Survival rate

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The survival rate is a term from epidemiology and indicates the probability of surviving a defined period of time from the diagnosis or therapeutic intervention (e.g. surgery). It is used to assess the prognosis of a disease. In the year survival rate, it does not have to the period until the death of the patient act (eg. As in cancer ), but it may also mechanically to the failure of systems (eg. As artificial heart valves , prostheses or dentures ) and organ replacement refer . When we speak of cancer in the following, however, all considerations can also be applied to the failure of mechanical systems. The annual survival rate is a statistical value and is given in percent . A distinction is made between absolute and relative survival rates. The complementary value to the survival rate is the mortality .

Absolute survival rate

Standardized incidence / 100,000, the five-year (5a) survival rates in% (as of 2016)
Art Incidence relative 5a survival rate [%]
♀ ♂ 2014 1980s
All in all 348 423 ♀: 65; ♂: 59 ♀: 50-53; ♂: 38-40
Childhood cancer 17th approx. 85 approx. 67
Oral and throat cancer 7th 18th ♀: 63; ♂: 47
Esophageal cancer 2 9 ♀: 22; ♂: 24 <10
Stomach cancer 7th 15th ♀: 34; ♂: 32
Colon cancer 32 51 ♀: 63; ♂: 62 approx. 50
Pancreatic cancer 11 14th ♀: 9; ♂: 9
Throat cancer 1 5 ♀: 64; ♂: 61
Lung cancer 31 58 ♀: 21; ♂: 15
Malignant melanoma 20th 21st ♀: 93; ♂: 91
Woman breast cancer 112 87
cervical cancer 9 67
Uterine body cancer 17th 78
Ovarian cancer 11 43
Prostate cancer 92 89
Testicular cancer 10 97
Kidney and urinary tract 8th 16 ♀: 77; ♂: 76 approx. 50
Bladder cancer 9 35 ♀: 45; ♂: 55
Cancer in the nervous system 6th 8th ♀: 24; ♂: 21
Thyroid cancer 11 5 ♀: 94; ♂: 88 ♀: approx. 77; ♂: approx. 67
Hodgkin's disease 2 3 ♀: 84; ♂: 86
Non-Hodgkin lymphoma 12 16 ♀: 70; ♂: 68
Leukemias 9 14th ♀: 57; ♂: 58

The absolute survival rate describes the proportion of patients who are still alive after a certain time. It results from the directly observed cases of patients who died within the period. The prevalence of a disease in a defined population can be inferred from the incidence and the absolute survival rate. The absolute survival rate can assume values ​​between 0 and 100%. Here, 0% means that no patient is alive within a certain period of time after the diagnosis. The absolute survival rate is the complementary value to lethality (Ü = 100% - L).

Five year survival rate

The five-year survival rate (also 5 a survival rate) denotes the proportion of patients with a particular disease who are still alive five years after the disease was recognized. For example, a five-year survival rate of 80% means that out of 100 patients, 80 patients are still alive after five years. The term is used particularly in oncology .

In oncology the five-year survival rate is highly dependent on the type of cancer. The relative five-year survival rate in the period 2013–2014 for pancreatic cancer was nine to ten percent, for lung cancer between 15% and 20%, while for malignant melanoma of the skin, testicular cancer and now also prostate cancer it was over 93 percent.

In contrast to this, the ten-year survival rate is also considered for some cancers, such as breast cancer , because these diseases can still recur even after several years of tumor-free disease.

Relative survival rate

The relative survival rate sets the survival of the sick in relation to the survival of the general population, which is estimated on the basis of life tables according to the age and gender structure. The absolute survival rate serves as the link between incidence and prevalence . A relative survival rate of 100% means that the mortality rate among the sick is as high as the mortality rate among the general population of the same age.

Based on the Saarland cancer registry, the relative five-year survival rate for all types of cancer was around 55% for the period from 1998 to 2002.

Medium survival

The term mean survival or mean survival time (MÜZ) is generally understood to mean the median value of the survival times. This means the time within which half of the patients are still alive after the diagnosis.

Special aspects

Correct interpretation of survival data from clinical cancer studies can be difficult, and pitfalls related to the nature of Kaplan-Meier analyzes can lead to incorrect conclusions. In evaluating a randomized controlled trial, the authors of a methodological study encountered some statistical problems that were obviously difficult to identify and possibly associated with a misinterpretation of survival functions. These topics included the assumed crossing of survival curves, the change in the statistical approach in the follow-up examination, the different pretreatment between the groups and event-free survival as the primary outcome.

See also

literature

Web links

Individual evidence

  1. ^ Elisa T. Lee, John Wenyu Wang: Statistical Methods for Survival Data Analysis. In: Wiley Series in Probability and Statistics. 4th edition. John Wiley & Sons, 2013. ISBN 978-1-118-59305-9 . Chapter 2: Functions of Survival Time .
  2. ↑ Cancer in Germany 2015/2016. (PDF) joint publication by the Robert Koch Institute and the Society of Epidemiological Cancer Registers in Germany V. , 2019, accessed October 10, 2018 .
  3. ↑ pancreatic cancer. Center for Cancer Registry Data
  4. ↑ lung cancer. Center for Cancer Registry Data
  5. ↑ Total cancer. Center for Cancer Registry Data
  6. ↑ Brenner et al .: Improved Long-Term Survival Rates of Cancer Patients: The Underestimated Advances in Oncology . In: Dtsch Arztebl 2005 , 102 (39), pp. A-2628 / B-2220 / C-2096
  7. ↑ Peinemann F: Issues possibly associated with misinterpreting survival data: a method study . In: Journal of Evidence-Based Medicine . 11, No. 3, June 2018, pp. 208–215. doi : 10.1111 / jebm.12301 . PMID 29877035 .