, this implies that even with earlier detection and treatment, there can be a risk of recurrence during the entire life of the patient. However, with early screening, it is possible to detect these cells before they start causing symptoms (Schonberg  et al, 2014; Siegel et al, 2012). Once the disease symptoms start showing, the tumors are mostly larger and will have likely spread to other parts beyond the breast. In contrast, breast cancer cells found earlier through screening are likely smaller and their presence is still limited to the breasts thus their spread is much easier to curtail, for example, through prophylactic surgery (Freedman, 2010; Nelson, 2012). At the point of detection, it is easier to estimate the prognosis of breast cancer. The size of the tumor and how far it has spread are vital indicators of predicting prognosis and are almost entirely dependent on the time of detection of the cancer (Siegel et al, 2012). Screening enables detection of the disease in early stages and hence it is possible to reverse the spread of the disease. Consequently, screening improves survival rates among breast cancer patients. Q 1.2 On what other bases is there evidence that screening is worthwhile?  The proportion of the population affected by breast cancer is a pointer to the importance of screening the at-risk population. According to studies, breast cancer is the most common form of cancer and causes the second highest number of deaths in the US (Smith et al, 2013). Health statistics indicate that out of every 8 women, one will develop a severe form of breast cancer over the course of her lifetime. In 2014 alone, close to quarter million cases of new breast cancer cases were expected to be reported among women, along with 62,000 new cases of passive cancer. The disease burden on the population is equally huge. Breast cancer was expected to result to 40,000 deaths. There has been a steady decrease in the number of breast cancer related deaths since the early 1990s and this is thought to be a result of increased screening efforts. Breast cancer screening is worthwhile based on the characteristics of the screening methods used. This is both in terms of frequency and the cost of the screenings. While clinical breast examinations are encouraged, women can still opt to do self-examination. BSEs may costs a few dollars are still way compared to the cost of treating a detected case of breast cancer. Self-examinations cost absolutely nothing. Considering the frequency of screenings, which occur at most once a year, screenings are a cheap alternative relative to treating a full-blown cancer, or the disease burden. Consequently, the benefits of screening outweigh the costs by a large margin and hence encouraged. Breast cancer screenings are also supported by the efficacy of the methods used. Although there are risks of false positives and overdiagnosis, the rates are generally low. Women can be informed about the possibility of false positives to reduce anxiety in case the cases observed cannot be confirmed through additional tests. This can reduce tension in case a suspected case of breast cancer cannot be confirmed. Q 1.3 What are the potential risks and benefits of using this screening test for this condition?   Benefits of cancer screening outweighs the risks by far. The benefits include a reduction in the risk of dying from the disease, and if the disease is detected, surgeries required to remove the tumor may not be as aggressive as it would be for a late-stage cancer. Besides, alternative treatment options are always available when the cancer is detected earlier. Risks of breast cancer screening include the possibility of false positive results. This occurs when a suspected case of cancer are found to be false when detailed medical tests, such as imaging or biopsy, are conducted. False positives may also result to more mammograms being conducted. They may also results into anxiety or depression. However, most cases of depression are mild and have not been found to increase clinically diagnosed anxiety and depression (Pace & Keating, 2014), Research is inadequate into whether women are more or less likely to return for future screenings after a false positive result (Pace & Keating, 2014). A second risk associated with breast cancer screening is overdiagnosis. This occurs when a non-progressive (dormant) tumor is detected through mammography (Smith et al, 2013). This kind of tumor will not cause any problems if undetected. This can occur due to a number of factors including indolent pathological features of due to competing mortality factors related to old age or interaction of various risk factors. There have been increasing cases of overdiagnosis and this is now thought to be one of the most serious effects of screening (Independent UK Panel on Breast Cancer Screening, 2012). Who should be the target population for screening? And what are the epidemiological arguments for choosing this target group? Generally, women aged 20 years and above are encouraged to go for screening once every three years. On clocking 40, the frequency of screening increases to once every year. There are also various at-risk groups that are encouraged to undergo regular screening. These include women who have had a history of breast cancer, women who have a family member that has suffered from breast cancer. Other vulnerable groups include women with no history of breastfeeding, women who use certain medical procedures (such as hormone replacement therapy), and women who have had no children at late ages (particularly after 30). PART 2 QUESTION 2.1 The information can be summarized in a table as shown below: PHQ-9 Score Major depressive Disorder (N=19) No depressive Disorder (N=373) 0-4 0 (0%) 183 (49.06%) 5-10 2 (10.53%) 122 (32.71%) 11-14 7 (36.84%) 39 (10.46%) 15-19 6 (31.58%) 20 (5.36) 20-27 4 (21.05%) 9 (2.41%) a) Sensitivity when cut-off is less than 14 Disease Present Disease Absent Test Positive 9 29 38 Negative 10 344 354 19 373 Sensitivity = 9/19 = 47% Specificity = 344/373 = 92% b) Sensitivity when cut-off is less than 19 Disease Present Disease Absent Positive 15 9 24 Negative 4 364 368 19 373 Sensitivity = 15/(19) = 79% Specificity = 364/(373) = 98% Q 2.2 The most optimal cut-off point is a PHQ greater than 8. There is minimal reduction in sensitivity. Q 3.1 Disease Present Disease Absent Positive 23 28 51 Negative 16 395 39 423 Sensitivity = 23/39 = 59% Specificity = 395/423 = 93% PPV = 23/51 = 45% Q 3.2 Disease Present Disease Absent Positive 55 91 146 Negative 14 432 69 523 Sensitivity = 55/69 = 78% Specificity = 432/523 = 83% PPV = 55/146 = 38% Q 3.3 Sensitivity Specificity Test 1 0.59 0.93 Test 2 0.78 0.83 Test 1 & Test 2 (series) Test 1 & Test 2 (parallel) Parallel Sensitivity = 1 – (1-0.59) * (1-0.78) = 1 – (0.41*0.22) = 0.91 = 91% Specificity = 0.93*0.83 = 0.77 = 77% Series Sensitivity = 0.59*0.78 = 47% Specificity = 1 – (1-0.93) * (1-0.83) = 99% Q 3.4 Group 1 Sensitivity = 31/411 = 8% Group 2 Sensitivity = 51/452 = 11% It performed better in Group 2 Q 3.5 Using ROC curves, the optimal cut-off for HbA1c for diabetes as diagnosed according to either fasting blood glucose or OGTT can be effective in determine cu-off point. PART 4 Q 4.1 & 4.2 Risk in reduction of pain of less than 50% Pain reduction No pain reduction 2.0 mW/day 36 80 116 Placebo 43 69 112 79 149 Absolute risk (It) = 80/116 = 0.6897 Incidence of risk in control (Io) = 69/112 = 0.616 Absolute risk reduction (ARR) = It - Io = 0.6897 – 0.616 = -0.0737 Relative Risk (RR) = It / Io = 1.12 Relative Risk Reduction (RRR) = 1 – RR = -0.12 Number needed to treat = 1/ ARR = 8 Pain reduction No pain reduction 6.0 mW/day 53 57 110 Placebo 43 69 112 96 126 Absolute risk (It) = 57/110=0.5182 Incidence of risk in control (Io) = 69/112 = 0.616 Absolute risk reduction = It - Io = -0.0978 Relative Risk (RR) = It / Io = 0.84 Relative Risk Reduction (RRR) = 1 – RR= 0.16 Number needed to treat = 10 Pain reduction No pain reduction 8.0 mW/day 80 25 105 Placebo 43 69 112 123 94 Absolute risk (It) = 25/105 = 0.238 Incidence of risk in control (Io) = 69/112 = 0.616 Absolute risk reduction = It - Io = -0.3780 Relative Risk (RR) = It / Io = 0.386 Relative Risk Reduction (RRR) = 1 – RR= 0.614 Number needed to treat = 3 Pain reduction No pain reduction 10.0 mW/day 104 5 109 Placebo 43 69 112 147 74 Absolute risk (It) = 5/109 = 0.0459 Incidence of risk in control (Io) = 69/112 = 0.616 Absolute risk reduction = It - Io = -0.57 Relative Risk (RR) = It / Io = 0.0745 Relative Risk Reduction (RRR) = 1 – RR= 0.925 Number needed to treat = 2 Q 4.3 Laser acupuncture is effective in reducing pain in chronic knee pain. The most optimal dosage is 8.0 mW/day with a 61% reduction in pain. A higher dosage may be harmful while a low dosage is ineffective. Q 4.4 Calculate the disease impact number. DIN = NNT * (1/Pe) To obtain at least 50% reduction in pain using 8.0mW/day dosage, we need to treat 3 * (1/0.4) = 8 We need to treat 5 more people to have the same effect if only 40 % of population can tolerate laser acupuncture Q 4.4 Calculate the population impact number PIN = DIN * (1/P∆) Assuming prevalence of 30%, then, PIN = 3 * (1/0.003) = 1000 Implies that in a population of 1000, the treatment would prevent 1 (one) outcome within 6 weeks Q 4.5 Other outcomes that would need to be considered include the side effects on the users (long-term and short-term effects), and comparison with other pain relief methods (cost and efficacy). Reference List Freedman, A  E., Seruga , OC., Evans, D. (2010). Assessing women at high risk of breast cancer: a review of risk assessment models. J Natl Cancer Inst. 102(10):680-691. Gail, M, Rimer  B. (1998).  Risk-based recommendations for mammographic screening for women in their forties. J Clin Oncol. 16(9):3105-3114. Independent UK Panel on Breast Cancer Screening. (2012). The benefits and harms of breast cancer screening: an independent review. Lancet. 380(9855):1778-1786. Keating, N L., and Pace, L E. (2014). A Systematic Assessment of Benefits and Risks to Guide Breast Cancer Screening Decisions; JAMA, 311(13):1327-1335. Lipkus, IM, Biradavolu  M, Fenn  K, Keller  P, Rimer  BK. (2001).  Informing women about their breast cancer risks: truth and consequences. Health Commun. 13(2):205-226. Nelson, HD, Zakher  B, Cantor  A,  et al. (2012).  Risk factors for breast cancer for women aged 40 to 49 years: a systematic review and meta-analysis. Ann Intern Med. 156(9):635-648. Schonberg, MA, Hamel  MB, Davis  RB,  et al. (2014).  Development and evaluation of a decision aid on mammography screening for women 75 years and older. JAMA Intern Med. 174(3):417-424. Siegel, R, Naishadham D, Jemal A. Cancer statistics, 2012. CA Cancer J Clin. 2012;62: 10-29. Smith, RA.et al (2013). A Review of Current American Cancer Society Guidelines, Current Issues in Cancer Screening, and New Guidance on Cervical Cancer Screening and Lung Cancer Screening. Cancer J Clin 2013;63:87–105 Tabar, L, Vitak B, Chen TH, et al. (2011). Swedish two-county trial: impact of mammographic screening on breast cancer mortality during 3 decades. Radiology. 260:658-663. Read More