Quantitative basis for planning the costs of medical care in oncology: analyses and predictions for 2017 – SW Moravia

Prepared by a team of authors led by:
doc. RNDr. L. Dušek, Ph.D.; prof. MUDr. R. Vyzula, CSc.; prof. MUDr. B. Melichar, Ph.D.; prof. MUDr. J. Abrahámová, DrSc.; prof. MUDr. J. Fínek, CSc.; prof. MUDr. L. Petruželka, CSc.; prim. MUDr. K. Petráková, CSc.

Data analysis and information technology:
RNDr. O. Májek, Ph.D.; RNDr. T. Pavlík, Ph.D.; RNDr. J. Mužík, Ph.D.; Mgr. J. Koptíková, Ph.D.; RNDr. D. Malúšková; RNDr. D. Klimeš, Ph.D.; Ing. Petr Brabec, Ph.D.; RNDr. Jakub Gregor, Ph.D.; PhDr. Karel Hejduk; doc. RNDr. L. Dušek, Ph.D.

Expert panel (in alphabetical order):
prof. MUDr. J. Abrahámová, DrSc.; prof. MUDr. M. Babjuk, CSc.; doc. MUDr. Tomáš Büchler, Ph.D.; prof. MUDr. David Cibula, Ph.D.; doc. RNDr. L. Dušek, Ph.D.; doc. MUDr. D. Feltl, Ph.D.; prof. MUDr. J. Fínek, CSc.; prof. MUDr. V. Kolek, DrSc.; prof. MUDr. M. Marel, CSc.; prof. MUDr. B. Melichar, Ph.D.; prof. MUDr. J. Petera, CSc.; prim. MUDr. K. Petráková, CSc.; prof. MUDr. M. Pešek, CSc.; prof. MUDr. L. Petruželka, CSc.; prof. MUDr. M. Ryska, CSc.; prof. MUDr. A. Ryška, Ph.D.; doc. MUDr. Jana Prausová, Ph.D.; prof. MUDr. J. Skřičková, CSc.; MUDr. M. Šafanda; doc. MUDr. V. Študent, CSc.; prof. MUDr. J. Vorlíček, CSc.; prof. MUDr. R. Vyzula, CSc.; prof. MUDr. J. Žaloudík, CSc.

Summary

This report summarises analyses of available population-based data on the Czech Republic, aiming to predict incidence and prevalence rates of patients with selected cancer types for the year 2017. These predictions are based on population-based epidemiological data (Czech National Cancer Registry, see also www.svod.cz), demographic data on the Czech Republic including demographic projections, and data on causes of death. Population-based predictions of incidence and prevalence rates have been adjusted by survival probability models and by an expert panel of the Czech Society for Oncology (CSO), making it possible to predict quite reliably the number of patients likely to undergo a certain stage of cancer treatment in 2017. The predictions are available for the entire population of the Czech Republic, for individual regions of the country, as well as for catchment areas of comprehensive cancer centres.

The results of the below-described information system, which is used by the CSO to predict the numbers of cancer patients to be treated in the years to come, provide the following strategic outputs:

  1. The estimate of the number of cancer patients likely to be treated in the future, which is based on the epidemiological situation, provides a valuable population benchmark for subsequent monitoring of clinical practice.
  2. The number of cancer patients likely to be treated can be estimated for individual diagnoses and disease stages, as well as for individual regions of the Czech Republic. These predictions make monitoring and controlling significance of these calculations even stronger.
  3. The analysis of population-based data works with data on incidence and mortality of a certain disease, thus allowing a plausible estimate of patients who could actually benefit from a specific treatment (correctly diagnosed patients in adequate health condition and age, etc.). The calculations involve an important clinical adjustment and guarantee that costly treatment will be correctly indicated, and that spent resources will be used adequately.
  4. Each year, the predicted number of cancer patients likely to be treated can be compared with the actual number of treated patients, as well as with treatment results. The CSO and health care payers thus obtain valuable information on the availability of a specific therapy in the individual regions of the Czech Republic.

The predictions take into account the clinical stage of disease, and possibly also detailed components of TNM classifications, or morphology according to MKN-O classification. These data are not available in the databases of health care payers. By presenting the data, the Czech Society for Oncology makes it possible for health care payers to monitor the market with targeted therapies in the Czech Republic actively.


A. OVERVIEW OF DATA SOURCES AND THE METHODOLOGY OF ASSESSMENT

Methodology and definition of data sources are described in a separate article.


B. PREDICTED CANCER RATES FOR THE YEAR 2017

The concept of this report, the methodology of calculations as well as overall population-based estimates are provided in the main part of the report, which was compiled for the entire Czech Republic. This supplement only contains estimates derived by the same procedure for a given region. The estimates are focused on the most common diagnoses (C50; C18–C20; C34-NSCLC; C64 – renal cell carcinoma; C61; C67; C16; C25; C43; C53; C54; C56).

I. Predicted overall incidence rates for the year 2017

90% confidence intervals (in brackets) are provided for all estimates.

Predicted incidence rate1
(90% confidence interval)

Stage
I

Stage
II

Stage
III

Stage
IV

Stage
unknown2

Total

Breast cancer (C50)

516
(464; 568)

377
(333; 421)

150
(122; 178)

84
(63; 105)

35
(17; 53)

1,162
(1,085; 1,239)

Colorectal cancer (C18–C20)

326
(285; 367)

272
(234; 310)

327
(286; 368)

235
(200; 270)

95
(66; 124)

1,255
(1,174; 1,336)

Non-small-cell lung cancer (C34)

62
(44; 80)

54
(37; 71)

124
(99; 149)

271
(233; 309)

44
(22; 66)

555
(501; 609)

Renal cell carcinoma (C64)

332
(290; 374)

66
(48; 84)

68
(49; 87)

17
(6; 28)

483
(432; 534)

Prostate cancer (C61)

776
(713; 839)

98
(75; 121)

135
(108; 162)

110
(78; 142)

1,119
(1,043; 1,195)

Bladder cancer (C67)

150
(121; 179)

57
(40; 74)

21
(11; 31)

46
(30; 62)

21
(9; 35)

295
(255; 335)

Stomach cancer (C16)

23
(12; 34)

44
(28; 60)

36
(22; 50)

67
(48; 86)

35
(18; 52)

205
(172; 238)

Pancreatic cancer (C25)

68
(49; 87)

28
(16; 40)

170
(141; 199)

73
(46; 100)

339
(297; 381)

Malignant melanoma of skin (C43)

192
(161; 223)

76
(56; 96)

36
(22; 50)

14
(6; 22)

22
(9; 36)

340
(298; 382)

Cervical cancer (C53)

56
(40; 72)

11
(3; 19)

22
(12; 32)

21
(11; 31)

10
(3; 17)

120
(95; 145)

Uterine cancer (C54)

233
(198; 268)

26
(14; 38)

29
(17; 41)

22
(11; 33)

30
(15; 46)

340
(298; 382)

Ovarian cancer (C56)

22
(11; 33)

11
(4; 18)

53
(36; 70)

47
(32; 62)

21
(7; 35)

154
(126; 182)

1 The values in the table are predictions of the overall incidence including other primary tumours diagnosed in previously treated cancer patients (duplicities, triplicities, etc.).

2 Objective reasons for not reporting the disease stage involve diagnosis based on autopsy/DCO, early deaths, treatment not started for contraindications, patient’s refusal to treatment. If reason for not reporting the stage is not provided, the record is considered as incomplete. Records missing the information on clinical stage are not involved in the expected number of patients who might need cancer treatment.

II. Predicted overall prevalence rates for the year 2017

Estimates of the overall prevalence include the estimated numbers of newly diagnosed cancers in 2017, and the estimated numbers of living cancer patients who were diagnosed and treated in previous years (calculated according to survival probability models). The resulting estimates were adjusted in a way which reflects cancer progression to disseminated stages. Patients who were previously diagnosed in stages I, II or III, and whose cancers would probably relapse or progress to a disseminated stage, have been included in the predicted prevalence of the clinical stage IV. This model calculates the probability of relapses to stage IV only, because plausible population-based data is not available for a detailed monitoring of relapses to other stages. However, this limitation does not have a significant influence on population-based pharmacoeconomic indicators, because this particular model is focused on the monitoring of drugs indicated for disseminated conditions. 90% confidence intervals (in brackets) are provided for all estimates.

The estimates involve all malignant tumours, including other primary tumours diagnosed in previously treated cancer patients (duplicities, triplicities, etc.).

Predicted prevalence rate
(90% confidence interval)

Stage
I

Stage
II

Stage
III

Stage
IV

Stage
unknown1

Total

Breast cancer (C50)

6,658
(6,474; 6,842)

5,809
(5,636; 5,982)

1,589
(1,499; 1,679)

645
(587; 703)

285
(247; 323)

14,986
(14,709; 15,263)

Colorectal cancer (C18–C20)

3,770
(3,630; 3,910)

2,883
(2,760; 3,006)

2,639
(2,521; 2,757)

1,229
(1,149; 1,309)

667
(609; 725)

11,188
(10,946; 11,430)

Non-small-cell lung cancer (C34)

473
(424; 522)

226
(192; 260)

376
(333; 419)

723
(662; 784)

184
(153; 215)

1,982
(1,880; 2,084)

Renal cell carcinoma (C64)

3,507
(3,370; 3,644)

523
(470; 576)

360
(316; 404)

180
(150; 210)

4,570
(4,415; 4,725)

Prostate cancer (C61)

8,549
(8,338; 8,760)

1,263
(1,182; 1,344)

999
(926; 1072)

704
(645; 763)

11,515
(11,271; 11,759)

Bladder cancer (C67)

1,782
(1,686; 1,878)

482
(431; 533)

102
(78; 126)

221
(186; 256)

359
(317; 401)

2,946
(2,822; 3,070)

Stomach cancer (C16)

280
(242; 318)

226
(191; 261)

138
(111; 165)

205
(172; 238)

154
(127; 181)

1,003
(932; 1,074)

Pancreatic cancer (C25)

202
(169; 235)

43
(28; 58)

356
(313; 399)

178
(148; 208)

779
(715; 843)

Malignant melanoma of skin (C43)

3,003
(2,878; 3,128)

670
(611; 729)

306
(266; 346)

110
(86; 134)

195
(165; 225)

4,284
(4,135; 4,433)

Cervical cancer (C53)

1,654
(1,564; 1,744)

331
(290; 372)

417
(371; 463)

109
(85; 133)

203
(173; 233)

2,714
(2,598; 2,830)

Uterine cancer (C54)

3,716
(3,576; 3,856)

391
(346; 436)

272
(235; 309)

114
(89; 139)

456
(409; 503)

4,949
(4,788; 5,110)

Ovarian cancer (C56)

714
(654; 774)

181
(151; 211)

429
(382; 476)

287
(248; 326)

167
(138; 196)

1,778
(1,682; 1,874)

1 Objective reasons for not reporting the disease stage involve diagnosis based on autopsy/DCO, early deaths, treatment not started for contraindications, patient’s refusal to treatment. If reason for not reporting the stage is not provided, the record is considered as incomplete. Records missing the information on clinical stage are not involved in the expected number of patients who might need anticancer treatment.

III. Estimated total number of potentially treated cancer patients in 2017

The table below provides a summary of predicted numbers of potentially treated patients, which are derived from incidence trends, prevalence trends, and survival probability models for the year 2017. The estimates are based solely on valid population-based data, which involve a histological verification of the tumour, and which had the clinical stage established at the time of primary diagnosis. The table involves numbers of all persons potentially treated with anticancer therapy (based on information on treatment according to CNCR data from the period 2010–2014, according to clinical stage. 90% confidence intervals (in brackets) are provided for all estimates.

The estimates involve all malignant tumours, including other primary tumours diagnosed in previously treated cancer patients (duplicities, triplicities, etc.).

Diagnosis

Newly diagnosed and treated patients in the year 2017

Stage
I

Stage
II

Stage
III

Stage IV

Total

Newly diagnosed
and treated patients
in stage IV

Treated relapses and
progressions in patients
diagnosed in previous years

Breast cancer (C50)

508
(457; 559)

367
(323; 411)

142
(114; 170)

64
(45; 83)

177
(147; 207)

1,258
(1,178; 1,338)

Colorectal cancer (C18–C20)

287
(249; 325)

253
(217; 289)

304
(264; 344)

158
(130; 186)

224
(190; 258)

1,226
(1,146; 1,306)

Non-small-cell lung cancer (C34)

52
(36; 68)

45
(29; 61)

98
(75; 121)

177
(146; 208)

152
(123; 181)

524
(471; 577)

Renal cell carcinoma (C64)

312
(272; 352)

64
(46; 82)

54
(37; 71)

66
(47; 85)

496
(445; 547)

Prostate cancer (C61)

642
(584; 700)

93
(72; 114)

109
(85; 133)

155
(127; 183)

999
(927; 1,071)

Bladder cancer (C67)

145
(118; 172)

52
(35; 69)

17
(8; 26)

32
(19; 45)

51
(35; 67)

297
(257; 337)

Stomach cancer (C16)

16
(7; 25)

33
(19; 47)

27
(15; 39)

33
(20; 46)

32
(19; 45)

141
(114; 168)

Pancreatic cancer (C25)

46 (30; 62)

15
(6; 24)

67
(48; 86)

38
(24; 52)

166
(137; 195)

Malignant melanoma of skin (C43)

192
(161; 223)

76
(56; 96)

35
(21; 49)

11
(3; 19)

43
(28; 58)

357
(313; 401)

Cervical cancer (C53)

54
(38; 70)

10
(3; 17)

19
(9; 29)

15
(7; 23)

21
(11; 31)

119
(95; 143)

Uterine cancer (C54)

227
(192; 262)

25
(14; 36)

26
(14; 38)

14
(5; 23)

31
(19; 43)

323
(281; 365)

Ovarian cancer (C56)

22
(11; 33)

10
(3; 17)

49
(33; 65)

31
(18; 44)

50
(34; 66)

162
(133; 191)

IV. Highly specialised care – predicted numbers of patients indicated for treatment with individual drugs

Prediction of numbers of patients newly indicated for targeted therapies of cancer in 2017 in regions of the Czech Republic – drugs with valid categorisation. Drugs marked with an asterisk (*) have a valid registration, their reimbursement is being negotiated.

Drug – diagnosis

SW Moravia

Czech Republic

 

Drug – diagnosis

SW Moravia

Czech Republic

HERCEPTIN (Trastuzumab)
-
(neo)adjuvant therapy
- breast cancer

103
(85; 123)

653
(612; 697)

 

ERBITUX (Cetuximab)
- head and neck cancers

48
(37; 63)

322
(271; 382)

HERCEPTIN (Trastuzumab)
- metastatic breast cancer

30
(21; 42)

198
(170; 230)

 

GLIVEC (Imatinib)
- first line of treatment
- GIST

61
(48; 77)

322
(289; 360)

TYVERB (Lapatinib)
- metastatic breast cancer

7
(3; 14)

46
(35; 59)

 

SUTENT (Sunitinib)
- second line of treatment
- GIST

7
(3; 14)

35
(25; 48)

AVASTIN (Bevacizumab)
- first line of treatment
- metastatic breast cancer

18
(11; 28)

115
(98; 134)

 

NEXAVAR (Sorafenib)
- hepatocellular carcinoma

23
(15; 34)

140
(120; 164)

PERJETA (Pertuzumab)
- first line of treatment
- metastatic breast cancer

22
(14; 33)

148
(129; 170)

 

JAVLOR (Vinflunine)
- second line of treatment
- bladder cancer

35
(25; 48)

272
(245; 301)

KADCYLA (trastuzumab emtansin)
- metastatic breast cancer

19
(11; 29)

128
(105; 155)

 

ZELBORAF (Vemurafenib)
- first line of treatment
- malignant melanoma of skin

7
(3; 14)

53
(42; 67)

HALAVEN (eribulin mesilat)
- second and higher line of treatment
- metastatic breast cancer

18
(11; 28)

120
(103; 140)

 

TAFINLAR (Dabrafenib)
- first line of treatment
- malignant melanoma of skin

2
(0; 8)

15
(9; 23)

AFINITOR (Everolimus)
- second and higher line of treatment
- metastatic breast cancer

47
(36; 62)

307
(279; 337)

 

*TAFINLAR (Dabrafenib) + MEKINIST (Trametinib)
- first line of treatment
- malignant melanoma of skin

10
(5; 19)

68
(55; 83)

AVASTIN (Bevacizumab)
- first line of treatment
- colorectal cancer

215
(190; 244)

1407
(1346; 1470)

 

YERVOY (Ipilimumab)
- first line of treatment
- malignant melanoma of skin

10
(5; 19)

68
(55; 83)

AVASTIN (Bevacizumab)
- second and higher line of treatment
- colorectal cancer

50
(38; 65)

330
(295; 370)

 

YERVOY (Ipilimumab)
- second line of treatment
- malignant melanoma of skin

7
(3; 14)

48
(37; 61)

ERBITUX (Cetuximab)
- first line of treatment
- colorectal cancer

59
(46; 75)

384
(352; 418)

 

*OPDIVO (Nivolumab)
- first line of treatment
- malignant melanoma of skin

8
(4; 16)

57
(45; 71)

ERBITUX (Cetuximab)
- second and higher line of treatment
- colorectal cancer

33
(23; 45)

215
(184; 250)

 

*KEYTRUDA (Pembrolizumab)
- first line of treatment
- malignant melanoma of skin

8
(4; 16)

57
(45; 71)

VECTIBIX (Panitumumab)
- first line of treatment
- colorectal cancer

59
(46; 75)

384
(352; 418)

 

AVASTIN (Bevacizumab)
- first line of treatment
- ovarian cancer

30
(20; 42)

181
(159; 205)

VECTIBIX (Panitumumab)
- second and higher line of treatment
- colorectal cancer

30
(20; 42)

200
(172; 232)

 

AVASTIN (Bevacizumab)
- second line of treatment
- ovarian cancer

12
(7; 21)

75
(61; 91)

ZALTRAP (aflibercept)
- second and higher line of treatment
- colorectal cancer

28
(19; 40)

184
(156; 217)

 

LYNPARZA (Olaparib)
- second line of treatment
- ovarian cancer

9
(4; 18)

51
(40; 64)

STIVARGA (regorafenib)
- higher line of treatment
- colorectal cancer

28
(19; 40)

184
(162; 208)

 

XTANDI (Enzalutamid)
- initial treatment
- prostate cancer

18
(11; 29)

115
(98; 134)

TARCEVA (Erlotinib)
- first line of treatment
- non-small-cell lung cancer

4
(1; 11)

31
(22; 42)

 

XTANDI (Enzalutamid)
- follow-up treatment
- prostate cancer

12
(7; 21)

74
(60; 90)

TARCEVA (Erlotinib)
- second and higher line of treatment
- non-small-cell lung cancer

28
(19; 40)

203
(173; 239)

 

JEVTANA (Cabazitaxel)
- follow-up treatment
- prostate cancer

12
(7; 21)

74
(60; 90)

ALIMTA (Pemetrexed)
- first line of treatment
- non-small-cell lung cancer

55
(42; 71)

396
(364; 430)

 

ZYTIGA (Abiraterone)
- initial treatment
- prostate cancer

15
(8; 24)

98
(82; 116)

ALIMTA (Pemetrexed)
- maintenance after the first line of treatment
- non-small-cell lung cancer

32
(22; 45)

230
(206; 257)

 

ZYTIGA (Abiraterone)
- follow-up treatment
- prostate cancer

9
(4; 18)

59
(47; 73)

ALIMTA (Pemetrexed)
- second line of treatment
- non-small-cell lung cancer

42
(30; 56)

297
(269; 327)

 

XOFIGO (radium-223)
- initial treatment
- prostate cancer

3
(1; 9)

16
(10; 24)

AVASTIN (Bevacizumab)
- first line of treatment
- non-small-cell lung cancer

25
(17; 37)

179
(158; 203)

 

XOFIGO (radium-223)
- follow-up treatment
- prostate cancer

9
(4; 18)

59
(47; 73)

IRESSA (Gefitinib)
- first line of treatment
- non-small-cell lung cancer

17
(10; 28)

124
(106; 144)

 

HERCEPTIN (Trastuzumab)
- first line of treatment
- stomach cancer

4
(1; 11)

30
(22; 41)

GIOTRIF (Afatinib)
- first line of treatment
- non-small-cell lung cancer

9
(4; 18)

62
(50; 77)

 

*CYRAMZA (Ramucirumab)
- second line of treatment
- stomach cancer

20
(12; 31)

138
(119; 159)

XALKORI (Crizotinib)
- second and higher line of treatment
- non-small-cell lung cancer

4
(1; 11)

28
(18; 43)

 

 

 

 

AVASTIN (Bevacizumab)
- first line of treatment
- renal cell carcinoma

11
(6; 20)

67
(54; 82)

 

 

 

 

SUTENT (Sunitinib)
- first line of treatment
- renal cell carcinoma

59
(46; 75)

373
(342; 406)

 

 

 

 

SUTENT (Sunitinib)
- second line of treatment
- renal cell carcinoma

15
(8; 24)

97
(81; 115)

 

 

 

 

INLYTA (Axitinib)
- second line of treatment
- renal cell carcinoma

14
(7; 23)

88
(73; 105)

 

 

 

 

NEXAVAR (Sorafenib)
- second and higher line of treatment
- renal cell carcinoma

3
(1; 9)

23
(16; 33)

 

 

 

 

TORISEL (Temsirolimus)
- first line of treatment
- renal cell carcinoma

18
(11; 29)

117
(100; 136)

 

 

 

 

AFINITOR (Everolimus)
- second line of treatment
- renal cell carcinoma

18
(11; 29)

111
(94; 130)

 

 

 

 

VOTRIENT (Pazopanib)
- first line of treatment
- renal cell carcinoma

32
(22; 45)

201
(178; 226)

 

 

 

 

VOTRIENT (Pazopanib)
- second line of treatment
- renal cell carcinoma

3
(1; 9)

23
(16; 33)

 

 

 

 

Prediction of numbers of patients newly indicated for targeted therapies of cancer in 2017 in regions of the Czech Republic – drugs without specified reimbursement.

Drug – diagnosis

SW Moravia

Czech Republic

TARCEVA (Erlotinib)
- first line of treatment
- pancreatic cancer

50
(38; 65)

317
(288; 348)

AVASTIN (Bevacizumab)
- glioblastoma

18
(11; 28)

137
(118; 158)